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Electric Energy System Planning and the
Second Principle of Thermodynamics
by
Delly Oliveira F.
A thesis submitted to the Faculty ofGraduate Studies and Research
in partial fulfilment ofthe requirement for the degree
ofDoctor ofPhilosophy
Department ofElectrical Engineering
McGiIl University
Montréal, Québec, Canada
<0 October 1995
1+1 National Libraryof Canada
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The author retains ownership ofthe copyright in hisjher thesis.Neither the thesis nor substantialextracts from it may be printe;:! orotherwise reproduced withouthisjher permission.
L'auteur a accordé une licenceirrévocable et non exclusivepermettant à la Bibliothèquenationale du Canada dereproduire, prêter, distribuer ouvendre des copies de sa thèsede quelque manière et sousquelque forme que ce soit pourmettre des exemplaires de cettethèse à la disposition despersonnes intéressées.
L'auteur conserve la propriété dudroit d'auteur qui protège sathèse. Ni la thèse ni des extraitssubstantiels de celle-ci nedoivent être imprimés ouautrement reproduits sans sonautorisation.
ISBN 0-612-12452-5
Canada
1.
•
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Abstract
This thesis deaJs with the long-tenn planning ofe1ectric energy systems. Such systems are
defined by complex interconnections of end-uses, energy conversion devices and natural
resources. The planning process is usually guided by a number of design criteria, namely,
economic, social and environmental impacts as weil as system re1iability and efficiency. The
planning challenge is to find an acceptable compromise among these often conflictive
objectives. System efliciency is a critical design criterion normally measuring the ratio ofthe
system output and input energies. In e1ectric energy systems, efficiency is nonnally defined
according to the First Principle of Thermodynamics which states that energy cannot be
destroyed. In this thesis, the definition ofefficiency in e1ectric energy system planning is
broadened to include interpretations aocording to both the F1I'st and Second Principles of
Thennodynamics. The Second Principle essentially states that the "quality" of energy
decreases or, at best, remains constant in any conversion process where the quality ofenergy
(denoted here by exergy) is a measure ofthe ability ofa fonn ofenergy to be converted into
any other form. Work, hydroelectric potential and e1ectricity are examples ofhigh quaIity
energy sources while low temperature heat end-use applications are at the low end ofthe
quality scale. Since certain types ofenergy conversion processes may show high levels of
excrgy destruction, even though energetically efficient, it is important to design energy
systems such that the energy quality ofan end-use is matched as much as possible to that of
the energy supply thus avoiding situations where a high quality supply is used for a low
quality purpose.
The e1ectric energy industry bas virtually ignoredexergetic considerations in system planning
due, to a large extent, to a Jack offamiliarity with the Second Principle and its implications.
Nevertbeless, exergy is an attn1>ute which must be planned and conserved with at least the
same priority as energy. It is demonstrated here that the planning ofenergy systems will be
drastically affected when both energy and exergy are considered. However, to be able to
ü
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Abstract
rationalIy use the natural resources, exergetic analysis must become an integral part ofsystem
plamüng. This thesis analyses the application ofthe Second Principle ofThermodynamics in
the plamüng ofe1ectric energy systems through theory, examples and case studies including
econonûc considerations.
In order to achieve e1ectric energy systems that are more exergetically efficient, a new type
of electric energy tariffcalled type-of-use. is proposed. Analogous to the time-of-use rate
that assigns different monetary values for the time ofthe day considered, the type-of-use tariff
assigns a monetary value to the end-uses. Simulations are performed in different e1ecuic
energy systems to demonstrate that type-of-use tariffs will indeed lead to more exergetically
efficient system!:.
The benefits of exergetic analysis are supported by a number of studies presented in this
thesis. These studies analyse from the points ofview ofenergetic and exergetic efficiency and
cost the foDowing: (i) A space heating system; (u) The impact ofa major introduction of
e1ectric vehicles in Canada and (Ù!) The long range planning of a regional electric power
system consisting oftwo intercoMeeted provinces.
iii
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Résumé
Cene thèse traite le problème de planification à long tenne des réseaux d'énergie électrique.
De tels réseaux sont définis par des liens complexes entre les utilisations finales de l'énergie,
les appareils de transformation d'énergie et les ressources naturelles. Le processus de
planification s'oriente par divers critères de conception, c'est à dire, l'impact socia
économique et environnementale bien que la fiabilité et l'efficacité. Le défi de la planification
est de trouver un compromis acceptable entre ces objectifs souvent en conflit. L'efficacité du
réseau est un critère vital qui mesure normalement le rapport entre l'énergie totale à l'entrée
du système et celle à la sortie. Dans les réseaux électriques, l'efficacité est typiquement définie
selon le Premier Principe de Thennodynamique qui stipule que l'énergie ne peut pas être
détruite. Dans la thèse présente, la définition d'efficacité dans la planification de réseaux
d'énergie électrique est étendue pour inclure des interprétations selon le Premier bien que le
Deuxième Principe de Thermodynamique. Le Deuxième Principe établie que la "qualité"
d'énergie décroît ou, tout au mieux, se maintien constante dans tous les processus de
conversion d'énergie. La qualité de l'énergie, dénommée exergie, est une mesure de la
capacité d'une forme d'énergie donnée d'être convertie à n'importe quelle autre forme. Le
travail mécanique, le potentiel hydraulique et l'électricité sont des exemples de sources
d'énergie de haute qualité pendant que les applications utilisant de la chaleur à basse
température sont situées très bas dans l'échelle de la qualité de l'énergie. Vue que certains
types de processus de conversion démontrent de forts niveaux de destruction d'exergie,
même s'ils sont efficaces du point de vue de l'énergie, il est important de bâtir les réseaux
d'énergie de telle manière que la qualité de l'énergie des usages finaux so:t compatible autant
que poSSIble avec la qualité des ressources naturelles. De cette façon, des cas sont évités ou
une source de haute qualité est utilisée pour un usage finale de basse qualité.
L'industrie électrique a pratiquement ignoré des considérations exergetiques dans la
planification de réseaux, principalement due à une manque de familiarité avec le Deuxième
iv
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Résumé
Principe et tout ses implications. Néanmoins, l'exergie est un attribut qui doit être planifié et
conservé avec, au moins, la même priorité que l'énergie. Il est démontré ici que la
planification des réseaux électriques sera dramatiquement affectée quand les deux critères
d'énergie et d'exergie sont traités. Cependant, pour pouvoir utiliser d'une façon rationnelle
nos ressources naturelles, l'analyse exergetique doit se convertir dans une partie intégrale du
processus de planification. Cette thèse analyse l'application du Deu.'CÎème Principe de
Thermodynanùque à la planification des réseaux électriques à travers la théorie, des exemples
et des études de cas particuliers incluant des considérations économiques.
Afin d'obtenir des réseaux électriques qui sont plus efficaces exergetiquement, une nouvelle
tarife d'énergie électrique dénommée la tarife type-d'usage est proposée. D'une manière
analogue à la tarife heure-du-jour, qui établie une valeur monétaire de l'énergie électrique
pour chaque période du jour, la tarife type-d'usage établie une valeur monétaire sur les
usages finaux de l'énergie.
Les bénéfices de l'analyse ex:ergetique sont supportés par des études décrites dans cette thèse.
Ces études analysent du points de vue de l'efficacité énergétique et ex:ergetique et
économique ce qui suit: (i) Un système de chauffage résidentiel; (ii) L'impact de
l'introduction des véhicules électriques au Canada; (m) La planification à long terme d'un
réseau régional consistant de deux provinces interconnectées.
v
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Resumo
Esta tese trata do planejamen:o de longo prazo de sistemas de energia elétrica. Tais sistemas
sao projetados de acôrdo corn complexas relaçêies entre 0 uso finaI da energia, aparatos de
conversao e recursos naturais. 0 processo de planejamento é geralmente orientado por um
numero de critérios notadamente: impactos socio-econêmico e ambiental, bem coma a
confiabilidade e eficiência do sistema 0 desafio do planejamento é de se encontrar um
compromisso entre estes objctivos frequentemente conflitivos. A eficiência do sistema é um
critério de planejamento vital e é definido pela raziio entre as energias de saïda e de entrada
Nos sistemas de energia elétrica, eficiência é norma1mente definida de acêrdo corn 0 Primeiro
Principio da Termodinâmica, que estipula que a energia nao pode ser destruida Nesta tese
a definiçiio da eficiência para 0 planejamento de sistemas de energia eletrica é expandido para
inc1uir a interpretaçiio niio somente de acordo corn 0 Primeiro Principio mas também corn 0
Segundo Principio. 0 Segundo Principio da Termodinâmica essencialmente e,;tabelece que
a qualidade da energia decresce ou no me1hor dos casos permanece constante em qualquer
processo de conversao da energia A qualidade da energia, denotada aqui por exergia, é a
capacidade da energia de se converter em qualquer outra forma 0 trabalho mecânico, 0
potencial hidrâu1ico, e a eletricidade sao exemplos de fontes de energia de alta qualidade.
Enqllanto a aplicaçiio da energia a baixa temperatura estiio no fim da escaIa de baixa
qualidade. Visto que, certos tipos de conversao da energia podem ter altos niveis de
destruiçiio da exergia apesar de serem energeticamente eficientes, é importante que se projete
sistemas de energia elétrica de ta! modo que a qua1idade da energia de um dado !ISO finaI seja
compative\, tanto quanto possive\, corn à do suprimento da energia
o setor de energia elétrica tem virtualmente ignorado consideraçêies exergéticas no
planejamento de sistemas devido principalmente a falta de familiaridade corn 0 Segundo
Principio da Termodinâmica e de todas as implicaçêies decorrentes. Antes de mais nada,
vi
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Resumo
exergia é uma grandeza que deve ser considerada no planejamento pelo menos corn a mesma
prioridade da energia. Se demonstra aqui, que 0 planejamento de sistemas elétricos seradramaticamente afutado quando energia e exergia forem considerados. Todavia, para ser
capaz de utiIizar racionamente os recursos naturais, a anâlise exergética deve se tornar uma
parte integrante do processo de planejamento de sistemas de energia e1étricos. Esta tese
analisa a aplicaçao do Segundo Principio da Termodinâmica no planejamento de sistemas de
energia e1étrica através de teoria, exemplos e de estudos de cases particu\ares, incluindo
consideraçOes econômicas.
Afim de alcancar sistemas de energia e1étrica que sejam mais eficientes exergeticamente, um
novo tipo de tarifa de energia, denominada tipo-de-uso, é proposto. Do mesmo modo que a
tarifa hora-do-dia que estabe1ece um valor monetârio para cada um dos interva10s do dia
considerado, a tarifa tipo-de-uso estabeIece umvalor monetârio para os usos finais da energia
considerados. SimnlaçOes sao feitas em diferentes sistemas e1étricos para desmonstrar que a
tarifa tipo-d~uso ira certamente induzir sistemas e1étricos mais eficientes exergeticamente.
Os beneficios da anâIise exergética siio confirmados por um mimera de estudos apresentados
nesta tese. Estes estudos ana1isamdos pontos de vista, da eficiència energética, exergética e
econômico, os seguintes cases: (i) sistemas de aquecimento do ambiente, (ri) 0 impacto da
introduçio de carros e1étricos no Canada e (üi) 0 p1ant<jamento de longo prazo de um sistema
regional de potència consistindo de duas provincias.
vü
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AcknowIedgments
FJIStly, 1would like to thank God through Jesus Christ, because 1really have proven that He
is a great loving Father.
My sincere thanks to Professor Francisco D. Galiana for his knowledgable supervision,
encouragement and warm fiiendship, throughout this research. Without any doubt, 1 can say
that 1had the privilege, to say the least to have been supervised by Professor Galiana.
1 would Iike to thank Professor R Baliga, Professor R Banakar, Professor B. Gevay and
Professor B. T. Ooi for their support during my study.
1am thankful to my fiiends and colleagues in the Power Group. It was a great opportunity
to get to know and share experiences with fiiends with such a rich acadernic and cultural
background. 1 would Iike to thank Lester Loud, John Cheng, Luiz Lopes, Dr. Houssein
Javidi, Djordje Atanackovic, Bakari Mwinyiwiwa, Nivad Navid, George Jaber, Dr. Mherdad
Kazerani. 1 would Iike to thank as weil to the secretaries of the Department ofEleetrical
Engineering ofMcGiII University, Mrs P. Hyland, Mrs. R Pinzarrone and Mrs P. Jorgensen.
1 am very thankful to CAPES (Coordenadoria de Aperfeiçoamento de Pessoa! de Ensino
Superior) and to the FederaI University ofViçosa for the financial support that gave me this
unique opportunity.
1would Iike to thank, as weil, Mrs. E. Woolerton for giving me encouragement and support.
Last but not least, 1would Iike to thank my family, starting with my dear wife Luci for ber
support and incommensurable sacrifices, that aIIowed me to reaIize this objective. Thank you,
Acâcia, Liz and Ivo, you are wonderful children. 1 am blessed to be your failier, thank you
for your love.
viü
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• ix
To
my dear wife Luci
and
our children Acacia, Liz and Ivo
• Table of Contents
Abstract 11
Résumé IV
Resumo vi
Acknowledgments viii
Table of Contents x
List of Tables xv
List ofmustrations xix
Nomenclature xxi
Chapter 1. Introduction 1
1.1 Planning ofEIectric Energy Systems 1
• 1.2 Concepts ofExergy and Exergetic Efficiency 5
1.3 Motivation for Using the Second Principle in 7
EIectric Energy System Planning
1.4 Objectives oftlùs Thesis 9
1.5 Thesis Outline 10
1.6 Claim ofOriginality Il
•
Chapter 2. First and Second Principles ofTbermodynamics
2.1 Energetic and Exergetic Efficiency
2.2 Energy, Exergy and Entropy
Chapter 3. Electric Energy System Model
3.1 Motivation
3.2 Basic System Model
3.3 Mathematical Energy System Model
x
13
13
19
23
23
24
26
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Table of Contents
3.4 Example ofMathematical Model
3.5 Energy System Optimization
3.6 Computer Model
3.7 Concluding Remarks
Chapter 4. Applications of Exergy Analysis in Electric Energy
System Planning
4.1 Introduction
4.2 Linùting Levels ofFPT and SPT Efficiencies
4.3 Demand Side Management Perfonnance Improvement
4.3.1 Basic energy conversion model element
4.3.2 Model with cross-effects
4.3.3 System impact ofDSM perfonnance improvement
strategies description ofcase-studies
4.3.4 Evaluation ofPI measures
4.3.5 Comparison of savings at different system levels
4.3.6 Comparison ofenergetic and exergetic savings
4.3.7 Comparison ofdifferent perfonnance improvement measures
4.3.8 The effeet ofdifferent climates and dwelling insulation levels
4.4 Energetic and Exergetic Impact ofElectric Vehicles in Canada
4.4.1 Introduction
4.4.2 Evaluation ofe1ectric vehicle (EV) and internai combustion
engine vehicle (lCEV) efficiencies
4.4.3 Energy system with EV and ICEV
4.4.4 Petroleum displacement by EV
4.4.5 Energy supply for EV
xi
31
35
42
42
43
43
46
53
54
57
60
62
64
65
66
68
68
68
70
73
80
82
5.1
5.2
5.3
• 5.4
5.5
5.6
•
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Table of Contents
4.5 Conc1uding Remaries
4.5.1 Limiting IeveIs ofSPT and FPT efficiencies
4.5.2 DSM perfonnance improvement inc1uding cross-effects
and exergetic anaIysis
4.5.3 Electric vehic1es and exergetic analysis
Chapter 5. Economie and Exergetic Optimization Analysis
ofSpace Heating Systems
Introduction
Space Heating Model
Economie Analysis ofSpace Heating
Optimization with Mixed Objectives
Implementation ofDesired Optimum Solutions
Closure
Chapter 6. Exergetic Optimal Regional Planning
6.1 Introduction
6.2 Region Characterization and Model Description
6.2.1 Regional planning model
6.2.2 Estimation ofthe end-uses for Québec and Ontario for 1995
6.2.3 Limiting levels ofFPT and SPT efficiencies
6.3 Regional Planning Optimization Studies
6.3.1 Québec-Ontario 1995 system
6.3.2 Base case constraints for regional planning
6.3.3 Impact oftransmission line capacity
6.3.4 Comparison ofthe 1995 case with the maximum SPT system
xii
87
87
87
88
90
90
92
95
103
113
118
120
120
122
125
129
133
136
139
142
144
148
• Table of Contents
effieiency solution
6.3.5 Upper bound limits relaxation 152
6.3.6 Exergetie or type-of-use tariffs 154
6.4 Coneluding Remarks 158
Chapter7. Conclusions and Recommendations for Future Research 163
7.1 General Conclusion 163
7.2 Specifie Conclusions 163
7.2.1 Exergetie ana1ysis in the context ofIntegrated Resouree 164
Planning
7.2.2 Deve10pment ofan energetic and exergetie generaI model 165
for the design and ana1ysis of e1ectric energy systems
• 7.2.3 Demonstration ofthe impact ofexergetic considerations 166
on the planning process ofe1ectric energy systems
7.2.4 Integration ofenergetic, exergetic and economic ana1ysis 167
7.2.5 Energetic and exergetic regional optimization studies 168
7.2.6 A proposition ofa new kind ofe1ectric rate, type-of-use 170
tariffs, that incorporate exergetic considerations
7.3 Recommendations for Future Work 171
•
References 173
Appendix A. First and Second Principle Efficiencies for DilTerent System 184
Configurations
Appendix B. Energetic and Exergetic Savings at DilTerent System Levels 187
for DSM Performance Improvement
Appendix C. Estimation of the End-uses for Ontario and Québec in 1995 190
xili
• Table of Contents
C.I Ontario End-uses 191
C.U Space-heating end-use in Ontario 191
C.1.2 Space-heating end-use in Ontario 192
C.l.3 Water heating end-use in Ontario 193
C.1.4 Lighting end-use in Ontario 193
C.I.S Traction end-use in Ontario 195
C.2 Québec End-uses 196
C.2.l Space heating end-use in Québec 196
C.2.2 Cooking end-use in Québec 196
C.2.3 Water heating end-use in Québec 197
C.2.4 Lighting end-use for Québec in 1995 198
C.2.5 Traction end-use for Québec in 1995 199
•
• xiv
• List of Tables
Table 2.1 F1I'St (Tl) and Second (e) Principles efficiencies and percent exergy 17
in the input (a,) and output (aJ energies.
Table 3.1 Data for the example ofFigure 3.2. 32
Table 3.2 Energetic and exergetic relations for Figure 3.2. 34
Table 3.3 Numerica1 examples ofefficiencies for extxeme design objectives. 37
Table 3.4 Energy and exergy relations as function ofe, and ~. 37
Table 4.1 End-uses, end-uses devices and natura1 resources considered. 45
Table 4.2 Main system configurations. 46
Table 4.3 Main system configurations in decreasing order ofefficiency. 47
Table 4.4 Energy system configurations considered. 60
Table 4.5 Energy and exergy savings at the appliance level. 61
Table 4.6 Energetic savings at different system levels for 62
PI '1mproved Refrigerator'.
• Table 4.7 Exergetic savings at different system levels for 63
PI '1mproved Refrigerator'.
Table 4.8 Use ofthe energy in an typica1 gasoline powered ICEV. 67
Table 4.9 Electric vehicle characteristics. 69
Table 4.10 Forecast fuel consumption (kmIl) and weight (kg) of ICEV. 70
Table 4.11 F1I'St (Tl) and Second (e) Principle efficiencies for ICEV and EV. 71
Table 4.12 Configurations considered for road transportation. 72
Table 4.13 First Principle efficiency for eight configurations for 75
road transportation in 1995.
Table 4.14 FII'St Principle efficiency for eight configurations for 76
road transportation in 2010.
Table 4.15 FII'St and Second Principle efficiencies for 77
ICEV and EV different configurations.
Table 4.16 E1ectric energy production for difi'etent fuel types in Canada, 1992. 78
• Table 4.17 EV efficiencies in the Canadian provinces. 79
xv
• List of Tables
Table 4.18 Pettoleum displacement by the adoption ofEV in 1995 and 2010. 81
Table 4.19 Percent ofelectric energy consumption above the present level 83
due to by EV in the Canadian provinces, in 1995 and 2010.
Table 4.20 Yearly consumption ofspace heating alternatives and 84
electric energy conserved to replace an electric baseboard.
Table 4.21 Savings characteristics to replace electric baseboard heater by 85
more exergetically efficient options in terms ofroad transportation
end-use in 1995 and 2010.
Table 5.1 Relevant economic data for different space heating alternatives. 96
Table 5.2 Average Iife cost.~ to customers for di1ferent space heating alternatives. 100
Table 5.3 Energy, maintenance and capital average costs at the customer 101
Ieve\ for different space heating optiOI:S for Ontario.
• Table 5.4 Energy, maintenance and capital costs at the customer Ieve\ for 101
different space heating options for New York.
Table 5.5 Energy, maintenance and capital costs at the customer Ieve\ for 102
di1ferent space heating options for Québec.
Table 5.6 Best space heating design as a function ofthe minimiZl'tion 103
criterion, unconstrained case.
Table 5.7 Optimizarion criterion and objective function considered for the 104
space heating model analysïs.
Table 5.8 Optimum energy states for di1ferent oprimizarion criteria. 105
Table 5.9 Optimum exergy states for different optimization criteria. 106
Table 5.10 Cast and efficiencies orthe space heating for di1ferent 108
optimum criteria.
Table 5.11 Minimum energy/exergy weights (c/kWh) in the Iinear programming 113
objective to force the solution to be equal to the minimum Xa solution.
• Table 5.12 Minimum % subsidies for varying oPPOrtunity cost rates in the initial 115
xvi
• List of Tables
•
•
Table 5.13
Table 6.1
Table 6.2
Table 6.3
Table 6.4
Table 6.5
Table 6.6
Table 6.7
Table 6.8
Table 6.9
Table 6.10
Table 6.11
Table 6.12
Table 6.13
. Table 6.14
Table 6.15
Table 6.16
Table 6.17
Table AI
capital ofthe heat-pump ground-to-air to induce the minimum
exergy and minimum cost solutions to be identical in Québec.
Heat-pump ground-to-air initial capital subsidy and maximum rate 117
for the minimum solution XRbe the minimum cost solution.
Important supply and load charaeteristics in Québec and Ontario 124
in 1995.
States considered for Québec and Ontario. 126
End-use energy for Québec in 1995. 131
End-use energy for Ontario in 1995. 132
Fraction ofthe e1ectric consumption covered by the regional 133
planning study in %.
Cases Iimiting the values ofthe First Principle efficiency, Tl. 134
Cases limiting the values ofthe Second Principle efficiency, E. 135
Summary ofcases studied in regional planning. 137
Energy and exergy states considered for Québec and Ontario for 1995. 140
Upper bound (base case) state limits considered for regional planning. 143
SPT efficiency, for max E, for increasing values oftransmission 145
line capacity.
SPT efficiency, for max Tl, for increasing values oftransmission line 146
capacity.
Comparison of 1995 and Min xRsolutions in Québec. 149
Comparison of1995 and Min xRsolutions, in Ontario. 150
Lagrange multipliers for seleeted states for minimum exergy. 153
Objective function for exergetic tariffdesign. 155
Summary ofcases studied in regional planning. 157
FPT efficiency, Tl, ofend-use devices for various system 185
xvii
• List of Tables
configurations (%).
TableA2 SPT efficiency, e, ofend-use devices for various system 186
configurations (%).
TableB.l Energetic savings at different sys~em 1~'Vels for PI 'Efficient Electric 188
Water Heater'.
TableB.2 Exergetic savings at different system levels for PI 'Efficient Eectric 188
Water Heater'.
TableB.3 Energetic savings for PI 'Replacement ofIncandescent by Compact 189
Fluorescent Light Bulbs'.
Table BA Exergetic savings for PI 'Replacement ofIncandescent by Compact 189
Fluorescent Light Bulbs'.
TableC.l Energy consumption for the space heating end-use devices in 191
• Ontario, 1995.
TableC.2 Energy consumption for the cooking end-use devices in Ontario, 192
1995.
TableC.3 Energy consumption for the water-heating end-use devices in Ontario, 193
1995.
Table CA Energy consumption for the Iighting end-use devices in Ontario, 1995. 194
TableC.5 Energy consumption for traction end-use devices in Ontario, 1995. 195
TableC.6 Energy consumption for space heating end-use devices in Québec, 196
1995.
TableC.7 Energy consumption for the cooking end-use devices for the residential197
sector in Québec, 1995.
TableC.8 Energy consumption for the water heating end-use devices, for the 197
residential and commercial sectors in Québec, 1995.
TableC.9 Energy consumption for the Iighting end-use in Québec, 1995. 198
Table C.I0 Energy consumption for traction end-use devices in Québec, 1995. 199
• xviii
• List of IHustrations
Figure 1.1 Electric energy system. 2
Figure 1.2 The energy planning challenge - balance ofdesign criteria 4
and perspectives.
Figure 2.1 Basic energy conversion e!ement. 15
Figure 3.1 Composition ofa generai energy system. 25
Figure 3.2 DIustrative example ofelectric power system. 33
Figure 3.3 Feasible region. 39
Figure 3.4 Ftrst and Second Principle efficiencies optimization aspects. 41
Figure 4.1 Space heating mode\. 44
Figure 4.2 Second, E, and First, Tl, Principle efficiencies for the end-use 48
space-heating.
Figure 4.3 Second, E, and First, Tl, Principle efficiencies for the end-use 49
• cooIàng.
Figure 4.4 Second, E, and First, Tl, Principle efficiencies for the end-use 50
water heating.
Figure 4.5 Second, E, and First, Tl, Principle efficiencies for the end-use 51
traction.
Figure 4.6 Second, E, and First, Tl, Principle efficiencies for the end-use 52
Iighting.
Figure 4.7 Energy conversion element. 55
Figure 4.8 typical subsystem containing cross-effects. 58
Figure 4.9 Road transportation mode! for internaI combustion engine. 74
vehicles and e!ectrical vehicles.
Figure 4.10 Two natura! resources and end-uses mode!. 82
Figure 5.1 Space heating mode!. 93
Figure 52 F1t'st, Tl, and Second, E, Principle efficiencies for different lIO
• optimization criterion.
xix
• List of Illustrations
•
•
Figure 5.3
Figure 6.1
Figure 6.2
Cost ofthe space heating for different optimization criteria.
for New York, Ontario and Québec.
Model for regional planning.
Second Principle efficiencies for increasing values of
transmission line limits.
xx
III
121
147
• Nomenclature
ac average cost over the life time
Ac matrix ofenergy states ( Ac E R( mX"l)
A. matrix ofexergy states ( Ax E R( mx'l)
ait end-use device alternative
b set ofupper bound limit
b. veetor ofenergy end-uses ( b. E Rm)
bx veetor ofenergy end-uses ( bx E Rm)
BB electric baseboard heater
BL biomass liquefaetion
BP biomass production
BT biomass transport
• Cu cross-effeet
c cost to the customer
Co cost at the energy conversion device leve1
C cooling end-use
Cl, C2, C3 cooking system configurations
Cl,... C6 energy system configurations
~ consumption ofEV
~CEV consumption ofICEV
CF crude refinery
C; energy conversion device i
CK cooking
CM coalmining
co coal natural resource
Cr consumption ratio ICEV and EV
• CR crude recovery
xxi
• Nomenclature
CT crude transport
d petroleum displacement
D driving distance
D diagonal matrix made up ofthe coefficients 0:'0 (D lE R(UO»
DC direct cooking fumace
DH direct oil space heater
DSM Demand Side Management
DW direct water heating
el input energy
~ output energy
e; energy at state i
EL efficient lighting
• ~ energy losses
!la energy at the natura! resource level
EC energy conversion device
EC e1ectric cooking fumace
EM efficient motor
Eq equivalent gasoline savings
eu; energetic content ofa given end-use i
EUi end-uses i
EV E1ectric Vehic1es
EXAM EXergy Analysis Model
EW electric water heating
f objective function, in the optimization procedure
gs natura! gas resource
GE gas extraction and gathering
GT gas transport• xxii
• Nomenclature
ICEV Internai Combustion Engine Vehicles
IM inefficient motor
IL inefficient lighting
IRP lntegrated Resource Planning
FPT First Principle ofThermodynamics
FT fuel oil transportation
GT gasoline transport
H heating end-use
HL heating load
Hp-aa air-to-air heat pump
Hp-ga ground-to-air heat pump
hy hydro energy resource
• 1 illumination end-use
ic capital cost
IC initial capital cost
1 expected number ofyears in the life ofthe device
LI, L2, L3, L4 lighting system configurations
If load factor
LC present life cost
LR syncrude refinery
LT syncrude transport
m number ofend-uses
m maintenance cost per year as a fraction ofthe initial cost
max(x) maximum value ofx
min(x) minimum value ofx
M electric motors
n number ofequalities constraints• xxiü
• Nomenclature
n number ofhours ofoperation per year
n.. number ofenergy conversion devices
n... number ofend-uses
n.. number ofpower plants
fi,. number ofnatural resources
n,.. number ofrefineries
n.. number ofpower plants
n.r number oftransportation offuel systems
n.t numberofttarurnn~onlines
!InI number oftransportation ofnatura! resources systems
NR natural resources
nu nuclear energy resource
• 01 petroleum natura! resource
ON Ontario
om operation and maintenance costs
p opportunity cost rate
P. pressure at the reference state
P_B power plant biomass
P_C power plant coai
P_G power plant natura! gas
P_H,PP-hy power plant hydre
P_O power plant petroleum
PI performance improvement measure
PP power plant
PP-th thermoelectric power plant
q heat transfer per unit ofmass
Q heat transfer• xxiv
• Nomenclature
QB Québec
1'; electric tariff or fuel rate
R-hy hydro resources
RT refined transport
R-th thermal resources
RE refinery
R; natura! resource i
s expected energy cost esca1ation rate
Sj entropy per unit mass ofthe initial and final states
S entropy ofthe state relative to the reference state
SI, S2... S7, S8 space heating system configurations
S· entropy ofthe thermo-mechanica1 dead state
• SR space heating
SPT Second Principle ofThermodynamics
SSM Supply Side Management
T absolute temperature, in Kelvin
T traction
Tl, T2, TI, T4 traction system configurations
T_l coal transport type 1
T_2 coal transport type 2
To reference temperature, in Kelvin
TI temperature ofthe heat source, in Kelvin
T2 temperature ofthe cold sink, in Kelvin
'ID transmission line and distribution system
TF transportation offuel
TL transmission line
TN transportation ofnatura1 resources
• xxv
• Nomenclature
TR transportation device
U1,2 upper bound limits for states 1 and 2
U internaI energy ofthe state relative to the reference state
u" internaI energy ofthe dead state
V volume ofthe state relative to the reference state
V' volume ofthe thermo-mechanical dead state
wi weighting factors in the objective function
WEV we~htofclectricverucle
W1CF:V weight ofinternai combustion engine verucle
Wr efficiency loss factor
WH water heating
Wl,W2,W3 water heating system configurations
• X exergy
~ exergy content in a chemical process
x.... exergy content in the clectricity
X- exergy content in a gravitational ficld
x... exergy content in the kinetic energy
x..,. exergy content in the Iight
x... exergy content in a thermo-mechanical process
".t exergy destruction per unit ofmass
x.s... exergy destruction
XI input exergy
x2 output exergy
xa exergy at the natura1 resource levcl
X; exergy at state i
X.... exergy losses
• XII; exergetic content ofa given end-use i
xxvi
• Nomenclature
y vector ofenergy and exergy states ( y E R:lm)
() refers to the thermo-mechanica1 dead state ofthe system
et proportion ofa exergy in a given energy source
etl proportion ofexergy in the input energy
~ proportion ofexergy in the output energy
et", proportion ofexergy at the end-use
cr. proportion ofexergy at the naturaI resource
etail proportion ofexergy in oil
cr.-. proportion ofexergy in water
cr.- proportion ofexergy in traction
~ proportion ofexergy in low temperature heat
etail proportion ofexergy in oil
• E Second Principle ofThermodynamics efficiency
e.... maximum exergetic efficiency
En. exergetic efficiency ofa thermoelectric power plant
Elly exergetic efficiency ofa hydroelectric power plant
EM exergetic efficiency ofa electric motor
EDR exergetic efficiency ofa direct oil space heater
EBB exergetic efficiency ofa electric baseboard heater
TI FII'st Principle ofThermodynamics efficiency
TlAC air-conditioning coefficient-of-performance
TJEV electric vehicle efficiency
TlICEV internzl combustion engine vehicle efficiency
TIL lighting alternative efficiency
TlSH space heating device efficiency
TI.... maximum energetic efficiency
• TIn. energetic efficiency ofa thermoelectric power plant
xxvii
•
•
•
Nomenclature
Po,;
ô
energetic efficiency ofa hydroelectric power plant
energetic efficiency ofa e1ectric motor
energetic efficiency ofa direct oil space heater
energetic efficiency ofa e1ectric baseboard heater
Carnot efficiency
subsidy level
variation in a given parameter or variable
chemical potential ofsubstance i at the thermo-mechanical dead state
chemical potential ofthe substance i at the reference state
adjust on the weighting function for the hydro potential natural resource
for optimization purposes
xxviii
•
•
•
Introduction
Chapter 1. Introduction
1.1 Planning of Electric Energy Systems
Electric energy systems form one ofthe most vital components of life-support systems in
modern-day societies. It is therefore essentia1 to he able to plan the best system possible
based on the following genera11y accepted design criteria:
(i) Reliabi1ity,
(ù) Efliciency,
(m) Environmental impact,
(IV) Socioeconomic consequences.
The cha11enge of system planning is to find an appropriate balance among these often
conflieting objectives.
1
•
•
Introduction
•••
•••
• •• •• •C
C.- -,--,-Lqud
Jt - ..tlIl'111 .....lUUIC - aera collvenlo. devlcesEU • OIUI-lIICS
2
•
Figure 1.1 E1ectric energy system.
An electric energy system of the general type shown in Figure 1.1 is composed of the
following three main constituentparts:
(a) Natural energy resources,
(b) Energy conversion processes,
(c) End-uses.
Hydraulic potential, petroleum, coal, nuclear minerais and natural gas are examples of
natural resources. The second set ofconstituent parts consists ofseverallayers ofenergy
conversion, transmission or transportation devices wbile end-uses refer to energy services
(e.g., heating, traction and Iight).
• Introduction 3
•
•
Note that the design of an e1ectrie energy system must also inelude non-e1ectrie energy
conversion devices and their respective supplies since the planning ofelectrie energy systems
cannot he carried out in isolation. This is evident because some end-uses can be supplied from
both electrie and non-e1ectrie energy sources. The methodology of Integrated Resource
Planning (IR.P) bas been deve10ped witll these broad considerations in mind [Rosen et al,
1993, Litchiie1d et al, 1994].
In planning e1ectrie energy systems, the emphasis placed on eaeh ofthe four main planning
criteria bas varied over the years. Today, environmental impact (e.g., toxie emissions from
power plants) bas acquired even greater importance than in the pasto Capital, operational and
maintenance costs have always been and will continue to be a very high priority planning
criterion although the least cost solution must be moderated by acceptable levels of
environmental impact, efficiency and reliability as we1I as job creation and other social impacts
[Northwest, 1991]. In the IRP context, costs may refer to the utility costs or to those borne
by individual customers or by society [Litchiie1d et al, 1994). The reliability criterion is
normally satisfied through certain minimum standards expected by society in terms ofthe
average number ofpower outages per year and their average duration [Endrenyi, 1978). The
reIiabiIity standards demanded by modern societies are very high due to their ever increasing
dependency on a continuous and ample supply ofe1ectrie energy. Before the first oil crises
of the 197CYs, efficiency had a relatively low priority however increasing fue1 and investment
costs have forced planners to place a much greater significance on the efliciency ofindividual
energy conversion components as we11 as that of the e1ectrie energy system as a whole
[Boustead & Hancock, 1979; Talukdar & Ge1Iings 1987]. Ofthe four main planning criteria,
efficiency and reliability are precisely qllantifiab1.e since they are based on we11 supported laws
of physics and statistics. However, environmental and socioeconomie impacts are more
subjective and usua1ly ref1eet the vaIue placed by society and the market on resources,
services and the protection of the environment. The great hurdle to overcome in the
integrated planning process is to obtain a compromise among the four design criteria, a task
• Introduction 4
•
•
Figure 1.2 The energy planning challenge - balance ofdesign criteria and perspectives.
wbich is complicated by the1àct that iliese objectives do not usually coïncide. See Figure 1.2.
Diftèrentpe~ctives can be followed to assess and implement a given planning sttategy,
namely those of
• The utility,
• The customer,
• Society
From the utilitypoint ofview, the broad objectives are to improve the financial performance
• Introduction 5
•
•
as weil as customer and employee relations [Rosen et al., 1990; EPRI, 1993]. Other utility
objectives include the maximum possible use ofits generation and transmission capacity. the
deferral ofgeneration and transmission expansion plans and the reduction ofthe utility's
dependence on critical fuels. In general, the customer is primarily concemed with energy
rates and supply reliability. The society peispectives encompass at least four major objectives:
macro-eeonomie impacts (e.g., job generatio:l, country development and tax-revenue),
regulation oftariffs and reliability indices, country strategie constraints (e.g., reduction of
eritical technology and fuel dependency) and minimization of environment damage
(emissions, waste disposai, land use). Clearly, there exist conflicts among the three points of
view. For example, the cost objectives ofa utility are not synehronized with those ofthe
customer. Similarly, society is extremely interested in the creation ofjobs which may not be
a high priority objective for the uti1ities. The proper balance between these conflicting
perspectives and objectives bas been studied under the umbrella of Integrated Resource
Planning [Rosen et al. 1993; Hobbs et al. 1993].
1.2 Concepts ofExergy and Exergetic Efficiency
The use ofthe Second Principle ofThennodynamics1 is weil estabIished in numerous fields
such as mechanical and chemical engineering [MacGovem, 1990; Wepfer, 1979; KIenke,
1991; Boustead & Hancock, 1979]. Through this approach, efticiency is measured by two
dimensions. That is, not only by the conventional input/output energy balance as defined by
the First Principle but also by a second dimension ofefticiency in terms ofenergy quaIity
1 In the 1840'5Mayer lIIId JouIe sbowcdtbat thermodynamics is IlOt restrictcd oaly ta bcat
transfcr studies but CI1lXlIDpasses olbcr fonDs ofœcrgy. Mee gœcraIly, thermodynamics cm he
intcrpretcd as energydynamics.
• Introduction 6
•
•
denoted here by exergy. Qua1ity in energy conversion can be quantified through exergetic
analysis based on the Second Principle of Thennodynamics [Oliveira & GaIiana, 1995a;
Gardner& Robinson, 1993]. The quantitative analysis ofthe qua\ity ofenergy bas numerous
implications in the design ofe\ectric energy systems as discussed in this article. Note that,
throughout this thesis, the words Law and Principle are used interchangeably.
The tenn exergy, derived from the Greek, is also known as essergy, availability, free energy
and usefuI energy [Wepfer, 1979]. Exergy is usua\Iy interpreted as avai1able worle. Exergy
represents the fraction ofa form ofenergy that can be converted to any other arbitrary form.
This characteristic is ca1led reverstbility.
To clarify the distinction between energy and exergy, it is important to observe that in
energetic analysis the energy in a given source ofenergy can be considered as constant (e.g.,
45,475 kJJkg ofoil, 37,260 kJ/m3 ofnatural gas)[Québec, 1992]. In contrast, the exergetic
content ofa given source ofenergy is the amount ofkJ ofwork that can be extraeted from
this source. Exergy is not only a function of the source of energy but of the existing
technology for the extraction ofworlc from the given source. For example, the exergy in
e\ectricity is deteimin\ld by the most energetica1ly eflicient e\ectric motor presently available.
As another example, the exergy in a heat source bas a theoreticaI upper bound determined by
the ideal Camot efliciency [Klenke, 1991]. Low temperature heat bas a very low exergy
content in contrast to e\ectricity or mechanicaI worlc which bas a high exergetic content since
the)' .::an be more efliciently converted to other forms ofenergy. In essence, the higher the
reversibility ofa form ofenergy, the higher the qua1ity that is assigned to it. In contrast to
energy which can never be destroyed, some amount of exergy is always irreversIbly lost
during any energy conversion process. Simi1arly to energy conservation, it is important to
minimize the irreversible destruction ofthis valuable resource which is exergy.
• Introduction 7
1.3 Motivation for Using the Second frinciple in Electric Energy
System Planning
The significance ofexergetic ana1ysis bas been recognized in thermodynamics since the third
quarter of last century [Maxwell, 1871] and its application in mechanical and industrial
engineering bas received considerable attention [Kaygusuz & Ayhan, 1993; Nieuwlaar, 1993;
K1enke 1991; Boustead & Hancock 1979]. Although exergetic anaIysis bas been practically
ignored in the planning ofe1ectric energy systems [Gardner & Robinson 1993, Oliveira &
GaIiana 1995a], there exist numerous motivations for incorporating the Second Principle into
this planning process:
•
•
(a)
(b)
One ofthe reasons why energy planning government bodies and the e1ectric energy
industry have not paid much attention to Second Principle efficiency is probably due
to a lack of farnj1jarity with its possible implications and impact on the planning
process. In particular, the economic value attributed to e1ectricity is basically
established, regardIess ofits end-use, in terms ofits energy content and the energy
consumed to generate this e1ectricity. This kWh energy content is usually directly
compared with alternative sources ofenergy (e.g., oil, gas) regardIess oftheir type
with no regard for the quality of the energy. Although it is weil recognized that
e1eetricity is a "bigh quality" energy, this quality bas not been explicitly assigned a
quantitative measure and a corresponding monetary value. In some sense, this is
anaIogous ta comparing a Formula 1racing car with an old jalopy ooly because they
both provide transportation. This thesis strongly recommends that a systematic
framework ofplanning methods and policies should be established by industry and
government to account for the quaIity ofenergy in e1ectric system planning.
Traditionally, e1ectric energy systems have been concerned with the kWh consumed
by the customers regardIess ofthe type ofend-use (i.e., the service provided) since
the kWh consumed define the system e1ectric load forecast wbich was the primary
• Introduction 8
•(c)
driving function of the planning process. A more recent trend is to plan systems
according to the end-use requirements rather than on the basis ofthe kWh consumed
to supply such demands [Litchfie1d et al, 1994; Hirst, 1992; Berrie, 1983]. As an
example, an end-use cao be the heating comfort leve1 inside a dwelling which is not
Ilecessarily measured by the e1ectric energy required since this leve1 cao be affected
by the amount ofiItslllation. Simi\arly, the end-use traction needs ofa given industry
are independent ofthe process used to generate this end-use, more eflicient motors
c1early consuming fewer kWh. Second Principle analysis would a1Iow the
classification of end-uses according to quality by measuring and ranking their
exergetic contenf. For example, traction is a very high quality end-use however low
temperature heat would be ranked very 10w on the quality scale.
Another significant advantage ofexergetic analysis is that it permits the comparison
ofdiffèrent types ofenergy conversion processes, even ifthey have identical FJrst
Principle efliciencies, by exarn;ning the Second Principle efliciency.
•
(d) Exergetic analysis provides a means to systematica1ly and quantitatively incorporate
the irreveI'SIbility ofavailable work ioto the design ofenergy systems. Available work
orexergy is a limited resource that must be monitored and conserved at least on an
equaI footing with energy resources since it bas been argued that exergetic efliciency
is a "true" measure of the rational use of energy [Gardner & Robinson, 1993;
Boustead & Hancock, 1979; Oliveira & Galiana, 1995a]. Ignorance ofthe Second
Principle cao r=Jlt in high levels ofexergy destruction which constitutes, to say the
least, a mismanagP.lIlent and waste ofa limited resource.
(e) The consideration ofexergy in e1ectric energy system planning cao be carried out in
2 Nole tbat eveD eod-uses with low exezgy content (e.g.lowtempaature hcating) must be
supplicd. Exergetic ana1ysis would belp te systernatically find the most suitablc cncrgy supply match
for this low qua\ily applicatiOlL
• Introduction 9
•
the context ofIntegrated Resource Planning (IRP). TIùs is a general approach which
places equal emphasis on the planning of resources at the supply side and their
counterparts at the demand side. Exergetic anaIysis would be extremely helpful to
achieve one ofthe more diflicu1t objectives ofIRP which is the rational matching of
resources to end-uses. As an example of this application, resources with low
exergetic content should be matched to low exergy end-uses as much as possible.
1.4 Objectives of this Thesis
The main objective ofthis thesis is to present a system approach for the planning ofelectric
energy systems including a new perspective, namely, the consideration of system efficiency
as measured not onlyby the more commonly used First Principle ofThermodynamics (FPT)
but, aIso, by the Second Principle ofThermodynamics (SPT). It is shown in this thesis that
the extension of the efficiency criterion to include the Second Principle would resu1t in
fundamentaI changes in the way electric energy systems are designed and operated. The
motivation for such a change in design philosophy is further discussed in this thesis together
with its potential advantages and drawbacks.
The specific objectives ofthis thesis are:
(1) To introduce exergetic anaIysis into the planning ofelectric energy systems.
(2) To deveiop a general model to design and analyse electric energy systems from the
points ofview ofenergetic and exergetic anaIysis;
•(3) To demonstrate through a number of case studies the impact of exergetic
considerations on the planning process ofelectric energy systems;
• Introduction
(4) To integrate economic, energetic and exergetic analysïs in the planning process;
10
•
•
(5) To carry out a regional planning study by optimizing the system energetic and
exergetic efficiencies;
(6) To introduce a type of electric tariff that induces the optimjzation of the use of
naturaI resources from the point-ofview ofthe Second Principle ofThermodynamics.
1.5 Thesis Oudine
Chapter 2 reviews the F11'St and Second Principles ofThermodynamics and presents some
basic data about the FPT and SPT efficiencies ofa number ofend-uses devices.
Chapter3 presents the electric energy system model utilized in the present thesis. The model
accounts for inputs and outputs as weil as internal t10ws ofboth energy and exergy. An
example10 graphically iDustrate the various aspects ofsystem planning from the F11'St and the
Second Principle is presented.
Chapter 4 examines ditrerent applications ofthe Second Principle to electric energy system
planning In the first place, the five most common end-uses, that is, space beating, cooking,
water beating, traction and Iighting are ana\ysed. This study involved 54 diffetent system
configurations including the following naturaI resources: hydrau1ic potential, nuclear energy,
coaI, petroleum and naturaI gas. For each end-use, the lirniting levets ofthe system efficiency
as measured by the F11'St and the Second Principle are calcu\ated. The nela application is the
el' Bllljllarion cfthe impact ofDemand SideManagementPetformance Improvement measures
at the residential sector. The influence ofthe beat-gains due to cross-eff'ects on beating and
coo1ing loads is ïnvestigated as weil. Fma11y, a simulation ofthe impact ofa major adoption
• Introduction 11
•
•
ofelectric vehicles (EV) in Canada is presented. Different aspects are investigated such as:
petroleum disp\acement by EV and possible sources ofenergy to supply the EV alternative.
OptirniZlltion and exergetic anaIysis ofspace heating systems is presented in Chapter 5. T1üs
chapter applies the principles developed in Chapter 3 in greater detail to a more realistic space
heating problem. Mmùm!I!! energy and exergy solutions are compared with the minimum cost
solution. Diffi:J:ent types ofcost incentives are analysed in order that the minimum exergetic
solution be adopted by the customers. This includes subsidies in the capital cost, in the
opportunity cost rate, or in the electric rate. The analysis is performed for three regions in
North America, tbat is, New York, Québec and Ontario.
Chapter 6 presents a study ofthe planning ofelectric energy systems at the regional leve\
including exergetic considerations. The region studied is composed ofthe Canadian provinces
of Québec and Ontario. First and Second Principle analyses are performed simulating the
influence of different values of transmission line leve\s connecting the two neighbouring
provinces as weil as the state constraints. A different type oftariff structure is introduced
based on the type-oj-use ofenergy. This tariffstructure is tested in order to induce the system
to maximize its ex:ergetic efliciency.
Fmally, Chapter 7 presents the conclusions of the present thesis together with
recommendations made regarding future work.
1.6 CIaim ofOriginality
This thesis proposes tbat energetic analysis derived from the Second Principle of
Thermodynamics should become an integral part ofthe planning ofe\ectric energy systems.
• Introduction 12
•
•
Energetic analysis is specialIy important to ensure a rational matching ofnatura! resources and
end-uses ofenergy, in o'.her words, that high quality energies be used for quality end-uses to
the extent feasible. Energetic anaIysis is a type ofanaIysis, which at present, is not explicitly
considered in the e1ectric energy system planning.
The benefits of exergetic anaIysis are supported by a number of studies presented in this
thesis. These studies analyse from the points ofview ofenergetic and exergetic efficiency and
cost the following: (i) A space heating system; (ul The impact ofa major introduction of
e1ectric vehicles in Canada and (ml The long range planning of a regional e1ectric power
system consisting oftwo interconnected provinces.
A new type ofe1ectric energy tariffis proposed ca1Ied type-oj-use. This tariff is analogons to
the time-of-use rate but it assigns a monetaIy value to the end-use according to the type of
services provided. The purpose ofwhich is to induce the system to maximize the efficiency
as measured by the Second Principle ofThermodynamics. A number ofoptimi'Zlltion studies
are presented in this thesis to support the hypothesis that type-oj-use tariffs willlead to a
more exergetica1ly efficient use ofenergy.
•
•
First and Second Principles of Thermodynamics
Chapter 2.
First and Second Principles of Thermodynamics
2.1 Energetic and Exergetic Efficiency
The understanding ofthe energetic and exergetic analysis and the corresponding efficiencies
are presented in this section. Exergetic analysis is a technique at the forefront ofapplied
thermodynamics research where any systems that uti1i2.e energy are assessed in the Iigbt ofthe
Second Law of Thermodynamics. AlI forms of energy transfer and transport can be
represented by equivalent exergytransfers which are, in filet, the quantities ofwork that could
be produced ftom the same types ofenergy transfer [McGovem, 1990a].
The FII'St Principle ofThermodynamics (FPT) states that energy con neither he crealeDnor
destroyed but con only he cJv:mgedfrom oneform to another [KIenke, 1991; Bejan, 1988;
Holman, 1980 ]. Thus, for any energy conversion process,
13
• First and Second Principles of Thermodynamics
[Input Energy] = [UsefuI Energy] + [Losses]
The energetic efficiency ofa process based on the FPT is defined as,
,,= UsejuI EnergyInput Energy
14
(2.1)
(2.2)
•
The Second Principle ofThermodynamics (SPl) states tbat heat cannot be directly converted
to work without any other effect. For a heat engine, low temperature waste heat cannot he
avoided [Krenz, 1980, Eejan, 1988; Holman, 1980]. In other words SPT states that during
any energy transformation, the quaIity ofthe energy. as measuredby ilS ability toperjorm
work (erergy) degraJies orat most keeps ilS original state.
[Exergy (Input Energy)] ~ [Exergy (UsefuI Energy)] + [Exergy (Lasses)] (2.3)
It is evident from the above inequality that, un1ike energy, exergy is not conserved in a
process. The destruction ofelœlgy is caned irTeversibiIity. Note the c1ear distinction between
lasses and the irreversible destruction ofexergy. Lasses are energy which is not usefùI to the
particular conversion process and it is usua11y in the form oflow temperature heat. Energy
losses do not however imply a destruction, simply a conversion to another non usefùI form
of energyl. On the other band, the destruction ofexergy in an energy conversion process
normally implies a permanent decrease in the amount ofavailable work.
1 There exist numerous examples of energy losses with usefùI applications such as
• cogeneration [perlman & Moore, 1991, Clark, 1986] and space heating "heat gains" due
to cross-efftcts [Moreau & Stricker, 1994].
• First and Second Principles of Thermodynamics
Encrgy , Exergy in the 1.osses
IS
InputEncrgy , Exergy
e,
xLou Lou
Useful Encrgy
e, ~onvc:rsion.,
ent -,x, t1,€ x,
,Exergy Destructionx....
,Exergy
•
Figure 2.1 Basic energy conversion e1ement.
The energetic efficiency ofa process based on the SPT is given by,
t: = Exergy (Useful Energy)Exergy (Input Energy)
(2.4)
•
Figure 2.1 illustrates these two Principles in tenns ofthe energy and exergy variables ofa
basic energy conversion e1ement. Note that this device bas one input and three outputs. The
input bas two attributes or dimensions, the energy and the exergy. Simi\arly, the useful output
and the lasses output also have two such atttibutes. The third output, bas only one attribute,
name1y the exergy destruction since by the Fust Principle no energy destruction can occur.
In many energy conversion devices, the losses consist ofiow temperature heat 50 that its
exergy content, "'- is re1atively low. In such cases the exergy destruction, x.- can be
accurate1y estimated by X:z - X, = (1 - e) x,,
In this study, the function Exergy(.) re1aring energy and cxcrgy is cxpresscd by,
• First and Second Principles of Thermodynamics
Erergy = a Energy
16
(2.5)
where a is a parameter lying between zero and one dependent on other states such as
temperature in the case of heat as weil as on the available technology for converting that
particular form ofenergy into work. A justification and examples ofrelation (2.5) is given
below. From equations (2.2), (2.4) and (2.5), it follows that for a given device,
(2.6)
•where al and ~ are the a's corresponding to the input and output sources of energy
respectively. This is an important equation indicating that the First and Second Principle
et1iciencies and the energy/exergy conversion factors are not independent.
In the case ofheat, ais limited by the Carnot et1iciency ofthe ideal heat engine cycle, TIc..
and depends on the temperatures ofthe heat source, T:z, and ofthe cold sink, Tl, and the
reference temperature T. that is,
1'Jcœ- = 1 (2.7)
where, 8SS'!1l1ing a finite heat source and sink, T is the logarithmic average ofthe cold and hot
sources [McGovern, 199Oa],
• T = (Tl - Tz)ln (TIl T.J
(2.8)
• First and Second Principles of Thermodynamics 17
Table 2.1 First (11) and Second (e) Principles efficiencies and percent exergy in the input
1] for lIIl" CODditiomng aDd hcat.pumps IS the roef!iaeut-of-peâClnllllllCe.
a,) and output (a:.,) enenties.
Encrgy Conversion DevieeParamcler (%)
t].
€ Ct, ex,1. Natural Rcsourcc Tl'llIlSpOl"Ultion 99.0 99.0 37.0 37.0
2. Rdincry 95.0 85.5 41.1 37.0
3. Power-plant
3.1. Hyclro Power-plant 95.0 93.0 97.0 95.0
3.2. ThcnDlÙ Power-plant 35.0 89.9 37.0 95.0
4. Transmigsjoo and Distribution 90.0 89.4 95.0 94.4
5. Fuel Transportation 94.0 72.0 37.0 28.3
6. Spacc Heating (0 to 20" C)
6.1. Electric Basc-board 100.0 2.8 95.0 2.7
6.2. Heat -pump Air-to-aïr 170.0 4.8 95.0 2.7
6.3. Heat-pump Ground-to-8Ïr 300.0 8.5 95.0 2.7
6.4. Di=! OiIIGas Spacc Heating 81.0 5.9 37.0 2.7
7. Water Heating (10 to 60" C)
7.1 StandardElectric Water Heatcr 82.0 5.2 95.0 6.0
7.2. Di=! OiIIGas _ Heatcr 80.0 13.0 37.0 6.0
S. CmkiDgdcviccs(20to ISO"C)
S.1. Electric CookiDg Deviee 89.0 11.5 95.0 12.3
S.2. Di=! OiIIGas CooIcing Deviee 70.0 23.3 37.0 12.3
9. Air ConditiODÏDg (32 to IS OC) 300.0 5.7 95.0 I.S
10.1. ElectricMotor (0.25 kW)
10.1.1 Standard 5S.0 61.1 95.0 100.0
10.1.2. Efficient 69.5 73.2 95.0 100.0
10.2. Electricmotor (10 kW)
10.2.1. Standard 85.0 89.5 95.0 100.0
10.2.1. Efficient 87.4 92.0 95.0 100.0
11. Ligbt
11.1. Jucandesœut 5.0 0.2 95.0 3.0
11.2.1"' Fluorescent 20.0 4.2 95.0 20.0. . .. . . .
•
•
• First and Second Principles of Thermodynamics 18
•
Note that, for practical reasons, the ideal Carnot efficiency cannot he achieved but can only
be considered as an upper bound Iimit.
As examples ofthe above-mentioned ideas, the exergy content ofe1ectricity depends on the
efficiency ofthe best e1ectric motor available for the given kW rating (typicaIly in the range
0.80 < Tl < 0.95). Thus, for a 1kW baseboard space heater, where the input is e1ectricity and
the output is heat at 20 degrees C, acloclricily is approximately 95% (based on the highest
efficiencyofelectricmotors) while ac..... is 6.8% (based on the ideal Carnot cycle efficiency
with temperatures of 20 and 0 degrees C). Since an e1ectric baseboard heater is 100"/0
energetically efficient, its exergetic efficiency (e) is 100*6.8/95=7.2%. Therefore, whereas
100"/0 ofthe input energy is converted to a usefuI output in the form ofheat, 92.8% ofthe
input exergy is destroyed by this process. This is a c1ear example of the possible wide
disaepancies between energetic and exergetic efficiencies and ofthe significant irreversible
loss ofexergy even for a process which is 100"/0 energetically efficient [McGovern 1990a;
Krenz, 1980; Klenke, 1991; Oliveira & GaIiana, 1995a).
Comparison between energetic and exergetic analysis guides us to the following reasoning:
To perform energetic ana1ysis ofa process, it is l'ecessary to treat it only as a black box with
known input and output energies but knowledge ofthe process it is not required. On the
other band, to perform exergetic ana1ysis it is l'ecessary to know, not only the input and
output energies, but aIso the details ofthe process as well as the technologies available to
convert the input and output energy into work.
Table 2.1 shows, for a set ofenergy conversion devices, typical values ofthe efficiencies
according to the FD'St and Second Principles ofThermodynamics (Tl, e) as well as the fraction
ofthe input (aJ and output (~) energy that can he converted to work. In this Table, the a's
are estimated assnming the most efficient available technology to convert a given form of
• energy into available work [Wang & DeLuchi, 1992; Québec, 1992a,b,c; Zhu& Lodola,
1993, Law, 1993; Hydro-Québec, 1993].
• First and Second Principles of Thermodynamics 19
For an energy system with multiple natural resources, R; , and multiple end-uses, EUj , the
F1I'St and Second Principle efliciencies are defined as follows:
n.
E EU,
" =/-1
(2.9)n,
E Rjj-1
•(2.10)
2.2 Energy, Exergy and Entropy
In tbis section the relationsbip among energy, exergy and entropy is discussed. While the
FIISt Principle ofThennodynamics is regarded as the principle ofcooservation ofenergy, the
Second Principle is tbat ofirreversibility [KIenke, 1991]. The concept ofenergy is govemecl
by the FIISt Principle but exergy and entropy are regulated by the Second Principle of
Thermodynamics.
• The exergy assocïated with some forms ofenergy is given by straightforward relations:
• First and Second Principles of Thermodynamics
• Potential gravitational energy is ful)y convertible to worle, thus it is pure exergy,
• Kinetic energy is ful)y convertible to worle, thus it is pure exergy
20
• The chemica1 exergy is the maximum useful worlc that could be produced by the
interaction ofthe system with the reference environment,
• The exergy, X, ofa heat trllnsfer process is given by applying equation (2.11),where
1'). is given by equations (2.7) and (2.8) ifthe idea1 Carnot efficiency is considered,
(2.11)
•l'hus, exergy is, in some idea1 cases, equaI to energybut, in general, exergy is only a fraction
(lX) ofenergy as shown in equadon (2.5).
Exergy can aIso be related to other thermodynamic quantities such as entropy and internai
energy. However, the physica1 significance ofentropy bas historica1ly been the subject of
controversy and is more diflicu1t to conceptualize [Wepfer, 1979]. Whereas entropy tends
to increase to a maximum in any ïsolated system, exergy follows an opposite trend a1ways
tending ta decrease. Exergy is conserved only in idea1 processes which are thermodynamica1ly
reversible. In such processes entropy remajns constant [McGovem, 1990a].
There is agreement in the literature [McGovem, 199Oa; Klenlce, 1991; Wepfer, 1979] that the
total exergy, X, ofa simple substance is given by,
x =X... + Xc:/r + X"... + X.tvr + X., + XUg'" + ... (2.12)
where the subsaipts tin, ch, gray, kin, dec and ligbt respectively represent the exergy content
in thermo-mechanical, chemica1 and gravitational potential, and kinetic, dectrical, and Iight
energies and where the fust two terms are given by,
•
•
First and Second Principles of Thennodynamics
x"" = U - U· - To (S - S') + Po (V - V')
Here,
() refers to the thenno-mechanical dead state ofthe system,
U represents the internaI energy ofthe state relative to the reference state,
S is the entropy ofthe state relative to the reference state,
V is the volume ofthe state relative to the reference state,
iii is the chemical potentia1 ofsubstance i,
N is the number ofmoles ofa specifie substance i,
P. is the pressure at the reference state.
21
(2.13)
(2.14)
The exergy destruction per unit ofmass, x.t. also called irreversibility or the lost work, is
givenby the product ofT. and the entropy generated within the system [McGovem, 1990a).
(2.15)
•
here Ta is the absolute tempeiature ofthe refaence state, ~ , i = 1,2 are the entropies per unit
mass ofthe initia1 and fina1 states, q is the heat transfer per unit mass and T is temperature.
• First and Second Principles of Thennodynamics 22
•
•
In SWllIIIaI)', this section bas higlùighted some ofthe important re1ationships among exergy,
energy, entropy and other thermodynamic properties. In particular, exergy bas a close relation
ta entropy but the former is easier ta conceptualize as it is a measure ofavailable wade.
•
•
•
Electric Energy System Model
Chapter 3.
EIectric Energy System ModeI
3.1 Motivation
An essential component ofelectric energy system planning is to have a clear understanding
ofthe behaviour ofail energy conversion processes from the natura1 resources to the end
uses. This understanding can he gained from the general system mode! shown in Figure 3.1
composed ofinterconnected individual input/output models ofthe type shown in Figure 2.1,
where both energy and eltergy are modelIed. The principal reasons for the deve!opment ofthis
mode! areto:
(a) Provide f1exibility to study and design a broad spectrum ofe!ectric energy
system scenarios of varying size and complexity through a user-fiiendly
software environment,
(b) Sïmulate system planning scenarios based on energy, exergy and cost,
23
• Electric Energy System Model
(c) Optimize system designs.
3.2 Basic System Model
24
•
•
The basic mode! desa:ibing l' geùera1 interconnection among the three main constituent parts
ofan e!ectric energy system (natural resources, energy conversion processes and end-uses)
was shown in Figure 3.1.
Figure 3.1 descn1>es the general model developed for an arbitrary energy system in its full
detail. Severa! forms of natural =urces (NR) cau be considered in the model such as
hydroelectric, nuclear fuel, natural sas. coal, crude oil and solar energy. These resources feed
the different kinds of retineries (RE) or fuel processing plants which, in tum, supply the
electric power plants (PP) or the fuel distribution system (TF). As seen in Figure 3.1, certain
types ofnatural resources (e.g., hydro, solar, wind) directly supply power plants bypassing
the transportation (TN) and fuel processing levels. Power plants provide electricity to the
transmission system (11..) which is connected to the various types of electric energy
conversion (EC) devices (e.g., electric motors, lighting, heating, transportation,
communications, e!ectronics). SimiIarly, the fuel distn"bution systems are tied to non-e1ectric
energy conversion (EC) equipment (e.g., direct space heating, industrial processes,
transportatioc).
The mode! pel11ùts the classification ofenergy conversion devices into more refined classes
For example, one cau difl'erentiate among various types of space beating systems (e.g.,
electric basebosrd, air-to-air heat pump, central oil-fired furnace) or lighting (e.g.,
incandescent, fluorescent). Fmal1y, an of these devices supply the end-uses which are
considered the independent variables ofthe mode! [Broehl, 1987].
•
•
Electric Energy System Model
Figure 3.1 Composition ofa general energy systeI!1.
Lqud
NIl - ll&lUrII n:soun:c
'IN -lrIIlSpOIlIlioD oClIIlIIrI1 n:soun:c
RB - "'CIOCI)'
pp - power plaDt
TL -uaasmlssioa Ilae
...
. ..
25
•
The main end-uses incIude traction, Iigbting and heating which can be further subdivided into
more specifie categories as desired or as the available data permits. For example, the heating
end-use can be divided into: spaœ heating, cooking, water heating and ironing. End-uses can
also be classified by sectors (residential, commercial, industrial or institutional). The
definition ofan end-use is very flexible and includes examples such as:
(i) The spaee-heating load ofa region;
(u) The luminosity provided by the high-pressure sodium street Iighting ofa city;
• Electric Energy System Model
(Iii) Traction requirements in the steel industry.
26
•
•
The term end-use does not descnoe the kWh consumed by the 1000 but, rather, its usefu1
output or its service. For example, the lighting end-use requirements ofa city are elCpressed
in equivalent Joules of lumens.
One drawback ofthis definition ofend-use is that data in this format is not always easily
avai1able and may need to be estimared It is also difficult at times to define or quantllY what
is an end-;.JSe. For example, in space heating or cooling, the comfort level can be considered
as the end-use a quantity which is normal1y measured in terms ambient temperature and
humidity and is strong1y affected by the inslllatiQn level ofthe dwelling. The amount ofenergy
needed to meet this comfort level is the input to the model and must be calcu1ated based on
the knowledge ofthe external and internal ambient conditions. Thus, it can be said that no
demand exists for energy itselfbut oniy for the end-use services that it provides [Gardner &
Robinson, 1993; Rab~ 1991]. In spite ofthe difficulties in defining and estimating end-uses,
this is an essential step to be able to systematically plan electric energy systems.
Note that in Figure 3.1, a horizontal bar aets as a "dispatching centre" taking the inputs and
distributing them among its outputs according to a specified distnoution scheme. For
example, the barunder the refineries (RE) takes the refined fuels (e.g., oil, nuclear fuel, gas)
and dispatches some proportion ofeach fuel either to the power plants (PP) or to the fuel
transportation and distnoution system (TF).
3.3 Mathematical Energy System Mode!
Resources, eneIBY conversion processes and end-uses, are subject to equality and inequality
• Electric Energy System Model
constraints charaeterizing:
(a) Balance ofenergy flow;
(b) Specified end-nses;
(c) Relation between energy and ex:ergy;
27
•
(d) Limits on inputs/outputs of energy conversion, transportation and
transmission processes;
(e) Limits on natural resources;
(f) Government regulations on energy use and environmental impact;
(g) Penetration rates of demaI:d-side management alternatives [Talukdar &
Gellings, 1987; Lithchfie!d et al, 1994];
(h) Costs and tariffs at alllevels;
(i) Constraints imposed by public concems.
Ifthe total set ofattributes (states) ofa given energy system is denoted by a n-dimensional
veetor r. then the mode! for the entir., system is ex:pressed by a linear transfonnation,
where A is a matrix ofdimension m by n with m< n. The m-dimensional veetor b is usually
defined by the specified end-uses. In addition, some or all of the states may he bounded
according to•
•
Ay=b
ymID :S: Y :S: YIIIU
(3.1)
(3.2)
• Electric Energy System Model 28
The system states denoted by the vector y inc1ude energy, exergy and cost variables at all
levels ofthe energy system. The mode! is primarily designed to describe energy and exergy
consumption over a specified time interval (e.g., 1-25 years) as wel1 as the associated costs.
Other system characteristics such as peak load can aIso be modelled given load fàctor
parameters. In addition, the mode! is normally provided with a set of parameters which
inc1ude FII"st and Second Principle efliciencies for all individual devices, capital and
operational cost data, power ratings as wel1 as the limits on all states.
To illustrate the above general mode!, consider a special case where the vector y can he
expressed as,
• y = [elxJ
(3.3)
where e and x represent the vectors ofenergy and exergy states respective!y. Other states
associated with cost may aIso be included. Equation (3.1) then takes the form,
(3.4)
•
and
(3.5)
where the matrixA. depends on1y on the energy network topology and on the FII"st Principle
efliciencies, the matrix A,; depends oDly on the energy network topology and on the Second
• Electric Energy System Model 29
Principle efliciencies, while the vector b. depends onIy on the specified energy end-uses.
FinaIly, the vector b. depends onIy on the specified exergy end-uses.
In addition, because ofequation (2.5) re!ating exergy to energy, one bas a set ofrelations of
theform,
x=De (3.6)
•
where D is a diagonal matrix, made up of the coeflicients lXt reIating energy to exergy
examples ofwbich appear in Table 2.1. This type ofgeneral matrix mode! is used extensive!y
in chapter 4 where severa! cases ofsystem planning are exarnjned as weIl as in Chapters 5 and
6 where the optimal design ofenergy systems are discussed.
It is important to note that ofthe three reIations describing the energy/exergy system (3.4),
(3.5) and (3.6), only two are independent, the third being dependent on the other two. Thus
nonnal1y, one only needs the energy reIations (3.4) and (3.6) or equivalently, (3.5) and (3.6).
In order to demonstrate this property, first note that the topologies ofthe energy and exergy
relations (3.4) and (3.5) are identical, only differing in the parameter values as follows:
(i) For each energy conversion device similar to that shown in Figure 2.1 one bas the
reIation,
(3.7)
•appearing in 3.5. However, from 3.6, it follows that,
(3.8)
• Electric Energy System Model
andthat,
50 that using (2.6),
30
(3.9)
which is the corresponding relation in (3.4).
(3.10)
(ù) At each junction point in the energy networle, the energies and exergies being
summed must be ofthe same type. In such a case, equation (3.4) would contain an
• equation ofthe type,
(3.11)
where n is the number ofenergy f10ws at that junction. Then, using (3.6),
(3.12)
5Othat,
• but since the CXt • s are ail equal at a junction,
(3.13)
• Electric Energy System Model 31
(3.14)
•
•
Thus, the energy equation (3.4) together with (3.6) are sufficient tO define the corresponding
exergy equation (3.5).
Thus, to snmmarize this section, it is ooly necessary to develop the energy (exergy) mode) of
the system. The exergy (energy) attributes can then always be obtained from the energy
(exergy) attributes and the relations between energy and exergy (3.6).
3.4 Example of Mathematical Model
In arder ta better understand the generaI mathematical model descn"bed in the previous
section, consider the iIlustrative case shawn in Figure 3.2. This system bas the foUowing
characteristics:
(a) The inputs are the end-uses, in this case, the traelion, T, and the heating requirements,
Q, bath ofwhich are taken as specified quantities;
(b) The heating end-use tan be met by either direct ail heating, DB, or by electric
baseboards, BB;
(c) AIl the traction requirements, T, are met by electric motors;
(d) The electricitY demand is met by thermal (pP-th) and hydro (pP-hy) power plants;
(e) The natura1 resources considered in this simple example are hydraulic potential
(Water, ~o> and crude ail (Oïl, ~J.
• Electric Energy System Model
Table 3.1 Data for the example ofFigure 3.2.
32
Q = 200 MJouies
11 n = 35 %
1111y= 95%
11M = 87%
11D11= 80%
11BB= 100%
T = 100 MJouies
En = 90% ŒaiI =0.40
EIIy= 93% Œ..- =0.95
EM= 92% Œ_=1.00
EDII =6% Œ_ = 0.027
E 8B =3% 1Iœu.iàl) - 0.95
•(f) The rl1'St and Second Principle efliciencies ofthe five energy conversion devices are
denoted by the symbols 11 and E with the appropriate subscript while the Œ'S represent
the enet13/exergy conversion fàctors. Table 3.1 shows seme typical values assumed
for the example ofFigure 3.2.
For the above mode!, the relations shown in Table 3.2 define the vector equation (3.4).
Then,A. and b. take the form,
• Electric Energy System Model 33
T o o o o o o (3.16)
where the superscript T in equation (3.16) stands for the transpose of the vector. These
arrays are normally very sparse, a faet that can be exploited to simplify numerica1 analysis.
T
Q
~
DH..1 e HUI,e4
JJJ
e,PP-th
.. et ~,1
, ,ïl,O
~ BB .. ~,1
,
e. e.eJ' .., pp-,]
J,
410, JY e, T,Gdio",
Jes, M ,
e,
o•
Legeru1
PP-th = tierlfUl1powerpllutbPP-lly =i]tIro powerpllutbDH =lÜredoiZ,plICe1,utenBB =e1edric 6ueiolll'ti iutenM = e1ecIric "'olon
F"JgUre 3.2 IDustrative example ofe\ectric energy system.
• Electric Energy System Model
Table 3.2 Energetic and exergetic relations for Figure 3.2.
34
Energy Relations Exergy Relations
Q=e l+e 2 "QQ=X 1+X 2
T=e3 T =x3
e.= e I/'I'J OH X.=X 1/E DH
e 5=e2/ 'l'JBB X5=~/ EBB
e6= e3/ 'l'J M X6=X3/ EM
~+el=e5+e6 x,+X I =X 5+x 6
en =e,+e. Xn =x,+x.
eIO=el/'l'JHl' X10= x 1/ E Hl'
e,= e,/ 'l'J 1Il X,=X,/E lIl
• It is also crucial for the mode! to ensure that ail the energy and exergy states are nonnegative
in order to guarantee physically realjz.able solutions.
For the simple iIIustrative system shown in Figure 3.2 the Fust Principle efliciency ofthe
overalI system, 'l'J. is given by.
(3.17)
•whieb is an exampleofthe general equation (equation (22» descn"bing the ratio ofthe total
energy output (sum ofthe end-uses) to the total energy input (sum ofnatural resources).
• Electric Energy System Model
Similarly the efliciency, E as measured by the Second Principle is given by,
35
E = (3.18)
•
3.5 Energy System Optimization
This simple example serves to iIIustrate the large differences that arise in system planning
when the efliciency criterion is based on the FU'St or on the Second Principles. For example,
two extleme designs can he considered, one that maximizes 1'1 and another that maximize E•
In thefirst design, by anaIysing the energy equations in Table 3.2 as weil as equation (3.17)
and the energy inequalities, as will he demonstrated later in this section, it can be readily
shown that the maximum FU'St Principle efliciency occurs under the following conditions:
• No direct oil heating, that is, 100"10 e1ec:tric baseboard heating.
• No thermal power plant, that is, 100"10 hydroe1ec:tric generation.
This optimum solution is reasonable since, from the FU'St Principle, baseboard e1ec:tric heating
is 100% efficient compared to direct heating (81%), while thermal generation is more
ineflicient (35%) than hydro (95%). This optimum design then yields a FU'St Principle
efliciency given by,
•1'I1IlIX =
Q+TQ T 1'IHy-+-1'188 1'Iu
(3.19)
• Electric Energy System Model 36
•
At the other extre:me, ifthe system were designed to maximize the Secontl Principle efliciency
as defined by equation (3.18), again, as will he shown later in this sec, the corresponding
design would he characterized by:
• No electric baseboard heating, that is, 100"/0 direct oil heating.
• No thermal power plant, that is, 100"/0 hydroelectric generation.
Thus, both the First and Second Principle criteria produce designs which exclude
thermoelectric generation. The Second Principle, however, tends to reduce electric
baseboard heating to a minimum replacing it with direct oil heating, in contrast to the First
Principle criterion which does the opposite.
The maximum E design thl::1 :tas a Second Principle efliciency given by,
(3.20)
•
It is also usefùl to e-BIIiÏIICthe design corresponding to the worst efliciencies from the points
ofview ofboth the F1ISt and Second Principles. This design is defined by,
• 100 % thermoelectric generation.
• No direct oil heating, that is, 100% electric baseboard.
Table 3.3 shows the values of" and E for the three ex:tIeme designs describe above.
In SllmmBry, one can observe that system design based on the maximization ofthe F1ISt
Principle efliciency does not necessarily match those designs based on the maximization of
• Electric Energy System Model
Table 3.3 Numerical examples ofefliciencies for extIeme design objectives.
Design objective Tl (%) e(%)
1. MaYÏmjze First Principle Efliciency 90.6 32.5
2. Maximize Second Principle Efliciency 81.7 50.6
3. Minimize First & Second Principle33.4 31.4
Efliciency
37
•
the Second Principle. In fàct, for this simple example, the maximum Tl design corresponds
to a design close to the minimum e design (31.4%). On the other band, the design
correspondingtothemaximum e (50.6%) bas a corresponding Tl (81.10/0) fàirIy close to its
maximum (90.6%). l'hus, it is poSSIble to find reasonable compromises between the First and
Second Principle requirements.
In order to demonstrate the above optimiZllrion results and to gain greater insight into the
oprimization ofenergy systems, it is worthwhiIe to develop a geometric interpretation ofthe
Table 3.4 Energy and ex:ergy relations as funetion of~ and ~.
•
Energy Relations
~=Q-Ct
e,=T
e.=Ct/1Jœ
e, =(Q - Ct) 11'\aa
~=T lT]w
es =(Q - Ct) IT] B8+T 11'Jw - e,
~ae,/T]m
Ct. '" «Q - Ct) IT] B8 + T hJw -e, ) IT] I!>'
Ctl =el/1Jœ+e,/1'Jn
Exergy Relations
Xs=(~Q-xl)/EB8
x.s=~T/ew
,,"=(~Q-xl)/E88+~T IEw-X,
",,-x,I Em
XI.-«~Q-Xt)/EB8+~T1Ew-x,)1 El!>'
XII "'XI IEœ+X, 1en.
• Electric Energy System Model 38
optimization process. Since this system is characterized by Il states and 9 equations (see
Table 3.2), it bas two degrees offreedom which can be independently designed to minimize
or maximize a given objective. These degrees offreedom are not unique, but one possible
choice is the pair (~ and ~), namely, the a......ount of space heating provided by direct
heating, and the output ofthe thermal power plant respectively. It is straightforward to show
from Table 3.2 that an the states can be eKpressed as a Iinear function of~ and ~ as shown
in Table 3.4 (the reader is reminded that an anaIogous result applies to the exergy states).
Since an the sta'..: variables must be nonnegative, the equations shown in Table 3.2 impose
the foUowing l"ecessa'Y and suflicient C{'nditions on the free variables ~ and ~ ,
•e. ~ 0
el Q Te7 +-s-+-
TJBB TJBB 1'JM
(3.21)
(3.22)
(3.23)
•
By plotting inequa1ities 3.21 through 3.23 in the ~ - ~ space, it is possible to ~snalizethe
region offeasible states in the sense that all are nonnegative and they satisfy a:I the system
equalities. See Figure 3.3. it can be noted that this region is bounded below by the ~ - Cr
axes and above by two Iines. The horizontal one simply represents the fàct that direct oil
heating cannot exceed the total space-heating end-use, Q. The inclined line represents the
fiIct that the output ofthe thermal power plant cannot be greater than the e1ectrical needs or
equivalently that the e1ectric generation must be nonnegative. It is useful to physica1ly
intertlret some ofthe vertices in this region. The point (0, Q), for example, implies that an of
_. - . space heating needs are met by direct oil heating and that there is no thermal power plant.
• Electric Energy System Model 39
•
(o.Q)~=
(0.0)
Figure 3.3 Feasible region.
• Q)
•
The point (Q/11œ +T/1'JM, 0) corresponds to a system with no direct oil heating (orny e1ectric
baseboard heating) and ail the e1ectric needs supplied by thermal power plants.
In a more gen,;rai system, the region offeasible states becomes ofa higher dimension and
cannot be plotted but the principle is the same.
Now, since the design objective may be to maximize either the FlfSt or Second Principle
system efliciencieswithin the limits offeasibi1ity shown above, it is nece:;sary to express 3.17
and 3.18 in terms ofthe free variables~ and e,. This gives,
• Electric Energy System Model
and
40
(3.24)
(3.25)
•
•
It can he seen that maximizing Tl is equivalent to mjnjmjzir ~ the denominator of(3.24). Ifwe
plot the locus ofconstant Tl in the l:t - ~ space, this will he a straight line with a negat!-Ie
s10pe. In Figure 3.4 three such loci are shown, 1')",;" , 1'J.l. and "l'lm.. , corresponding respectively
to the minimum, intennediate and maximum values ofthe FII'St Principle system efliciency
within the feaslble region. This figure clearly shows that to maximize Tl, one must operate at
(0,0), that is at the point where there is no direct oil heating and where there is no thermal
power plant generation, thus proving the statement made in equation 3.19. A simiIar argument
cao he made for lle Second Principle efliciency where the locus ofconstant E is represented
in Figure 3.4 by a straight line with a positive s1ope. Two such loci are shown, namely, E",;"
and e-.It is interesling to note that the maxinmm Second Principle system efliciency occurs
at (O,Q), that is, at a design with no thermal power plant and al1 space heating requirements
are met by direct heating. In addition, Figure 3.4 shows that the minimum exergy efliciency
design corresponds to the minimum energy efliciency design, both occurring at (Q/Tbm
+T/TlM' 0), that is, a design with no direct heating (100".10 e1ectric baseboard) and al1 the
e1ectric needs met by therma1 powerplants. This rigorously confirms the results stated earlier
in this ch3pter.
It is aIso worthwhiIe to note that for an intennediate rU'St Principle efliciency, 1'J.l" given by
•
•
Electric Energy System Model
Figure 3.4 First and Second Principle efficiencies oprirni7Jltion aspects.
41
the straight line locus shown in Figure 3.4, there exist an infinite number ofpossible solutions
an with the same F1Ist Principle efficiency b1.:t with different Second Principle efficiencies
which vary from a maximum at point a 10 a minimum at point b. This confirms the statement
made earlier that for a constant " there can exist numerous designs ofvarying E and vice-
versa.
FmalIy, consider an optirni7Jltion objective wbich rninirnizes a combination ofE and " such
as" + E or some other linear combination. It is c1ear that the locus ofan possible solutions
• that satis1Y thismixed objective will again begiven by a straight line but with a different s10pe
• Electric Energy System Model 42
to those that bave as objective to maximize Tl or € alone. For example, the point (T/TlM , Q)
in Figure 3.4 is the optimum solution for an objective function f given by,
(3.26)
•
•
where w\ and W2 are positive weighting factors. Note also that fmay bave additional terms
re!ated to cost and emissions.
3.6 Computer Mode!
In order tû be able to f:2~ out the above-mentioned stu:lies, it was necessary to deve!op a
specialized so(..:~ tool [Oliveira & GaIiana, 1995a]. This tool, named EXAM (EXergy
Analysis Model), provides the userwith a set ofbasic constituent parts (resources, conversion
devices, end-uses) and a means to grapbically inter..onnect them to form an arbitrary
netwoIk. EXAM pennits the user to change the default values, to add new attributes and to
modifY the relationsbips among attrîbutes. To acbieve tiIis generality and flexibility, an object
oriented modelling approach was chosen using the generic environment G2, Version 3.0
[Gensym, 1992].
3.7 Concluding Remarks
This ch2.pter bas presented a general mode! for the planning of e!eetric energy systems
including euergetic and exergetic considenmons. 'Ibrough an ü1ustrative example, this chapter
presents a grapbical interpret&tion ofthe main aspects ofenergetic and exergetic optimization.
•
•
•
Applications of Exergy Analysis in Electric Energy System Planning
Chapter4.
Applications ofExergy Analysis in
Electric Energy System Planning
4.1 Introduction
In this cbapter, severa! applications ofthe Second Principle in e1ectric energy system planning
are presented, name1y:
(i) The ana1ysis of the main e1ectric energy system end-uses: (a) space heating. (b)
cooking, (c) water heating. (d) traction, (e) Iighting. This ana1ysis is performed for
different system configurations including the following natural resources options:
hydraulic potenti:!1, Duclear energy, petroleum, coal and natural gas. The limiting
leve1s ofFPT and SPT efliciencies are calcnlated for each end-use under the best
possible system configurations;
43
• Applications of Exergy Analysis in Electric Energy System Planning 44
R-by - IClOlIrCC8 bydroR·th - forri! fuel
(pctrolcmn. uatural su,coa1) or .."cloar OIlo:gy
by - bydro polClltialth- thormalRe - rcfiJlcrypp - power p1alltTD - Innsmission Jm.c and
dirtrib"tio.. systemTP - tr8Illponatio.. ryrtemAIt - OIld-".e dcvicc altcmativcE""-".o i
Figure 4.1 Space heating modei.
•
(n) The impact ofperfoI1IlllLce improvement (PI) measures at the residential sector of
electric power systems is invesrigatetl at diffelent Ieveis, namely, the e1ectric appliance
being improved, the customer, the electric and gas/cil utilities and the overa11 natnra1
resources. Snch PI measnres inclnde the introdnction of more efficient e1ectrical
appliances, water-heaters or Iight bnlbs. Special attention is devoted to the influence
ofheat-gains due te cross-ejfects on beating and cooling loads. The impact ofsevera)
• PI u:.easures is examjned from the points ofview ofthe FII'St and Second Principles
• Applications of Exergy Analysis in Electric Energy System Planning
Table 4.1 End-uses, end-uses devices and natural resources considc:red.
4S
•
End-uses End-use Deviee Altcmative Natural Numbcc ofPossibleRcsourccs Configurations
Spacc hcating fumacc
Bascboard clcdric hcatcr Hydro cncrgy1. Spacc Hcating 18Hcat-pump air-to-air
Hcat-pump ground-to-airNuclcar cncrgy --
2. CookingDirect cooking stave
8Elcdric cooking
Pclrolcum
3. Watt:r hcatingDirect watcr hcating fumacc
8Elcdric watcr hcating
Incfticicnt motorNaturalgas
4. Traction 10Efficient motor
IncfIicicnt Iighting CoalS.Lighting
Efficient~10
of Thennodynamics for various PI measures, generation types and mix and space
heating alternatives.
(ùi) The energetic and exergetic impact of electric vehicles (EV) on Canada's power
systems is investigated. Different scenarios are eva1uated to simulate the incrcased
e1ectric demand due to the adoption of EV technology. These scenarios include
variations on the system load fàctor and changes in the e1ectric load through the
adoption ofmore energetical1y and exergetically efficient space heating alternatives.
The amount ofpetroleum that would he displaced ifEV were adopted as well as the
demand to build new power generation units are eva1uated. It is shown that there is
no need to build new e1ectric energy generation facilities for most ofthe Canad;an
• provinces ifa fraction ofthe space heating loads were converted to direct oil/gas
• Applications of Exergy Analysis in Eiectric Energy System Planning 46
space heating fumaces or to more efficient space heating options.
4.2 Limiting Levels of FPT and 8PT Efficiencies
This section is dedieated to the analysis ofthe limiting leve1s ofthe FPT and SPT efficiencies
for live end-uses: space heating, cooking, water heating, traction and Iighting under different
Table 4.2 Main system configurations.
Or cocffiCient-of-perfOlDlllDl:C
E 1).
End·use Code System coafiguration% %
SI Ground-to-aïr hcat-pump with hydroelcdricity 5.4 ID.7S2 Ground-to-aïr hcat-pump with natural gas 5.5 81.1S3 Grouod-uHIir bcat-pump with coal, ail or nuc1ear enc:rgy 5.4 80.0
1. Spacc 54 Air-to-aïr hcat.pump lIIId hydroelcdricity 4.2 148.6hcating S5 Spacc hcating fumacc using fossil fuel 3.9 57.2
S6 Air-to-aïr hcat-pump with fossil fuel orDuel.:cncrgy 3.6 53.3S7 Bascboard e1cdric heatcrs lIIId hydroelcdricity 2.5 87.4S8 Bascboard e1cdric heatcrs lIIId thcnnoclcdricity 2.1 31.5
CI Direct cooking range with fossil fuel 10.1 33.72.Cooking C2 Elcdric cooking with hydroelcdricity 5.6 44.6
C3 Elcdric cooking lIIId thcrmoelcdricity 4.8 16.0
3. Waœr WI DirectWlIlCr beating fumacc with fossil fuel 8.2 40.8
hcating W2 Elcdric WlIlCr hcating with hydroelcdricity 6.3 75.2W3 Elcdric WlIlCr beating lIIId thcrmoelcdricity 5.4 27.0
Tl Efficient motorwith hydroelcdricity 73.6 69.9
4. Traction T2 Efficient motorwith thcrmoelcdricity 63.0 25.1TI Inefficient motorwith hydroelcdricity 55.2 52.4T4 Inefficient motorwith thcrmoelcdricity 47.0 18.8
LI Efficient lisbtingwith hydroelcdricity 2.8 17.5
5. Ughting L2 Efficient Iightingwith thc:rmoelcdricity 2.4 6.3L3 Inefficient Iighling withhydroelcdricity 0.3 5.2L4 Inefficient Iighting with thcrmoelcdricity 0.2 1.9. .•
•
• Applications of Exergy Analysis in Eleetric Energy System Planning
Table 4.3 Main system configurations in decreasing order ofefliciency.
47
•
•
End-useSystem configuration in decreasing order ofefficiency
Second Principle First Principle
SI SIS2 S4S3 S7
1. Space bealing S4 S2SS S3S6 S6S7 SSS8 S8
Cl C22. Cooking C2 Cl
C3 C3
WI W23. Water bealing W2 WI
W3 W3
Tl Tl
4. Traction 1'2 T3T3 1'2T4 T4
LI LI
S. Ligbting L2 L2L3 L3L4 L4
system configurations. FlVe naturaI resources were tested: hydro, nuclear petroleum, naturaI
gas and coa!. Different tests were done to find out the limiting levels ofthe FPT and SPT
efficiencies of eacb end-use including the consideration of all possible combinations of
refineries, power-plants, transportation, transmission and distribution systems and end-uses.
See Figure 4.1.
Table 4.1 presents a Iist ofend-uses, end-use devices and naturaI resources considered in the
• Applications of Exergy Analysis in Electric Energy System Planning 48
f --.----- ••• ------- -.- ••••••• --- •• - ••• --- •• -- •
•. . . . .6- -: :- - : .. -- ~ (]I) :. • Œtl . , .
Figure 4.2 Second, E, versus First, 1'), Principle efliciencies for the end-use space heating.
'-(S3 y.: : -- : -- :. , . .
5 " .
~~ . . . . .• • • • • •
4 - ........•. :.•• {~} - •. :•.•••.••.••: • - GD' : :il! : : : :
CE), .. H.~ (~'IH HH~I~1HH... 'H .. H.H. ,[~~~ )
2+---~--r------r------r------r--===="1
o 50 100 150 200 :25C~.in(%)•
calculation ofthe limiting leveIs ofthe FPT and SPT efliciencies. Similarly, for each end-use,
the nwnber ofpossible system configurations is also shown. Note that, for the space heating
end-use, four devices were considered, white, for each ofthe remaining end-uses, only two
aItematives were evaluated. As seen in Table 4.1, for the space heating end-use, the number
ofpossible system configurations is 18. This includes tbree possible space heating fùmaces
(gas, oil or gas from coal) and 15 el~c space heating configurations (tbree electric
alternatives tintes five natural resources).
•
For each of the possible configurations, the First and Second Principle efliciencies were
calculated. Table 4.2 shows the main types of system configurations and their F11'St and
Second Principle efliciencies. Table 4.3 summarizes, in decreasing order ofSecond and F11'St
Principle ofThennodynamics efliciencies, the typical configurations listed in Table 4.2. It is
expected tL..t realistic designs would have efliciencies 1ying inside the rr..nge defined by these
• Applications of Exergy Analysis in Electric Energy System Planning 49
11 •••••••••• - - - ••••• - •• - - •••••••• - - - • - - • • • • • • - • • • • • -
tD • - - -. _ ••: _ •••• - - -:- • - - - •• - ~ - • - •• -@ : -.. -:• ........' • - - - - - - • 'e • • • • • • • : _ _ _ • • • • .'. _ _ _ • • • • 'p • • • • • • • pO-.j.. - ' '. -----.-, -'--.-.--.'. -.. - '!. . . , . . .
.!: • • , 1 • •
.; 7 •••••• - .' • - - - - •• - Op ••••• _ • J •• _ • _ ••• ' •••• _ ••• '•• _ ••••••'. . . . . .. . . , . .1· c , .......•........: : .. 5:)~· ~-- -> --:-- .... (SC;::~:l» --~ -.. ~~ -.~4 1 1 1 1 1.. •• ••
•Figure 4.3 Second, E, versus First, 1'), Principle efficiencies for the end-use cooking.
extreme limits. Analysing Tables 4.2 and 4.3, it is noticed that,
(i) There eKists a wide range ofenergetic and exergetic efficiencies for the set ofend-use
devices studied. The FPT efliciency (or coeflicient-ofperformance) ranges from 1.9"10
(lA) to 223.7"10 (SI) while the SPT ranges from 0.2% (lA) to 73.6% (TI);
(ü) The end-use traction bas the highest SPT efficiency (TI). Even the minimum e for
traction (T4) is higher tban the e for an other combinations ofend-uses and natural
(üi) Note that the heat-re\ated end-uses and lighting haVI:: an e- always less tban or equai
to 10.1%, as opposed to traction that reaches an eof73.6%;
(IV) For heat related end-uses, the maximum efficiency as measured by the Second
Principle ofThermodynamics occurs for the following configurations:
•(a) Space heating: ground-to-air heat-pump and hydre electricity (SI): Ifthe
heat-pump alternatives are not considered, then the maximum SPT occurs for
Sj!3CC heating fumace (SS). Note that even the air-to-air heat-pump with fossil
• Applications of Exergy Analysis in Electric Energy System Planning 50
B5 •.••..•••••••••••.•••••••••••••••••.•••••••••••••
, . . . . ,. ..~. . . .B' ....•••.: ..•••... :.•~ ••• ; •••.•.••: •.••••. -;••••••.. :
7.5 - _. - ..• - -, . - . - - . - - ,- ....•.. :- - - - .••• -.•.••.•• '.' •• - - - . - .
7' _ ••••.•••••••••••••
. .8.5 ••••••••; •••••••• :•••••••• ~ ••••••••: •••••••• :••••• JW2 )
•
807D8050q.In~)
40
8 .•..•. Ci1J ~ : ~ ; :. . . . Ler;eDd J:'5.5 •••• ,.~ •.•••••• :•••••••• : ••••••• ~ •••••• SccTablc4.2 ::. . . .
s-t-~-~~-~,-~,~~,20• Figure 4.4 Second, e, versus First, 1'\, Principle efficiencies for the end-use water heating.
fuel or nuclear energy (S6) is Jess elI:ergeticel\y efficient tban the space heating
furnace (S5);
(b) Cooking: direct cooking furnace (Cl);
(c) Water heating: direct water heating with fossil fuel, (Wl);
(v) For heat related end-uses, the maximum efficiency as measured by the FIISt Principle
heat related end-uses, the maximum efliciency as measured by the FIISt Principle of
Thermodynamics occurs for the following configurations:
•(a) spaœ heating: ground-to-air heat-pump and hydro electricity (SI), followed
by air-to-air heat-pump and hydroeIectric generatiOD (84);
• Applications of Exergy Analysis in Electric Energy System Planning 51
75] ~ : : ~ : Ii
70 •••••••• :••••••••• :. - •••••••: •••••••••: •••••••• ; ••••• Œ)· . . . . .
65- ..•..•.• :•.•..•... :--- :......•..: ; .
· " . . , ,....... ':' .GD' .':' ':' : : :1 • • • • ,....................................................... ,
. . . :GD.50· ••••••••••••••••• ',' ••••••• '.' ••••••• ',' ••••••• ; •••••••.
Figure 4.5 Second, e, versus First, 'l'J, Principle efficiencies for the end-use traction.
,:45 ·····cir·······:·········:········:········ . . .
•40
'0 20 30 40Il.ln(")
50
•
(b) Cooking: e1ectric coomg with hydroe1ectricity (S2);
(c) Water-heating: e1ectric water heating with hydroe1ectricity (W2);
(vi) The worst FPT and SPI' efliciencies coincide for the set ofconfigurations studied. In
an ofthe worst efficiency cases the energy is supplied by thermoe1ectric generation.
(vii) Comparing columns two and three ofTable 4.3, note that, with the exception ofthe
lighting end-use, an other end-uses have a different order ofdecreasing SPT and FPT
efficiencies;
(viii) Final1y, it is clear from the above discussion that, in general, for a given system
configuration, it is not possible to maximize both the FU'St and th~ Second Principle
efficiencies simu1taneously.
The question that presents itselfnow is how to compare energy system alternatives from the
• Applications of Exergy Analysis in Electric Energy System Planning 52
3- . - - - - . - - - - - - - - - - - - - - - - - - - - -
. . '.Œ):
25- "-'-'---"'~"lifJ-"":"""""-'-:"""""--':2 • - ••• - •••••• , •••••••••••• ~ •••••••••• - • -,- - - ••••• - ••••.
. , .- - ~ ~ - . -,- - - . - - - - . - .
, - - . - - . ~ - : : - .
Figure 4.6 Seco:lll, c;, versus F1I'St, l'J, Principle efficiencies for the end-use Iighting.
5
•o.s-
oo
. . . . . . . . . . . . , - .. - . - .' - '- - _.,------...,-
• Œ) ~ @), : Scc~~2 jro ~ ~
q.1n (%)
•
combined points ofview ofenergy and exergy (excluding cost for the moment). Figures 4.2
to 4.6 show, for each end-use, (space heating, coolàng, water heating, traction and Iighting)
in graphical fc:m, the information presented in Tables 4.2, by plotting the FPT efficiency
against ~j,~ SPT efficiency for each configuration listed. Note that, for these five figures, the
system Cln11lguration shown corresponds to the ones Iisted in Table 4.2. Cost will, ofcourse,
play a role in the fiIll..\ analysis lII:d is further discussed in Chapter 5.
One can argue that cll the proposee! alteri1lltives are extreme cases of only one type of
generation and end-use and arc unlikely to be realized. Nevertheless, these cases provide
benchmar\c Iimits which cau neverheexceeded by any alternative. For example, for the space
heating end-use, SI (hydroeIectric poV':c.- with ground-to-air heat-pump) is the limiting
alternative because of its highest Fust 3Ild Second Principle performance. The worst
alternative for tŒs end-use from both Pr'.nciples is S8 (thermoelectric generation with
• Applications of Exergy Analysis in Electric Energy System Planning 53
•
•
baseboard electric heaters). For space heating, saturation through direct gas or oi. heating,
is an alternative that is more like1y to be approached since it implies changes in the end-use
heating systems and not in the generation mix ofthe utility.
4.3 Demand Side Management Performance Improvement
Demand Side Management (DSM) is recognized by e1ectric utilities and society as an
attractive alternative to system expansion and ~.s a resource to be planned [Ra!>l, 1991). In
1990, Latorre et al studied the application of DSM techniques in the industrial sector
concluding that the cost ofelectric energy saved by DSM was estimated to be between 12 and
21 US$/MWh whereas the marginal ('.ost of expansion was estimated to be around 62
US$IMWh. Similarly, a study in British Columbia [Henriques, 1992] indieates that the cost
of a DSM program is Can$16/MWh compared to Can$50/MWh to generate equivalent
energy with new power plants. One important DSM measure, known as Performance
Improvement (PI) [Talukdar & GeDings, 1987], consists of incentive programs to encourage
the rep1acement of electrical equipment 1»' more efficient substitutes. Examples of PI
measures are: (i) Rep1acement of incandescent by fluorescent compact lighting, (ü)
installation ofmore efficient water heaters, (ili) switching to more efficient motoTS.
DSM Performance Improvement measures cannot be eva1uated by only cCinsidering the
energy savings at the level of the equipment being rep1aced, since these Sllvings spread
throUghOl.lt the entire energy system. Thus, implementing a PI measure for one type ofenergy
conversion device will also influence various other level.s ofthe energy systema11 the way
~ack to the natural resources level. Similarly, a PI measure will affect the consumption of
energyby ether load.s at the same level Decallse ofthe phenomenon known as eross-effects.
Atypical example ofeross-effects is the impact ofimproving the performance ofany indcor
• Applications of Exergy Analysis in Electric Energy System Planning 54
•
•
energy conversion device on the space heating and cooling requirements ofa dwelling. In a
study conducted by a Cnnadian utility [Moreau & Stricker, 1994], it is demonstrated, for a
given type ofhouse in Montreal, that a more efficient water heater economizing 438 kWh /yr
resu1ts in ollly 42"10 ofthese savings being rea1ized at the dwelling or customer leveI. This is
50 since, as a result ofthe increased water heater efficiency, less nc:ll is released indoors as
heat loss and therefore the space heating requirements increase by 291 kWh/yr during the
heating season. Similarly, the air-conditiofÜng requirements decrease by 38 kWh/yr during
the cooling season. Outside the cooling or heating seasons, the energy saved does not
significantIy etreet ether heat-reIated loads. Note that ifone propagates these net savings at
the dwelling back to the natural resources, the accumulated benefits can be considerably
more substantiaI depending on the generation mix.
The purpose ofthis example is to report on the impact ofDSM performance improvement
measures from both the energetic and exergetic points ofview and with emphasis on cross
etlèets. One important reason for developing broad perspectives in anaIysing DSM strategies
is to provide planners with more systematic means to evaluate and prioritize different PI
alternatives.
4.3.1 :Basic energy conversion model element
To understand how an energy model is constructed, first consider Figure 4.7 showing an
arbitrary basic energy conversion element. Let Et and E.z represent the input and output
yearly energy values of tI:~ element. SimiIarly Xl and X 2 represent the corresponding
exergetic values. Let TJ and e represent respectively the energetic and exergetic efficiencies.
Then, the following relations hold,
(4.1)
• Applications of Exergy Analysis in Eleetric Energy System Planning
1E, ~ E2 ...,
En~ Conversion,.
~anal!
X,.... tl. E ~~ ,
,t ,ifx =Excrgy x ="y~cbt dcslnJclion ... ~pated
55
•1 -----1
Figure 4.7 Energy conversion elemen~
(4.2)
Since energy is conserved,
(4.3)
the energy dissipated in the form ofheat to the environment is,
(4.4)
•On the other band, exergy is not conserved in any conversion process, 50 that,
• Applications of Exergy Analysis in Electric Energy System Planning S6
(4.5)
where x.- is the exergetic content ofthe energy dissipated as heat. The irreversible exergy
destruction, X-, that a1ways takes place is given by,
(4.6)
•In addition, for any process it is possible to estimate what fraction of the input (al) and
outpl1t lexJ energies Cêdl be converted to available work (exergy). Then,
(4.7)
Because ofequations (4.1), (4.2) and (4.7), it is necessa'Y that the energetic and exergetic
efliciencies satisfy the ratio,
(4.8)
•Table 2.1 in Chapter 2 shows, for a set ofenergy conversion devices, the as.<;umed values of
the efficiencies according10 the FIISt and Second Principles ofThermodynamics ('1'), E) as weil
as the fraction ofthe input (am) and outPut (a....) energy that can be converted to work. In
this Table, the a's are estimated ~snming the most efficient available technology to convert
a given form ofenergy into available work.
• Applications of Exergy Analysis in Electric Energy System Planning 57
•
For example, for a 1 kW basc:board space heater, where the input is electricity and the
output is heat al 20 degrees C, Ctl is approxirnately 95% (based on the highest efficiencj of
electric motors) while ~ is 6.8% (based on the ideal Carnot cycle efficiency with
temperantres of20 and 0 degrees C). Since an electric baseboard heater is 100"10 energetically
efficient, its exergetic efficiency (e) is 100* 6.8/95 = 7.2%. Therefore, whereas 100% of
the input energy is converted to a usefu1 output in the form ofheat, 92.8% ofthe input exergy
is destroyed by this process.
4.3.2 Mode! with cross-effects
Figure 4.8 shows another example ofa su:Jsystem with a combination ofbasic elements
including cross-effects. It consists of air-conditioning (AC), light (LT) and space heating
(SR). The end-uses are cooling (C), illumination (1) and heating (H). In this example, ooly
the energy quantities are disp1ayed. A simiIar set ofvariables and relations apply to the exergy
balance. The input/output relation ofeach energy conversion element in Figure 4.8 yields,
(4.9)
(4.10)
(4.11)
•cross-effects complieate the pieture as seen in Figure 4.8 since seme fraction (~I) of the
lighting device (LT) losses, (1-1lJ E:" as weil as another fraction (en) ofthe illumination
end-use ~atributes to the heating requirement. A similar but opposite effect occurs with
respeci: to the cooling needs. These cross-effects are modelled by,
• Applications of Exergy Analysis in Electric Energy System Planning 58
• Figure 4.8 Typical subsystem containing cross-effects.
1 - E- 4
c
(4.12)
(4.13)
(4.14)
•
where E:z is the output ofthe Air Conditioner (AC) and E, is the net cross-e1fect on the AC
due to the heating effects ofthe Iighting process. Clearly, for a given cooling end-use, C, the
impact ofthe cross-effeet, E" is to force an increase in the output energy ofthe AC,~.
Alternative1y, the impact ofthe Iighting cross-effeet, Eu. is to decrease the output .:>fthe
SpaceHeater, ~, in order to meet the bearing end-use, H. The cros.<.-t...fect energi~, E, and
• Applications of Exergy Analysis in Electric Energy System Planning
El2 , each have two components,
59
(4.15)
(4.16)
the component~ is a fraction (cu) ofthe Iighting device losses during the cooling season,
while ElO is a fraction (c:n) ofthe Iighting device losses during the heating season.
•E, = Cil (1 - TIL ) ~ (4.17)
(4.18)
Simi1arly, Es and ~l respectively represent fractions ofthe summer and winter Iighting end
use which are converted to heat and affect the cooling and space heating end-uses. These
fractions Cat are estimated in the model from utility and government statistics [Moreau and
Stricker, 1994]. It should be noted that Er +~o must be less than the total yearly Iighting
load losses, (1- "ù.) E:J, due to the fàct that sorne losses occur outside the cooling or heating
seasons. Simi\arly, Es+~l must be less than the illumination, 1, due to two facts: One is that
sorne ofthe Iight escapes through windows without being converted to heat indoors. The
second, as before, is that the heat produced by Iight bas no effect on heat-related loads
outside ofthe cooling or heating seasons.
• Applications of Exergy Analysis in Electric Energy System Planning 60
•
•
4.3.3 System impact of DSM PeJformance Improvement strategies
description ofCase-studies
In this section, a representative set ofcase-studies is discussed including:
(1) The impact ofperformance improvement DSM strategies at various system levels,
namely a;,pliance, customer, utilities and overa!l naturaI resources.
(2) The impact ofthese PI measures in terms ofenergy and exergy savings at the various
system levels.
(3) The impact ofCTOss-effects on heat-re\at~ loads.
(4) The impact ofPI measures under different system configurations. These consist of
various combinations ofnatural resources, power plants, refineries and space-heating
devices.
(5) The effect ofdifferent climates and dwel1ing insulation levels.
Table 4.4 Energy system configurations considered.
Type Type ofGeneration Type ofSpace Heating
Cl Electric base-board
C2 Hydro-e1ectricity Heat-pump ground-to-air
C3 Direct oil\gas heating
C4 Electric base-board
CS Thermal-electricity Heat-pump ground to air
C6 Direct oil\gas heating
• Applications of Exergy Analysis in Electric Energy System Planning 61
•
•
TAble 4.4 presents the savings assumed at the appliance level due to the implementation of
three different PI alternatives, namely, the introduction at the residential level of more
efficient lighting, e1ectric water heaters, and refrigerators. These energy data (assuming a
well-insulated dwelling in Montreal) [Moreau and Stricker, 1994] represent the predicted
yeariy savings for the appliance only, that is, without cotsidering cross-effects. The exergetic
savings shown in Table 4.4 are based on the assumption that 95% ofthe energy savings could
be converted into work through an efficient e1ectric motor. To evaluate the impact ofPI
measures at the various levels ofan energy system (appliance, customer, utilities and natura!
resources), six diffèrent energy system configurations were studied as descn1led in Table 4.5.
These system configurations were simulated and include two types ofe1ectric generation:
hydro and thermal, and three types ofspace heating devices: baseboard considered being
100% efficient, ground-to-air heat-pump with a coefficient ofperformance of300% and a
direct oil or sas heater with 81% efliciency. These configurations were selected l>ecause they
represent extIeme cases of generation and space-heating types. Other space heating
alternatives such as the more common air-to-air heat-pump lie in between the two e1ectric
space heating types shown in Table 4.5.
The Sl..JÏngs at the customer Ieve\ are definee: by the net equivalent kWh yearly savings from
Table 4.5 Energy and exergy savings at the appliance Ieve\.
Savings at the Appliance Leve)
Performance Improvement in equivalent kWb/yearMeasure
Energyt Exergy
PI-l ImprovedRefrigerator 353 335
PI-2 Efficient Eectric Water Heater 438 416
PI-3 Replacement ofIncandescent by 518 493Compact Fluorescent Light Bulbs
.
• Applications of Exergy Analysis in Electric Energy System Planning
the heating and cooling devices including cross-effects.
62
•
•
Two types ofutiIities are considered in this thesis, namely, e1ectric and g3Sfoil. The savings
due to the introduction ofa PI measure are calculated for each utility at the input level.
Finally, the combined utility savings define the net naturaI resource savings.
4.3.4 Evaluation 'IfPI Measures
Tables 4.6, 4.7 as weil as the Tables BI to B4 shown in the Appendix, summarize the
simulation resuIts obtained for the cases defined in the previous section. The Tables contain
six rows, each corresponding to a system configuration as Iisted in Table 4.4. In addition, the
Table 4.6 Energetic savings at diffèrent system levels for PI 'Improved Refiigerator'.
Encrgy Savingsin cquivalent kWhlycarJc:ustomer
CoofigmalionNet
Appliancc Cooling Sp8l:C Dwc1Iing Electtic GaslOii RcsourceHeating Uti1ity Uti1ity Savings
Cl 353 27 -216 164 192 0 192
C2 353 27 -72 30B 360 0 360
C3 353 27 -266 114 444 -304 140
C4 353 27 -216 164 561 0 561
CS 353 27 -72 30B 1051 0 1051
C6 353 27 -266 114 1296 -304 992
• Applications of Exergy Analysis in Electric Energy System Planning 63
•
•
columns of each Table indicate the savings at different system levels. Fmally, for each
Performance Improvement measure listed in Table 4.4, two tables are shown, one for energy
and another for exergy savings.
The numerous results shown in these six Tables are analysed according to the foUowing
points:
(A) Impact ofcross-effects;
(B) Comparison ofsavings at different system levels and configurations;
(C) Comparison ofenergetic and exergetic savings;
(ù) Comparison ofdifferent PI measures;
(E) "fhe effect ofdiiferent climates and dwelling insulation levels.
As discussed in above, because ofthe influence ofcross-effects on heating and cooling loads,
the net savings at the dwelling level di1fer significantly from the savings at the appliance level.
Table 4,7 Exergetic savings at different system levels for PI 'Improved Refrigerator'.
ExclBY Savinssin equivoJc:nt kWhlyoarl=-
ConfigurationGasIOiI Net
Appliancc Cooling Spacc DweUing EIcclric UtiJity ReoowccH<aling UtiJity Savinss
Cl 335 26 -205 156 183 0 183
C2 335 26 -68 293 342 0 342
C3 335 26 -98 263 422 -113 309
C4 335 26 -205 156 208 0 208
C5 335 26 -68 293 389 0 389
C6 335 26 -98 263 479 -113 366
• Applications of Exergy Analysis in Electric Energy System Planning 64
•
•
In order to discuss this point, consider Table 4.6 showing the energy savings for the PI
measure 'irnproved Refiigerator'. The following observations cao be made:
(i) Because ofcross-effects, the net energetic savings at the customer (dwelling) level are
considerably less than at the appliance level. The net eustomer energetic savings f::nge
from 32% to 87% of those at the appliance leve1 depending on the system
configuration.
(ü) Column 2 indicates the assumed savings at the appliance leve1. Column 3 shows the
savings in the cooling load during the summer months, while column 4 indieates
negative savings in the heating system due to the faet that the improved refiigerator
releases less residual heat during the heating season. These savings differ according
to the efficiency ofthe space heating system. Thus, the least efficient space heater
(direct heating) must work harder to make up for the missing residual heat resuIting
in a reduced net savings at the dwelling 1eve1. Column 5 shows the net savings at the
dwe1ling whieb are the sum ofcolumns 2,3 and 4. The worst impaet ofcross-effects
occurs for configuration C3 (hydroe1ectric generation combined with direct oil/gas
heating) where ofthe 353 kWh/year saved at the appliance leve1 only 114 kWh!year
or 32"10 are saved at the dweIIiIlg 1eve1. The least damaging impact ofcross-effects at
the dwelling 1eve1 takes place for configurations C2 and CS, both of~hich use the
very efficient ground-to-air heat-pump.
4.3.5 ComparisoD of savings at ditTerent system leve1s
The net savings propagate beyond the dwe1Iing leve1 toward the utilities and natural resources
by diffdeut amocnts depending on the system configuration and the individuaI efficiencies of
each energy conversion process (See Table 2.1 in Chapter 2). Continuing with Table 4.6, the
• Applications of Exergy Analysis in Electric Energy System Planning
following observations are made:
65
•
•
(i) Columns 6 and 7 show respectively the savings at the electric utility and gas or oil
utilities. Column 8 represents the total natural resources saved which is the sum of
the savings at a1l utilities;
(ri) The savings at the electric utility are always larger than at th~ dwelling due to
transmission and generation losses;
(ili) In the configurations where there is direct space heating, the savings at the electric
utility are even higher since the increased demand on space heating due to cross
effects will affect only the gas/oil utility where the savings are negative;
(iv) The maximum savings at the electric utility level occur for C6 (thennoelectric
generation and direct heating) mainly due to the low efficiency ofthe thennal power
plant (35%);
(v) At the resource level (column 8), the savings are highest for configurations CS and
C6, confirming that the greatest impact ofa PI measure is felt in the least efficient
system.
4.3.6 Comparison ofenergetic and exergetic savings
The corresponding ex:ergetic savings ofthe PI 'Improved Refiigerator' are shown in Table
4.7 The fullowing observations are made:
(i) Because ofcross-effects, the net ex:ergetic savings, at the dwelling level, lire aIso
lower than at the appliance level.
(ri) When two dilfaent sources ofenergy are used in a given configuration, the exergetic
Applications of Exergy Analysis in Electric Energy System Planning 66
•
•
savings at the natura! resource and dwel1ing levels are comparativel)' higher than the
energy savings. Thus for C3 (hydroelectric generation plus direct heating), as an
example, the exergy savings at the natura! resource level are 93% of those at the
appliance level while the comparable energy savings are only 40%. This is e.xplained
by the faet that the exergy content in oil or gas is lower (37%) than in e1eetricity
(95%). Thus, for every extra equivalent kWh demand in oiVgas only 0.37 kWh
equivalent ofextra exergy will be required. These differences in behaviour highlight
the importance ofexergetic analysis in systems with multiple types ofenergy sources
and conversion processes.
(ùi) Comparing Cl (hydroe1ectric generation plus baseboard space heating) with C3
(hydroelectric generation and direct space heating), at the natura! resource level, the
energy savings ofCl are 31010 higher than for O. Alternatively, the corresponding
exergy savings for Cl are 69% lower than for C3 for the same reasons as in (ü).
(iv) Although from the point ofview ofenergy, the savings at the resource level vary over
a range of approximate1y one to seven for the six configurations studied, the
corresponding eltergy savings only vary over a range ofone to !Wo. Thus, the impact
ofthis PI measure from the point ofview ofexergy savings is not as striking as from
the energy savings perspective.
4.3.7 Comparison ofdifferent performance improvement measures
Tables B2, B3, B4 and B5 in the Appendix show the corresponding energetic and eltergetic
savings for the rernaining !WO PI measures: 'Efficient Electric Water Heater' and
'Replacement ofIncandescent by Fluorescent Light Bulbs'.
• Applications of Exergy Analysis in Electric Energy System Planning
Table 4.8 Use ofthe energy in an typical ga;:..,line powered ICEV.
67
•
•
Fraction ofthe energy contentin the gasoline %
Energy Conversion StepCrouse & Anglin DeCicco & Ross Québec
(1987) (1994) (1992)
1. Lest in cooling water air and oil 3560
2. Lest in the exhaust gas 35
3. Lest in the engine fric: :')n 580.021
4. Lest in power train 10
5. Lest in the brakes - 4.7
6. Left to propel the vehicle 15.0 14.3 20.0
7. Total 100.0 100.0 100.0
The foUowing points are made about PI measures in general:
(i) The absolute savings at the appliance Ievel difi'er over the PI'S, but the relative effects
at the various system levels are approximately in the same proportion. The observed
percent difFerences among the prs arise mainly due to variations in the cross-effects.
For example, considering configuration C6, the energy savings at the natura1 resource
Ievel as a percent ofthe appliance savings are respectively 2810/0, 274% and 280% for
the three PI measures;
(û) Other PI measures, not diSQIssed here, could result in much wider differences due to
variations in cross-elfects. For example, the use ofan efficient washing machine with
cold water bas a low cross-effect impact on the heating load;
• Applications of Exergy Analysis in Electric Energy System Planning
4.3.8 The efTect of difTerent dimates and dwelling insulation leveJs
68
•
•
The effect ofthe climate on the energetic and exergetic savings for a given PI measure was
tested in the following Canaclian cities: Montreal, Vancouver, WlDlIÏpeg. Toronto, Halifax and
Fredericton. The PI measure 'Efficient E1ectric Water-heater' was simulated for these cities
fo~ both configurations Cl (hydroeJectric generation with eJectric baseboard space-heating)
and C4 (thermoeJectric generation with eJectric baseboard space-heating). The energetic and
exergetic savings varied between 87"/0 (W1DDÏpeg) and 135% (Vancouver) of the savings
achieved in Montreal. For the cities studied, it seems that the warmer the climate, the Jess
significant is the impact ofcross-effects.
Three types ofdwe1ling thermal characteristics were considered: Type A (poorly insulated),
type B (weil insulated) and type C (very weil insulated). The influence ofthe dwe1ling thermal
cbaracteristics were studied for the system configurations Cl and C4. The energetic and
exergetic savings varied between 95% (dwe1ling poorly insulated) to 112% ( dwe1ling very
well insnJated) ofthe savings in the dwe1ling type B (well insulated).
For the cases studied, the climate bas a stronger effect on both energy and exergy savings
tban the thermal characteristics ofthe dwe1ling
4.4 Energetic and Exergetic Impact ofElectric Vehicles in Canada
4.4.1 Introduction
The Canadian transportation sector consumed 26% ofthe totaI energy consumption in 1995.
Of this total, 82% accounts for the road transportation and the remaining 18% for air, water
Applications of Exergy Analysis in Electric Energy System Planning
Table 4.9 Electric vehicle characteristics.
69
•
•
Sub-compactSmall van Large van
EV perfonnance item car
1995 2010 1995 2010 1995 2010
1. Driving range (km) 160 320 160 320 130 240
2. Extra weight (kg) 560 266 812 457 809 397
3. Efficiency loss factor, Wf (%) 18.6 12.0 19.0 13.6 16.6 10.1(Due to extra weight in the EV)
4. Consumption ratio lCEVIEV, Cr 2.62 4.04 2.62 4.04 2.71 4.25
5. EV consumption ( kWnIIan) 0.35 0.20 0.48 0.30 0.62 0.38Source: [Wang & DcLuchi. 1992]
and rail transportation [Canada, 1994).
The recent and predicted improvements in eIectrical vehicles (EV) technology raises some
questions in the energy planning sector regarding primary energy consumption, petroleum
displacement, air emissions and system efficiency.
A more intensive use ofEV's is expeeted to reduce air emissions [Gellings, 1993]. The
principal emissions that contribute to urban air pollution are volatile organic compounds
(VOC) and nitrogen oxides (NOx), bath precursors ofozone and carbon monoxide. Canada
bas signed a series ofprotocols [Canada. 1992) to: (i) Reduce the VOC emissions by 30010
ofthe 19881eve1sby 1999; (ù) Reduce annuai emissions ofNOx from stationary sources by
100,000 tonnes per year below the year 2000 forecast leveI of970,OOO tonnes. Besides the
beneficial effects of decreasing the air emission leve1s, the adoption ofEV will certainly
dccrease the energy dependency leveI from energy sources outside the respective province
or planning region.
Applications of Exergy Analysis in Electric Energy System Planning 70
To perform the energetic and exergetic anaIysis ofthis scenario it is important to evaluate the
efficiencies ofthe processes in question. T1ùs is the subject of the ne.'I."! section.
4.4.2 Evaluation of dectric vehicle (EV) and intemal combustion
engine vehicle (lCEV) efficiencies.
Analysis ofthe energy conversion processes that take place in an internai combustion engine
vebicle (ICEV) shows that only a small fraction of the energy content in the fuel is aetually
used to prepel the car [Creuse & Anglin, 1987, DeCicco & Ross 1994, Québec 1992]. Table
4.8 shows the fraction ofthe energy content in the gasoline that is aetually used for different
energy conversion stages in the ICEV's. Qnly between around 14.3% and 20010 ofthe heat
content ofthe fuel is used to propel the car. These figures rep:-esent the efficiency assessed
by either First or Second Principle since it is considered here that the end-use road
transportation is 100% exergy (work). The dissipated energy, at least 80%, is used mostly
for: cooling, braking, fiiction and gases escaping through the exhaust system.
Table 4.10 Forecast fuel consumption (IanIl) and weight (kg) of ICEvt.
Model
Year Item Sub-compaet Small Vans Large VansCars
kmJ1 9.8 6.8 5.11995
kg 1248.5 1747.9 2111.1-c_
kmJ1 13.4 8.2 6.12010
kg 1066.9 1566.3 1974.9.
t ICEV = intemal combUSllon engmc vcbic1esSource: (Wang & DeLuchi, 1992]•
• Applications of Exergy Analysis in Electric Energy System Planning
Table 4.11 First (1]) and Second (e) Principle efficiencies for ICEV and EV.
71
•
•
Sub-compact car and sma\I van
Type ofVehicle 1995 2010
n e n e
1. Internai Combustion 14.5 33.7 19.8 46.0Engine Vehicle ICEV
2. E1ectrica1 Vehicle EV 30.9 32.5 70.4 74.1
Wang and DeLuchi (1992) have conducted a study about the impact ofe1ectric vehicles on
the primary energy consumption and petroleum displacement. The ana\ysis was conducted for
difièient sizes ofvehic\es, subcompaet cars, small vans and large vans for the years 1995 and
2010. In that study, the authors compared the consumption per kilometre using the following
primary energy sources ofenergy: coal, crude oil, naturaI gas and biomass.
It was shawn that, between 1975 and 1990, the fuel consumption ofnew passenger cars had
improved from 5.6 to 9.8 km/\, resulting in an improvement rate ofapproximately 3.8% per
year during that period. The internai combustion engine vehicle (ICEV) is expected to further
improve its fuel consumption by 1.55% between 1990 and 2010 under a cost-effective
scenario, reaching 13.41an11 for a subcompact car. At the same time, the subcompact car
weight is expected 10 decrease from 124910 1067 kg. It is important to note at this time, that
severa! studies have demonstrated that alO"I. change in the vehic\e weight canses a 6%
change its performance [Unnewehr & Nasar, 1982; Bnssmann, 1990; Amann, 1990; Bleviss,
1988]. Table 4.9 shows the substantial forecast fuel consumption and weight for the internaI
combustion engine vehic\es.
Table 4.10 presents SOIJ1(; characteristics ofthe e1ectric vehic\es, inc\uding the driving range,
• Applications of Exergy Analysis in Electric Energy System Planning
Table 4.12 Configurations considered for road transportation.
72
•
Code Natural resource Type ofvehic1e
A ICEVPetroleurn
B EV
C EVBiomass
D ICEV
1E NaturaiGas EV
F ICEVCoal
G EV
H Hydro Potential EV
the extra weight of the EV compare<! to the ICEV and the EV energy consumption in
(kWhJlan). Other cbaracteristics ofthe EV are shown in Table 4.9 as weil such as efficiency
1055 fàctor, Wc and the consumption ratio ICEVIEV, Cr
The FPT efliciency of the ICEV (Thav) considered in this study was 14.5 %, for 1995. The
FPT efliciency ofthe EV ('lEV) is given by,
'lEV = TJJCEY Cr (1 - W) (4.19)
whereCristheconsumptionratio ICEVIEV shown in Table 4.10. Wc is the efliciency 1055
fàctor due to extra weight ofthe EV and it is given by [Wang & DeLuchi, 1992]:
•(4.20)
• Applications of Exergy Analysis in Electric Energy System Planning 73
•
•
where Cr is the consumption ratio ICEVIEV shown in Table 4.10. Wr is the efliciency 1055
factor due to extra weight ofthe EV and it is given by [Wang & DeLuchi, 1992]:
Table 4.11 presents, for a subcompact EV and ICEV car and a small van, the First and
Second Principl~ efficiencies for 1995 and 2010. The SPT efliciencies of the cars were
calculatOO estimating that the available work in the fossi! fuel source is 43% and in the
e1ectricity 95%. The usefuI work ofthe enC:-use road transportation was co~derOO to be the
same as the usefuI energy produced bythe car. AnalysingTable 4.10, it is notOO th:lt, in 1995,
the FPT efliciency for the lCEV was less than halfthat of the EV but the FPT and SPT
efficiencies were around 33%. For the year 2010, bath FPT lI!Id SPT efliciencies ofthe EV
are substantially larger than the equivalent for the lCEV.
4.4.3 Energy system with EV and ICEV
A rational use ofthe different sources ofenergy with respect to their exergetic content is
accomplished bythe appropriate matching ofthe energy source to the end-use required. For
this reason, it is important to evaluate the EV and lCEV efliciencies under different system
configurations. Wang and DeLucbi (1992) estimate the overall FPT efficiency ofseven energy
production processes, having as primaJy energy source petroleum, coat, naturaI gas and
biomass. They estimate the process efficiency from the naturaI resource to the service station
(lCEV case) or to the wall outlet (EV case). In this thesis, the configurations studiOO by
Wang and DeLucbi (1992) were extendOO to include hydroelectric resources. In addition, the
FPT and SPT efficiencies from the naturaI resources to the road transportation end-use were
calcu1atOO. Table 4.12 shows the eight configurations that were studied. Figure 4.9 shows
the energy transformation mode! considered for road transportation. In order to calculate the
exergetic efficiency ofeach configuration, the available work in each ofthe sources must be
• Applications of Exergy Analysis in Electric Energy System Planning
.----~o{oGT__---4..
74
• CR - =de ror:ow:ryCT-cn:dc1nDsporlCF - crudc roliDayGT - gasolinc1nIIlspcxtFT - fùcI oillrllllsperlllÏOIlP 0 - J>O'M:r plaIIt petroIcumTI. - tnmsmissiœ bDC
•
YJgUre 4.9 Road transportation mode! for intemal combustion engine vehic1es and e!ectricalvehic1es.
estimated. In this thesis it is collSÏdered that the available work in petroleum, biomass, natural
gas, coal, hydro potential is43, 36, 43, 43, and 95% respectively. Table 4.13 and 4.14 specify
the FPT efliciency ofeach ofthe energy conversion steps collSÏdered, for the years 1995 and
2010, respectively.
Finally Table 4.15 summarizes the overa11 FPT and SPT eiiiciencies of each of the
configurations collSÏdered in Tables 4.13 and 4.14. Analysing Table 4.15, note that:
Regarding the year 1995:
• Applications of Exergy Analysis in Electric Energy System Planning 75
•
•
Table 4.13 F1I'St Principle efficiency for eight configurations for road transportation in 1995.
1 EIT"ICieDcy.1n pemDt (1995) 1ConJï""llltion (A) Pc:trolcum-ICEV ConJi""..ation (B) Petrolcum-EV
CR - Crude Rccovcty 96.9 CR - Crude Rccovcty 96.9
CT - Crudc llllnapOrt 98.9 CT· Crudc llllnapOrt 98.9
CF· Crude Rcfincry 87.4 CF· Crode Rcfincry 95.2
GT • Gaaoline Transport 99.2 FT· Fuel Où Transport 993P_O, Power Plant Petrolcum 32.0
TL· Transmission Linos 92.0
Sc:rvicc Station 83.1 Wall Outlcr 26.7
lntcmal Combustion Engine Vchicle (ICEV) 14.5 E1ccrric Vchiclc (EV) 30.9
TJ p tCF.V 12.1 TJ p F.V 8.3
ConJiauration (C) BiOlllllSS-EV ConJiauration (E) Narura1 Gas-EVBP ·Biomass Production 92.7 GE· Gas Extraction and Gathcring 93.7
BT • Biomass Transport 99.2 GT • Gas Transport 963
BL· Biomass Liquefaction 60.0 P_G • Power PlantNatulll1 Gas 323LT • Syncrudc Transport 99.0 TL· Transmission Linos 92.0
P_B· Power Plant Biomass 32.5
TL· Transmission Linc 92.0
WalIOuUcr 163 WalIOuUct 26.8
Elccrric Vchiclc (EV) 30.9 E1ccrric Vchiclc (EV) 30.9
TJ B F.V S.O TJI'UV 8.3
ConJiRUllltion (F) CooI·1CEV ConJiauration (Q) CoaI-EVCM· Cool Mining 98.1 CM· Cool Mining 9S.l
T_1 • Cool Transport 993 T_2· Cool Transport 99.0
CL· Cool Liquefaction 60.0 P_C • Power Plant Cool 33.5
SR· Syncrudc refincry 87.4 TL· Transmission Lincs 92.0
ST· Syngasolinc Transport 99.2
Sc:rvicc Station 50.7 WalIOuUct 29.9
Intcmal Combustion Enginc Vchiclc (ICEV) 14.5 EIccrric Vchiclc (EV) 30.9
'1 B F.V 7.4 TJ C F.V 9.2
ConJiauration (D) Biomass-ICEV ConJiauration (HlH~EV
BP·Biomass Production 92.7 P_H· Hydra PowerPlant 95.0BT • BiomassTransport 99.2 TL· Transmission Iioc 94.0
BL ·Biomass Liquefaction 60.0
LR· Syncrudc Rcfincry 87.4
RT· Rcfincd Transport 99.2ScrviocStation 4S.2 WalIOuUct 87.4
lDtcmaI Combustion Enginc VchicIc (ICEV) 14.5 EIccrric VchicIc (EV) 30.9
11 R ,,...,, 7.0 11 v ""27.0
Applications of Exergy Analysis in Electric Energy System Planning 76
•
•
Table 4.14 First Principle efliciency for eight configurations for road transportation in 2010.
ElrlCÎene>',1n perœnl (2010)
Confi.uration (A) PctIDlcum-1CEV Confioullltion (S) PctIDlcum-EVCR - Crude Rccovcty 96.9 CR - CNde RccovCl)' 96.9
CT - Crudc llllnSpOrt 508.9 CT - Crudc llllnSpOrt 98.9
CF - CNde RcfinCl)' 87.4 CF - Crudc RefinCl)' 96.:!
GT· Gasoline Transport 99.2 FT - Fuel Cil Transport 99.3
P_0 - Power Plant PctIDlcum 39.0
TL - Transmis3ion Lines 94.0
Sctvicc Station 83.1 WallOudct 33.6
intemal Combustion Engine Vehicle (lCEV) 19.8 E1cctrie Vehicle (EV) 70.4
TI P leEV16.5 11 P F.V 23.6
Confilt\ltlllion (C) BiOllll.....EV Confi.Ullltion CE) N.tural Gas-EVBP ·BiomassPtoduction 92.7 GE - Gas Extraction and Gathcring 93.7
BT - Biomass Transport 99.2 Gr· Gas Transport 9S.3
BL - Biomass Liquefaction 80.0 P_G- Pnwer Plant N.tural Gas 43.0
LT - Syncrudc Transport 99.0 TL - Transmis3ion Lines 94.0
P_B - Power Plant Biomass 35.0
TL - Transmis3ion Line 94.0
WallOudct 14.5 WallOuUct 36.5
E1cctrie Vchicle (EV) 70.4 E1cctrie Vchicle (EV) 70.4
TI B F.V 10.2 11 N F.V25.7
Confiouration (F) Coa1-ICEV Confio=tion (G) Coa1·EVCM - Coa1 Mining 98.1 CM· Coa1 Mining 98.1
T_1 - Coa1 Transport 993 T_2 • Coa1 Transport 99.0
CL - Coa1 Liquefaction 70.0 P_C • Power PIanI Coal 39.0
SR· Syncrudc refincty 87.4 TL· Transmission Lines 94.0
ST· Syngasolinc Transport 99.2
Sctvicc Station 59.1 Wall 0u1Ict 35.6
intemal Combustion Engine Vchicle (lCEV) 19.8 E1cctrie Vchiclc (EV) 70.4
11 B EV IL7 TI c F.V25.1
Confio=tion (D) Biomaso-lCEV ConfiOWlltion IH)HWIOoEVBP·Biomass Ptoduction 92.7 P_H-H~PowerPlanI 95.0
BT·Biomass Transport 99.2 TL - Transmission Iinc 94.0
BL ·BiomassLiquefaction 60.0
LR· Syncrudc RcfinCl)' 87.4
RT·Rcfinod Transport 99.2
Sctvicc Station 48.2 WallOudct 893
intema1 CombustionEnginc Vchicle (lCEV) 19.8 E1cctric VchicIc (EV) 70.4
n .. '''"' 9.511 " "'
62.9
• Applications of Exergy Analysis in Electric Energy System Planning 77
•
•
Table 4.15 Frrst and Second Principle efficiencies for ICEV and EV different configurations.
1995 2010Configuration
E'lJ E 'lJ% % % %
A Petroleum - ICEV 12.1 28.1 16.5 38.4
B. Petroleum - EV 8.3 19.3 23.6 54.9
C. Biomass - EV 5.0 13.8 10.2 28.3
D. Biomass - ICEV 19.4 16.3 9.5 26.4
E. Natural gas - ICEV 8.3 19.3 25.7 59.8
F. Coal- ICEV 7.4 17.2 11.7 27.2
G. Coal-EV 9.2 21.4 25.1 58.4
H.Hvdro-EV 27.0 28.4 62.9 66.2
corresponding to the Iùghest SPT efficiency as weil. The second Iùghest FPT efficiency is the
traditional configuration A (petroleum and lCEV);
(ù) The SPT efficiency ofconfigurations A and H are not much different in spite ofthe
greater discrepancy in the FPT efficiencies for these two configurations. This is due
to the faet that the exergy content in the hydro potential is higher (95%) !han in
petroleum (43%);
(JÜ) On the other band the configuration with minimum FPT and SPT is C (biomass and
electricity).
(i) The configuration with the highest FPT efficiency is H (hydro electricity and EV)
Regarding the forecasts for the year 2010:
• Applications of Exergy Analysis in Electric Energy System Planning
Table 4.16 Electric energy production for cliffcrent fuel types in Canada. 1()92.
78
•
•
Region Cool Oi!Natural
Nuclear Hydro Othcr TotalGas
1. Canada 16.7 2.7 2.2 15.2 62.2 l.l 100.0,
2. Newfoundland 0.0 4.9 0.0 0.0 95.1 0.0 100.0
3. P.E.!. 0.0 100.0 0.0 0.0 0.0 0.0 100.0
4. Nova Scotia 61.7 27.5 0.0 0.0 9.2 1.6 100.0
5. New Bnmswick 7.5 41.9 0.0 30.3 18.6 1.7 100.0
6. Québec 0.0 0.8 0.0 3.1 96.1 0.0 100.0
7. Ontario 19.8 0.5 1.7 48.1 28.7 1.3 100.0
8. Manitoba 1.0 0.0 0.0 0.0 98.8 0.2 100.0
9. Saskatchewan 70.5 0.3 6.3 0.0 21.6 1.3 100.0
10. Alberta 81.4 0.0 12.4 0.0 3.3 2.9 100.0
II. British Columbia 0.0 0.5 2.6 0.0 94.5 2.3 100.0
12. Yukon and N.W. T. 0.0 25.7 9.0 0.0 65.3 0.0 100.0
5omee. [Canada, 19921.
(i) An configurations that use EV(B, E, G, H) with the exception ofbiomass have higher
FPT and SPT efficiency than the traditional option ofcrude oil and ICEV;
(Ji) Again configuration H bas the higilest FPT and SPT efficiencies among the
configurations studied;
(IÜ) The re1ative difference between the FPT efficiencies is much higher than between the
correspondïng SPT efficiencies;
(iv) It is ÏDteresting to note that configuration A (petroleum and lCEV) is less efficient
than configuration B (petrolewn and EV), indicating that, ifother restrictions will not
apply (such as car autonomy or cost ofthe e1ectric vehicle) the EV will be certainly
• Applications of Exergy Analysis in Electric Energy System Planning
Table 4.17 EV efficiencies in the Canadian provinces.
79
•
•
EV EfficiencyConsidering Generation:Mix (%)
Region1995 2010
1] E 1] E
1. Canada 20.3 24.7 45.7 57.3
2. Newfoundland 26.1 27.8 60.3 64.3
3. P.E.!. 9.4 16.3 9.5 26.4
4. Nova Scotia 10.8 20.5 24.1 49.8
5. New Brunswick 12.6 18.9 20.6 36.2
6. Québec 26.3 27.9 60.8 64.7
7. Ontario 14.4 20.8 28.2 44.8
8. Manitoba 26.8 28.3 62.4 66.1
9. Saskatchewan 12.9 22.7 33.1 59.7
10. Alberta 9.6 21.2 26.0 58.0
11. British Columbia 25.9 27.7 60.4 64.9
12. Yukon and N.W. T. 20.8 24.5 45.8 55.4
wide1y adoptee\, even in utilities with only thermoe1ectric power plants;
(v) The ICEV bas a much widervariation in their SPT efficiencies than the corresponding
EV alternatives.
Table 4.16 shows the generation mile in 1992 for different Canadian provinces [Canada
1992]. Note that hydroe1ectric resources account for approximate1y 6()O/O ofthe primary
eneIgy use for e1ectric generation. In five ofthe Canadian provinces, petroleum constituted
more than 25% ofthe generation mix. However, in the remaining provinces petroleum always
represents less than 5% ofthe generation mile.
• Applications of Exergy Analysis in Electric Energy System Planning 80
•
Table 4.17 shows for the EV, the FPT and SPT efficiencies for the Canadian provinces for
1995 and for 2010. Note that, provinces with a high percentage ofhydro generation such as
NewfoundIand, Québec, British Colwnbia and Manitoba have lùgher efficiencies than the ones
with high concentration of fossil or nuc1ear power plants. The overall FPT and SPT
efficiencies for Canada in 1995 are respectively bigger and smal1er than the corresponding
configuration A (petroleum and ICEV). On the other band, comparing the corresponding
values for 2010, the EV in Canada is, by both FPT and SPT perspectives, more efficient than
the configuration A (Table 4.15).
4.4.4 Petroleum displacement by EV
EV's are potentially effective displaœrs ofpetroleum becallse, in Canada, in general, much
ofthe e1eetricity generation is hydroeIeetric. The amount ofpetroleum displaced is calculated
by:
1 Poil- - ----=----d = _T)...:;A,--_T)-,P;...-~o_T)-=:FT=--T)..;;;CF,--T),;;;CT,--T)~CR
1
1JA
(4.21)
•
where T).. is the FPT efficiency ofthe configuration A, Pail is the proportion of oil in the
generation mix and T)p_o, TJn, TIen 1l:r, 'rh equal the FPT efficiencies ofthe thermoe1ectric
power plant, fuel oil transport, crude refinery, crude transport and crude recovery,
respectively.
The amount of petrolemn displaced as a proportion oftbc amount used in road transportation
fortheyears 1995 and 2010 is shown in Table 4.18. The amount ofpetroleum displaced for
Canada would be at least 96% in 1995 and 97.7 % in 1995 and 2010. In other words, each
• Applications of Exergy Analysis in Electric Energy System Planning
Table 4.18 Petroleum displacement by the adoption ofEV in 1995 and 2010.
81
•
•
Petroleum displacement by the adoption ofEV,
Region %
Year 1995 Year2010
1. Canada 96.0 97.7
2. Newfoundland 92.8 95.9
3. P.E.!. -46.2 16.2
4. Nova Scotia 59.8 76.9
5. New Brunswick 38.8 64.9
6. Québec 98.9 99.4
7. Ontario 99.3 99.6
8. Manitoba 100.0 100.0
9. Saskatchewan 99.5 99.7
10. Alberta 100.0 100.0
11. British Columbia 99.2 99.6
12. YukonandN.W. T. 62.4 78.5
Joule ofthe road transportation end-use performed by an EV will displace 25 times more
petroleumin 1995. The corresponding rate for the year 2010 is 1:43. Note, however, that for
P.E.!. the adoption ofEV in 1995 will not represent an economy in the use ofenergy and
neither itwill displaœ petroleum. The reasons for these are: 1000/0 ofthe electricity in P.E.l
is generated by petroleum and the ICEV configuration A being more eflicient than
configuration B (lCEV and petroleum). However, by the year 2010, even in P.E.l, a switch
to EV's would lead to petroleum displacement.
• Applications of Exergy Analysis in Electric Energy System Planning
4.4.5 Energy supply for EV
82
•
•
The possible sources ofenergy to supply the eventual increase in the demand ofe1ectricity by
EV could he provided either by:
(i) Increasing gene.-ation;
(n) Improving in the system 1000 fàctor;
(ili) Improving ofthe system FPT and SPT efliciencies;
(IV) A combination ofthe previous alternatives.
-. lŒY ...r ~ n -,... -[ F_ ... , EV f--.
Fod_ r
1~ ... DH ~R - 1 '
,.
~
*', lit
~~H-,1-... ...,. ~
El ...~,. H,op
lCEl' -11IICmai"""'-...agi"" vchIckEV- c/M:trlc vchIckDlf - dINCt8poœ1walIngjùnrot:cSb - cIM:trlc bœcbocrd_~ - J.«-J1IDIfPtzlNo-air
p-ga- J.«-J1IDIfP,..,...wo-alr
• - CO'u-.::tlcm:
FJgUre 4.10 Two natural resources and end-use mode!.
Applications of Exergy Analysis in Electric Energy System Planning 83
•
•
Table 4.19 Percent ofelectric energy consumption above the present level due to by EV inthe Canadian provinces, in 1995 and 2010.
Percent ofelectric energy consumption represented
Region byEV
1995 2010
1. Canada 55.2 23.0
2. Newfoundland 9.8 4.2
3. P.E.!. 8930.7 3115.1
4. Nova Scotia 43.4 16.4
5. New Brunswick 92.0 35.1
6. Québec 31.8 13.6
7. Ontario 106.4 41.8
8. Manitoba 28.7 12.3
9. Saskatchewan 126.1 49.4
10. Alberta 150.6 55.7
Il. British Columbia 41.3 17.7
12. Yukon &. N.W.T. 76.6 31.8The eud-usc road·traDsportatiOll was CXlIlSidt:Rd to bc COIlSlllnt for the pcriod 1995-2010.
The first three alternatives are discussed now.
• Increase in the Generation Supply
The necessary increase in electricity demand due to EV is shown in Table 4.19 for Canada
and its provinces. Note that, for Canada, in the year 2010, the supply of a11 road
transportation byEV represents an inaease of23% in electric energy production with respect
to today's level. The corresponding value for 1995 is 55% due to the filet that today's EV is
not as efficient as forecasted for the year 2010.
• Applications of Exergy Analysis in Eleetric Energy System Planning 84
•
•
Table 4.20 Yearly consumption ofspace heating alternatives and electric energy conservedto replace an e1ectric baseboard.
Space Heating Alternatives Consumption Electric energy conserved toinkWhlyear replace an e1ectric baseboard
kWhlvear
1. Heat Pump Air-to-Air 9,000 6,000
2. Heat Pump Ground-to-Air 5,100 9,900
3. Direct Oil or Gas Heating 18,518 15,000
• Improvement in the load factor
The road transportation load in Canada could he supplied entirely by the 1995 power system
capability ifEV were adopted massively by the year 2010 and if the system load-factor
Canada from the existing 65.7"/0 to 80.8%. In those Canadi'311 provinces rich in hydro
resources such as Québec, Newfoundland, Manitoba and British Columbia the required
increase in the load-factor in the year 2010 will he 8.4%, 2.8%, 7.6% and 11.5%,
respectively.
Because ofthe difficulty ofensuring that the recharging ofthe batteries will occur in off-peak
hours, some economic incentives must he introduced, such as time-of-use tariffs.
• Energy and exergy conservation
FmaIly, the use ofmore ex:ergetically efficient space heating alternatives will release e1ectric
power for EV road transportation. Figure 4.10 shows an energy system used to study this
type ofDSM strategy.
Almost fifty percent ofthe forecast demand for 1995 in Québec represents e1ectric loads at
low temperature (e.g., space heating). The demand for low temperature heat represents at
• Applications of Exergy Analysis in Electric Energy System Planning 85
•
•
Table 4.21 Savings cbaracteristics 10 replace e1ectric baseboard heater by more exergeticallyefficient options in terms ofroad tran.>-portation end-use in 1995 and 2010.
Driving distance (D) Equivalent gasoline
Space Heating with a sub-compaet (EJ savings,Alternatives EV, in kmlyear in litreIyear
1995 2010 1995 2010
1. Heat Pump Air-to-Air 17,143 30,000 1,749 2,239
2. Heat Pump Ground-to-Air 28,286 49,500 2,886 3,694
3. Direct Oil or Gas Heating 42,857 75,000 3,192 4,415
least 16,000 MW in 1995 andisexpected 10 reach21,500MWbytheyear 2010. The fraction
of the use ofe1ectricity for low temperature applications in Québec is expected to remain
practically stable up to the year 2010 [Hydro-Québec, 1993].
As seen in section 4.2, space heating alternatives are much less efficient ifaccording to the
8PT than the road the transportation. A simple example could illustrate this more clearly.
Consider Figure 4.10 that shows a system with two end-uses (road transportation and space
heating) and two primaIy energy sources (oil and hydro potential). Note in Figure 4.10, that
the end-use road transportation could be supplied by either EV or ICEV and the end-use
space heating could be supplied by space heating furnace, e1ectric baseboard, air-to-air heat
pump or ground-to-air heat-pump.
Considering that the space heating end-use requirement ofa given dwe1Iing is supplied by a
e1ectric baseboard, the space heating load will be 15,000 kWhlyear, Le., 5 kW per 3,000 h per
year and the FPT efficiency ofa baseboard cao be considered as 100"/0.
• Applications of Exergy Analysis in Electric Energy System Planning 86
Table 4.20 shows the amount of electric energy conserved if electric baseboards were
replaced by more exergetically efficient space heating options. Table 4.21 presents the same
information as the previous table but in terms ofdriving distance with a EV subcompact car
in 1anIyear and equivalent gasoline savings in litre! year for the years 1995 and 2010.
The driving distance, D was calculated by applying:
(4.22)
•where E. is the electric energy displaced by adopting more exergetically efficient space
heating alternatives and <;v is the EV consumption given in Table 4.10.
The equivalent gasoline saving, shown in Table 4.14 is,
DE =--
q CJCEV
np
T)DH C(4.23)
where ~CEV is the lCEV consumption given in Table 4.10, T)DIl is the direct heater FPT
efficiency, c is a constant to transform kWh to kJ, n is the number ofhours ofutilization of
the space heating device per year and p is the end-use space heating power.
The Iast term ofequation (4.23) ooly applies for the direct space heating option. Clearly, it
is possible ta see through this example that by changing space heating from baseboard to any
the other altemative will result in sorne savings. The direct gas or oil space heating alternative
will however, save the most, either in driving, distance as weil as in equiva1ent gasoline in
litres per year.
• Applications of Exergy Analysis in Electric Energy System Planning ô7
•
•
Extending the same reasoning to the whole province, the equivalent amount ofspace heating
in Québec that would have to be converted to direct space heating in order to make e1ectric
power available to supply the whole road transportation end-use in the year 2010 in Québec
is around 27%.
4.5 Concluding Remarks
4.5.1 Limiting levels ofSPT and FPT efliciencies
The Iimiting 1eve1s ofthe main five end-uses were studied inc1uding: traction, Iighting, water
heating, cooking, space heating. The limiting 1eve1s were ca1cu1ated for aIl possible system
CODfiguratiODS for the following natural resourœs: hydro potential, nuc1ear energy, petroleum,
natura! gas and coal. These levels are benchmark Iimits which cannot be exceeded by any
alternative with the assumed technology efiiciencies. It was shown that, in generaI, it is not
possible to maximize simultaneously the First and the Second Principle efiiciencies.
4.5.2 DSM performance improvement induding cross-efTects and
eurgetic anaIysis
·Demand SideManagement Performance Improvement (PI) programs in the residential sector
must considercross-elfects as these can sharply reduce the overa1l impact ofthe program as
viewed from the perspective ofthe dwelling. Thus, although there can be a savings at the
appliance leveI, increased beating loads reduce the overa1l savings.
This impact varies significant1y among the different levels ofan energy system (appliance,
• Applications of Exergy Analysis in Electric Energy System Planning 88
•
customer, electric utility, ail or gas utility and natura! resources). For example, the electric
utility can save an important amount ofenergy, however, the oil/gas utility will see its demand
increase so that the overall savings in natural resources are not as significant as expected.
Different energy system configurations have a major influence on the amount of savings at
various levels ofthe system. A number ofextreme cases ofsuch configurations were tested
in this thesis including two kinds ofelectric generation combined with three types ofspace
heating devices. Configurations with a mixture ofenergy sources are the most susceptible ta
gain from PI measures.
The evaluation of PI measures should include exergetic as weil as energetic analysis.
Exergetic analysis is particularly important in evaluating the impact ofPI measures in the
residential sector since most ofthe measures will generate cross-effects on heat-related loads.
Since these loads are not necessarily supplied by the same source ofenergy, their exergetic
content is different. This distinction cannot be detected by the FI1'st Principle of
Thermodynamics and it bect-mes necessary to make a comparison on the basis ofthe Second
Principle.
4.5.3 Electric vehicles and exergetic analysis
Eigbt configurations ofenergy supply for EV and ICEV have been studied. SPT analysis for
1995 shows that the configurations A (petroleum and lCEV) and H (hydroelectricity and EV)
had approximately the same efliciency for 1995, that is, around 28%, However, by the year
2010, configuration H will have much bigher efliciency than configuration A
EV technology will most probably drastical1y decrease the amount ofair emissions since, even
in the case ofthe coDfiguration ofEV that utilizes thermoelectricity, its efliciency is forecast
• to he much bigherthan the traditiollll1 configuration ofpetroleum and lCEV. In other words,
• Applications of Exergy Analysis in Electric Energy System Planning 89
•
•
EV technology will provide much iower air emissions than the traditional ICEV in any ofthe
configurations ana1ysed. In addition, EV will permit much greater f1exibility in terms offue~
since power plants can use a wider range offuels than ICEV.
The necessary increase in the electric energy to supply the EV's could be met by:
(i) The improvement of the system load factor. Since car batteries take tirne to be
recharged, this type ofload is a good candidate for tariffstrategies like tirne-of-use
or type-of-use'. It was shown that an improvement in the Canadian power system load
factor from the existing 65.7% to approximately 80.8%, by the year 2010, is enough
to supply the tota1ity ofthe road transportation EV load.
(ü) DSM strategies. It was demonstrated through an example that the changing ofthe
space heating devices to more SPT efficient ones will contn"bute significati....e1y to
provide energy for the adoption ofe1ectric vehicles.
(iü) Increasing in power generation. A 23% increase in e1ectric generation will suffice to
supply the whole Canadian road transportation f1eet by the year 2010.
1 These type oftariffs will he discusscd in Chapter 6.
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems
Chapter 5.
Economie and Exergetic Optimization Analysis
of Space Heating Systems
5.1 Introduction
•
Cbapter 3 of this thesis presented a general energetic and exergetic mode! of an e!ectric
energy system, the principles ofoptimizarion oftbis mode\, as well as an illustrative example
of system planning with multiple optimjzarion goals. The present chapter applies these
optimization principles in greater detail to a more realistic space-heating problem. This
problem is iirst analysed from the Fust and Second Principle of Thermodynamics by
minjmjzing the total energetic and exergetic use at the natura1 resources leve!. The minimum
energy and exergy solutions are then compared with the minimum cost designs. Fmal1y,
diffdent types ofcost incentives are studied with the intent offorcing the minimum cost and
90
• Economie and Exergetie Optimization Analysis of Space Heating Systems
minimum exergy solutions to coincide.
91
The importance ofoptimization1 is its ability to systematically find feasible designs among
the infinite choices that satisfy a given set ofequaIity and inequaIity constraints and at the
same time, minimize a predetermined objective function. A generaI objective function can be
defined which assigns different weights to each natura1 resource and energy conversion
device so that,
(5.1)
•
•
where R is the set ofnaturaI resources and Disa set ofenergy conversion devices. The last
term ofequation 5.1 descnbes the cosf to the customers. Other, even more generaI objective
functions can be formulated by assigning a weighting factor to each energy and exergy state.
Such formulations permit the planner to assign different values to each individual resource,
including the possibility ofdifferentiating between energy and exergy. As an example, an
energy policy may assign a higher value to oil, relatively to other resources, becanse ofits
scarcity, greater environmental impact and its dependence on foreign imports.
As discussed in chapter 3 and demonstrated in severaI examples in chapter 4, in many
situations the minimiZlltion ofone ofthe above variables does not necessarily correspond to
the minimization ofanother. Thus, a compromise must be made by the planner to ensure that
an acceptable balance among all variables is reached.
1 In this thesis, all the optimiZllrion problems are solved with the Matlab
OptimiZlltion Toolbox [Grace, 1992].
2 Cost can assume different fonDS, such as, cost to the customers, to the utilities orto society.
• Economic and Exergetic Optimization Analysis of Space Heating Systems 92
•
•
The relevance of such optimization studies resides in allowing the planner to better
understand the system behaviour under different conditions. Although the solutions provided
by the optimization algorithms are most Iikely not to be found in the real world by reasons
difficult to mode! such as human preferences, optimal solutions do outline the system
behaviour under ideal conditions. The solutions provided by such optinùzation studies are like
landmarks, estabüshing limits for planning plhl'0ses under different objective functions.
5.2 Space Heating Mode!
Section 4.1 presented an energetic and exergetic analysis of a space heating system.
However, this analysis was carried out without optimizing the system variables. The present
section, therefore, analyses this system by optimizing energy and exergy variables combined
with economic considerations.
The application of optïmization techniques to the planning of heat re!ated end-uses
(particularly space-heating) is important in exergetic analysis for the following reasons:
(i) There exist many space heating system alternatives because ofthe wide spectrum of
possible energy sources and energy conversion devices and they should be assessed;
(ù) Heat re!ated loads usually have a wide difference between the FPT and SPT
efiiciencies;
(m) To make an intelligent choice among the many alternatives, a systematic approach is
required. Such a choice may favour a design alternative which does not necessarily
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems
<, ,--. <1r--::....-----------~ DB
<F < pp_tk BB
<J7l HP_""
H <~I PPjty t-J HP;<4
Figure. 5.1 Space beating model.
bave the bigbest FPT efliciency but wbicb bas a bigb SPT efliciency;
93
(iv) SimiIarIy, the minimnm cost design witb the existing electricity tariffs and fuel priees
sbould he compared with other designs wbicb maximize FIl"St and Second Principle
efliciencies.
•
Figure 5.1 presents a model witb only one end-use, namely the overall space beating
requirements, (Q) and two naturaI resources, bydro resources (II) and fossi! fuel (F). The
fossil fuel resources feed bath the direct beating energy conversion (DR) equipment and the
thermoelectric power plants (pP_th), while the bydro resources (II) are used for electric
powergeneration tbrougb thebydro power plants (pP_by). In tbis mode\, four space beating
alternatives were considered:
(i) Direct fossi! fuel (DR);
(u) Eectric baseboard (BB);
• Economie and Exergetie Optimization Analysis of Space Heating Systems
(iii) Electric air-to-air heat-pump (HP_aa);
(iv) Electric ground-to-air heat-pump (HP...sa).
94
To perform the optimization ofthe space heating mode! shown in Figure 5.1 it is necessary
to build the set ofequations that charaeterize this problem, that is,
•
(5.2)
(5.3)
(5.4)
(5.5)
The equivalent A matrix and b veetor are given by,
1 1 1 1 0 0 0 0
1 0 0 0 0 0 0 -11')DH
A= 01 1 1 -1 0 0 0
(5.6)-1')BB 1')HP-... 1')HP-gc
0 0 0 01 0-- 1')PP-th 1')pp.hy
1')77
•
• Economie and Exergetie Optimization Analysis of Space Heating Systems
b=[Q 0 0 0]'
where the symbol " . " , in equation 5.7, denotes the transpose ofthe vector.
5.3 Economie Analysis of Space Heating
95
(5.7)
•
•
Table 5.1 presents the necessary input economic and other relevant data for the analysis of
space heating options. The foUowing comments apply to each row ofthe table:
(1) The capital cost for the alternative e1ectric baseboard is the cheapest. The alternative
ground-to-air heat pump bas the highest capital cost and it represents more than 34
rimes the corresponding cost ofthe baseboard alternative. It must also be noted that
the capital cost figures shown for the heat-pumps correspond to 75% ofthe aetual
cost ofthe device as the remaining 25% is associated with the cooling mode ofthe
heat-pump;
(2) The Iife expectancy ofe1ectric baseboards is assumed to he the longest since the other
options have more moving parts and are more like1y to fiIil;
(3) The opportunity cost rate is the interest rate, on a yearly basis, that would be earned
above inflation ifthe capital spent had been invested in the market;
(4) The efficiency or coefficient-of-performance varies significantly, ranging from 81%
( for direct space heating ) to 300"/0 ( for heat-pump ground-to-air ). Note that the
e1ectric baseboard option is assumed to have an efliciency as measured by the FIISt
Principle of 100%, since it is assumed that ail e1ectric energy is converted to low
temperature heat;
• Economic and Exergetic Optimization Analysis of Space Heating Systems 96
(5) The priee offuel to the customers is around 177% of the fuel priee to the thermal
power-plants. In t1ùs study, it is assumed to be the same for ail three regions
considered;
(6) The energy escalarion rate per year is the increase above inflation ofthe fuel costs and
electricity tariffs;
(7) Direct spaee heating and the ground-to-air heat-pump alternative have the Iùghest
maintenanee rates ( percentage ofthe initial capital cost per year );
(8) The number ofhours ofoperation was assumed to be constant at 3,000 hours per year
for ail spaee heating alternatives considered;
Table 5.1 Relevant economic data for di1ferent spaee heating alternatives.
t Source: [Stalistics Canada, 1992]• CocfliCtCllt ofpcrfonD8llCC
Space Healing AltemaliveE1cctric Hcat.pump Heat'plDDp Di=t space heating
BaseboanI air·to-air ~.to-air
1. Capital cost 49 8S7 1,713 117(S/kW ofend·use)'
2. Lifc cxpcctancy (years) 20 15 15 15
3. Opportunity cost rate4.0
~/o/year.)
4. Eflicicncy ~/o) 100 170' 300' 81
5. Oilpricc4.8 SIG] (17.4 $IMWh) 8.5 SIG] (30.7 $IMWh)
(for thermal power-plants) (for customas)
6. Encrgy cscaIation rate2.0
~/olyear)
7. MainttTumœ1.0 1.5 2.0 2.0
~/o ofcapital cost1year)
8. Operation (hours 1year) 3.000
9. E1cctric rate,Québec, 6.52Ontario. 9.56(c/kWh)t New York. 16.56 ..
: Canad·anS
•
• Economie and Exergetie Optimization Analysis of Space Heating Systems 97
•
(9) Finally, for comparison purposes, clifferent e1ectric rates were consideree! for three
geographical locations: Québec, Ontario and New York. Because of the
preponderance ofhydro e1ectricity in Québec, the e1ectric rates in Ontario and New
York are respectively around 47"/0 and 154% higher.
Note that the parameters in Table 5.1 are representative and can be alteree! to simu1ate other
conditions.
Before optimizing the various design alternatives, it is useful to examine the Iife costs ofthe
space-heating options at the customer level. The term Iife cost represents the cost to the
customer for the expected Iife ofthe space heating device including, capital, maintenance and
operational costs. The capital cost includes the initial investment and the opportunity cost.
The operational costs invo1ve, both the maintenance and the energy costs (based on fuel rates
or e1ectric tariffs).
The Iife cost~ in today's doUars ofa given end use device i producing yearly useful energy,
t; , in kWhlyr, is given by,
(5.8)
•where IC; is the initial capital cost in $/kW ofend-use energy, q is the number ofhours of
operation peryear,1ti is the load filetor ofthe device elCpiessed as some dimensioDless fraction
ofone, p is the opportunity cost rate as a fraction ofthe initial capital, Ill; is the maintenance
cost per year as a fraction ofthe initial capital cost, fi is the e1ectric tariffOf fuel rate in
• Economie and Exergetie Optimization Analysis of Space Heating Systems 98
•
$/kWh, ~ is the ecpected number ofyears in the Iife ofthe device and 5 is the expected energy
cost escalation rate as a fraction ofone. Finally Tli is the FPT efficiency ofthe device.
Equation 5.8 is important becansc it discriminates among the various components ofthe cost
ofa device in terms ofits economic variables and energy consumption. Equation 5.8 is aIso
needed to define the cost components ofthe optimization criterion f given by equation 5.1.
Note that the cost ofa device is current1y a1ways rationalized in terms ofits energy and power
consumption. In other words, exergy bas been virtually ignored in economic analysis.
By dividing the life cost, Lei' by the life expectancy in years, ~ and by the amount ofenergy
that the device will consume per year, ~ , one obtains the average cost ofthe device over its
life time, in $/kWh, ac; , where,
(5.9)
Therefore, the cost term appearing in the objective fimctions defined by equation 5.1 is ofthe
forro,
(5.10)
•where Ci is in $/yr. The results ofan ortïrni7lrtion are usually summarized through the average
cost ofail end-use devices, narneIy,
• Economie and Exergetie Optimization Analysis of Space Heating Systems
Lac, e,ac = .,:D===__
Le,D
99
(5.11)
Note that the variable, 1IG, in equation 5.9 can be divided into two components, capital cost,
ie; and operation/maintenance cost, olD; ,
•where,
and
oc, = ic, + am,
l,
le 7, L(l+sY__, Cm 1) + .......f!.:·.:,.!__n lÇ' 1 1
1 ~I 1'),ami = ..L..:...::-=- ----::.-_LI,
(5.12)
(5.13)
(5.14)
•Note that the 1irst term in the equatïon 5.14 represents the maintenance cost and the Iast term
represents the energy costs.
Table 5.2 shows the average life costs for several alternatives consideree! for the space
heating system ofFigure 5.1. Note that, striet1yfrom the economic point ofview, in Table 5.2
• Economie and Exergetie Optimization Analysis of Space Heating Systems 100
Table 5.2 Average life costs to customers for different space heating alternatives.
the direct space heating alternative is the most economic one for the customer in terms of
life costs either for Québec. Ontario or New Yorlc. The alternative electric baseboard is the
most expensive for any ofthe three regions studied except in Québec. This occurs in spite of
the initial cost ofthis alternative being around 42% cheaper!han the direct space heating
option. Finally. the life cost of the heat-pumps are 2 to 32% cheaper in New York and
Ontario compared to the electric baseboard option, but 1 to 28% more expensive!han the
baseboardoption in Québec.
'CanadienS
Space Heating AItemalivcDirect space Eloeme Heat-pump Heat-pump
heating Baseboard air-to-air ground-to-air
New5.00 20.72 15.31 14.49York
1. Average lifc c:osts'(clkWh ofend-use) Ontario 5.00 12.04 10.47 11.74
Québec 5.00 8.27 8.37 10.55
New100 414 306 290York
2. Average lifc costs ("/0)1(Direct space heating =100) Ontario 100 241 209 235
n. .•~ 100 165 167 211..t Source: (Stal1SliCS Canada, 1992]
•
Tables 5.3, 5.4 and 5.s present the average life cost separated into energy, maintenance and
capital costs ofthe different space heating alternatives in New York, Ontario and Québec,
respective1y.
Note in Tables 5.3, 5.4 and 5.5 !bat:
•(i) The energy cost for direct space heating represents 89"10 ofthe life costs. For the
e1ectric baseboard the energy cost represents more !han 97% of the life costs
regardless ofwhere it is located, i.e., New York, Ontario or Québec. For the heat-
•
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Economie and Exergetie Optimization Analysis of Space Heating Systems 101
Table 5.3 Energy, maintenance and capital average costs at the customer level fordifferent space heating options for Ontario.
Direct Electric Heat-pump Heat-pumpSpacc Heating Alternative Spacc Bascboard air-to-air ground-to-air
Heatinl!
1. Encrgy costs, clkWh 4.45 11.84 6.61 3.74
("10) (89.0) (98.3) (63.1) (31.9)
2. Maintenance costs, clkWh 0.08 0.02 0.43 1.14
("10) (1.6) (0.2) (4.1) (9.7)
3. Capital costs, clkWh 0.47 0.18 3.43 6.86
("10) (9.4) (1.5) (32.8) (58.4)
4. Total, clkWh 5.00 12.04 10.47 11.74
("10) (l00.0) (l00.0) noo.O) noo.O)
Table 5.4 Energy, maintenance and capital costs at the customer level for different spaceheating options for New York.
Spacc Heating Altcmativc Direct Spacc Elcctric Heat-pump Heat-pumpHeatinl! Bascboard air·to-air l!rOUIId·to-air
1. Encrgy costs, clkWh 4.45 20.52 11.45 6.49
("10) (89.0) (99.0) (74.8) (44.8)
2. Majntc:nmœ costs, clkWh 0.08 0.02 0.43 1.14
("10) (1.6) (0.1) (2.8) (7.9)
3. Capital costs, clkWh 0.47 0.18 3.43 6.86
("10) (9.4) (0.9) (22.4) (47.3)
4. Total, clkWh 5.00 20.72 15.31 14.49
(%) noo.O) noo.O) noo.O) noo.O)
•
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems 102
pump spaœ heating alternatives the energy costs represent around 24 to 75% oflife
costs ofthe device;
(u) The maintenance costs represent between Jess than 1% ( e1ectric baseboard) to around
10% ( heat-pump ground-to-air in Québec) of the Iife cost of the space heating
alternative;
(Iii) The capital cost ofthe direct space heating alternative is 9.4 % ofthe Iife-cost ofthis
alternative. However for the heat-pump space-heating alternatives the capital costs
represent always a significant proportion oftheir Iife cost, ranging from 22.4% to
65.0"/0. On the other band, capital COsts represent only a smalI fraction, Jess than
2.2%, ofthe Iife cost ofthe e1ectric baseboard alternative.
Table 5.5 Energy, maintenance and capital COsts at the customer Jevel for different spaceheating options for Québec.
Direct Eicctric Hcat-pump Hcat-pumpSpllCC Hcating Alternative SpllCC Bascboard air-to-air ground-to-air
Hcatinll
1. Energy costs, clkWh 4.45 8.07 4.51 2.55
(%) (89.0) (97.6) (53.9) (24.2)
2. Maintenance costs, clkWh 0.08 0.02 0.43 1.14
(%) (1.6) (0.2) (5.1) (10.8)
3. Capital costs, clkWh 0.47 0.18 3.43 6.86
(%) (9.4) (2.2) (41.0) (65.0)
4. Total, clkWh 5.00 8.27 8.37 10.55
(%) (l00.0) (l00.0) (100.0) (100.0)
•
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems 103
5.4 Optimization with Mixed Objectives
The space heating system can be optirnized from the points-of-view of cost, energy and
exergy subject to the space heating mode! equations 5.2 to S.S. From the above discussion,
the minimum cost solution is clearly the option with 100% direct space heating. Table 5.6
summarizes these three optimum solutions according to the optimization criterion chosen
assuming that there are no limit on the amount ofspace heat provided by each alternative.
Later in this section, another case is studied with limits on the various heating options.
Thus, the "best design" heating alternative depends on whether cost or energy/exergy
considerations are preeminent. For example, as seen in section 4.1, if the space heating
altematives e!ectric baseboard and direct space heating are comparee!, then the first option bas
the highest FPT efiiciency but the direct space heating bas the highest SPT efiiciency.
In the more realistic case where the outputs ofthe possible space heating conversion devices
are limited, as is the case discussed later on in this section, the best designs may involve
combinations ofan heating devices. In such cases, an designs where onlyenergy and exergy
are considered in the objective function (zero weight for cost), the ground-to-air heat-pump
is normally saturated l:>ecanse from bath the FIrSt and Second Principles, this alternative is
Table 5.6 Best space heating design as a function ofthe minimizarion criterion, unconstrainedcase.
MinimizationBest Design ( Unconstrained )Criterion
1. Cost 100"/0 direct heating
2. Energy 100"/0 hydre power plants + 100% ground-to-air heat-pumps
3. 100"/0 hvdro llOwer Dlants + 100"/0 2I'Ound-to-air heat-DumDs
•
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems 104
Table 5.7 Optimization criterion and objective function considered for the space heatingmodel ana\ysis.
1Optimization Criteria
1Objective Function
1
1. Energy ea
2. Exergy xR
3. Cost Co
4. Energy and exergy ea+xR
5. Energy and cost w\ ea +Co
6. Exergy and cost W2XR +Co
7. Energy, exergy and cost w\ (ea +w2xJJ + Co
8. Cost with subsidies Co(6)
more efficient than ail others. Mer saturating ground-to-air heat pumps, the other
alternatives will he selected in accordance with the objective function and the constraints
chosen. In such cases, the minimum energy and exergy designs are norma1ly not necessarily
equal.
The combination ofenergy and exergy together with costs as optimiZlltion criterion gives
further insight when comparing space heating alternatives. The mixed optimiZlltion criteria
considered for the space heating mode! ana\ysis are \isted in Table 5.7. Note that ea and Xst
represent respectively the amount ofeneIBY and exergy consumed at the resource IeveI while
Co is the cost to the customer ofthe end-use energy conversion devices. In Table 5.7, the
variable r represents the fuel or e!ectric rate in clkWh charged to the customers. The explicit
dependence ofthe cost Co on r is described in equation 5.9. Note, as weIl, that optimization
• Economie and Exergetie Optimization Analysis of Space Heating Systems 105
criteria one and two in Table 5.7 are equivalent to maximizing the FII'St and the Second
Principle ofThermodynamics efliciencies. Criterion four in Table 5.7 minimizes with equal
weight bath the exergy, "R, and the energy, ea , consumed at the resource leve1. Optimization
criteria four, five, six and seven combine with different weights energy and exergy at the
resource level together with the cost to the customers. The optimization criterion eight takes
into consideration the minimization ofthe subsidized cost to the customers, <:0(6), where 6
is the parameter representing the given subsidy, ofwhich three have been consideree!, fuel
rates, initial investment and opportunity costs.
•The space heating model was again optimized for the criteria shown in Table 5.7 but, this
time, considering the constraints. These were chosen as typicallevels in a fossi1-fuel-based
utility:
Table 5.8 Optimum energy states for diffèrent optimization criteria.
t UpperbouDd Iimit rcachcd.Q =spccificd OVtnll spacc-hcating IeqUIICIIlCIIts
Optimi7JItion Criteria Min Min Min Min<:0 "R ea (ea + "R>
StatesEnd-use energy
(%ofQ=)
Ct (end-usedi=thcating) 100.0 95.0 66.3 85.0
e:(end-use cleclric bascboard) 0.0 0.0 18.7 0.0
e, (end-usehcat-pump air-to-air) 0.0 0.0 lOt 10.Ot
c. (end-use hcat-pump ground-air) 0.0 5.0t 5.0t 5.0t
e, (cleclric load) 0.0 1.7 26.2 7.6
Ca (fuel for thcrmaI power-plant) 0.0 0.0 0.0 0.0
c, (hydro potential resoun:es) 0.0 1.9 30.0t 8.6
Ca (fuel for di=t spacc hcating) 123.5 117.3 81.9 104.9
ea(tolal encrgy COIISumptiOll at lIlItlIral :œsowcc Icvcl) 123.5 119.2 111.9 113.6. . . .•
• Economie and Exergetie Optimization Analysis of Space Heating Systems 106
(i) The maximum values ofthe air-to-air heat-pump, ~. and ground-to-air heat-pump,
e., were 5% and 1(lOlo ofthe value ofthe overall specified space heating requirement,
Q, respectively;
(ù) The hydro potential state, e" was limited to 30% ofQ;
(iii) The remaining states were not constrained;
Tables 5.8 and 5.9 shows the simulated values ofthe energy and exergy states ofthe space
heating problem for some ofthe optimization criteria listed in Table 5.7. Analysing Table 5.8
and 5.9 note that,
•(i) In contrast to the unconstrained case ( see Table 5.6 ), in the constrained case the
optimum solutions for a minimum "R or minimum l:tt or even minimum (XR+ eJ are
Table 5.9 Optimum exergy states for diftèrent optimization criteria.
TUpper houDd limit reachcd.
Optimi7))tion Criteria Min Min Min Minc,., XD e" (e" + xD)
States End-use exergy(%ofQ:J
Xl (end-use direct hcating) 2.7 2.6 1.8 2.3
X: (end-use c1cetric bascboard) 0.0 0.0 O.sT 0.0
Je, (end-use hcat-pump air-~) 0.0 0.0 0.3T 0.3T
X. (end-use hcat-pump ground-air) 0.0 O.lT O.l! O.lT
les (clcetric load) 0.0 1.6 24.9 7.2
Xs (fuel for thcrmaI power-plant) 0.0 0.0 0.0 0.0
Je, (hydro potcnIiaI rcsoun:cs) 0.0 1.8 28.st 8.2
"s (fuel for direct spacc hcating) 49.4 46.9 32.8 42.0
1~(tota1~ tion at natural resourcc 1evcI) 4:1.4 48.7 61.3 50.2.•Q- spccificd overall space-hcating reqmremcnts.•
•
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems 107
ail distinct;
(ù) The upper bound Iimit ofstate e. ( spaœ heating from ground-to-air heat-pump ) was
reached for ail three optimization criteria This is due to the filet, as seen in Chapter
4, that the ground-to-air heat-pump is more efficient from either the F1I'St or Second
Principle perspectives;
(ùi) The state ~ (heating from electric baseboard) is different from zero ooly when the
optimization aiterion is the minimizatiQn ofthe energetic resources, ea. at the naturaI
resource level In this case, the upper bound Iimit ofthe hydro-potential, e" is reached
as weil;
(iv) The use ofthermaI power plants is never part ofthe solution for ail the criteria tested,
that is, the state e"is always zero. Ifhydro-resources are not available, thermal power
plants will be present to supply the heat-pump requirements ofthe optimum solution;
(v) The minimum cost solution requires ooly direct heating;
(VI) The first four e:.œgy states have re1ativeIy low values, due to the filet that the exergy
in low heat temperature sources is extIemely 10W;
(vii) The energy consumed at the resource Ievel, ea. is a maximum when minimizing cost.
The minimization ofthe end-use cost, Co. leads to the maximum energy consumption
at the naturaI resource, «la. However, the minimization «la leads to maximum exergy
. consumption. However the maximum exergy consumption occurs when minimjzing
«la. This bebaviour is very interesting since it implies that the minimjzarion ofthe cost,
energetic and exergetic resources are conf1icting goals;
Table S.10 presents the average Iife cost te the customer, the F1I'St and Second Principle
eftïciencies and the description ofthe states for five diflèlent optimizariQn criteria for the
regions ofNew York, Ontario and Québec. An the costs' figures shown in Table S.10 are
• Economie and Exergetie Optimization Analysis of Space Heating Systems
Table 5.10 Cost and efficiencies ofthe space heating for different optimum criteria.
lOS
•
•
Optimization Region Cost TI € Description orthe statesCriterion (cJkWh) ("10) ("10)
1. Min "" or New 14.49Mine,. or York Ail the space heating front heal.pwnpMin (x.+e,J 262.2 7.54
(Uneonstrained Ontario 11.74 ground-to-air and a11 e1ectrie power
solution)supplied by bydro power plants.
Québec 10.55
New 5.00
2. Mine:" York(Constrained 81.0 5.53 Ail the space heating front di=! oil or
solution) Ontario 5.00 gasheating
Québec 5.00
New 5.48 Heat-pump ground-to-air saturated power
3. Min""York supplied by hydro power plants; the
(Constrained 83.9 5.60 remaining space heating requirements
solution)Ontario 5.34 supplied by di=! fossil fuel space
Québec 5.28heating.
New 9.44 Heat.pwnp ground·to-air and air·to-airYOIk saturBted to the limil, e1ectric bBschoard
4. Mine,. 89.4 4.46 utiJizc up to the limil ofthe hydro power(Constrained Ontario 7.20 plants, the mnBining space heatingsolution) requitenx:nls suppliedby di=!fossil fuel
Québec 6.23 space heating.
New 6.51 Heat-pwnp ground-to-air and air·to-air5. Min (e,.o!?cJ YOIk SBlIIt'8It:d power supplied by hydro power
(Constrained Ontario 5.89 88.1 5.44 plants; the mnBining space heatingsolution) requitenx:nls supplied by di=! fossil fuel
Québec 5.62 space heating.
given in cents ofCanadian doUars per kWh. These costs were calculated over the Iife perlod
ofeach individual device, considering the economic inputs shown in Table 5.1 and equation
5.9. Several points should be stressed about the results shown in Table 5.10. For each
criterion the corresponding comments apply:
(1) For the unconstrained cases, shown in item one, ail three criteria ha~e the same
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems 109
solution, that is, ail the space hl.:ating requirements are met by ground-to-air heat
pump. The costsforthis case vary from 14.49 to 10.55 cJkWh, corresponding to the
costs of the ground-to-air heat-pump shown in Table 5.2. Note, as weil, that the
variation in the cost is not in the same proportion as the e1ectricity rates in the three
regions studied, since the capital cost for a heat-pump is a major portion ofits average
Iife cost as emphasizerl in Tables 5.3, 5.4 and S.S. Both the First and Second Principle
system efficiencies in this case are the highest among ail the cases tested with values
of262.2 and 7.54 %, respectively. Clearly the unconstrained cases are not normally
rea1izable and are presented only for references purposes. The importance to have
such lderence resides in aIIowing the planner to know the upper bound limits in the
efficiencies, as well as, to compare different end-uses ofenergy from the points of
view ofthe Fust and the Second Principle ofThermodynamics, as it will be shown,
Iater one in the section 5.3;
(2)
(3)
The minimum cost solution requires only direct space heating ( item 2 ) and yields an
aveœge Iife cost of5.DO cents per kWh. Since the oil cost for space heating purposes
was considered te be constant for the regions studied and the minimum cost solution
utilizes only direct heating then the costs for the three regions for this optimum
criterion are constant;
Minimization of the exergy consumption at the resource leveI, is equivalent to
DIaYimization ofthe Second Principle efficiency. Item three shows that e.....x, for the
constrained case, is achieved by saturation with ground-to-air heat-pumps with their
energy supplied by hydroeIectric power generation. The remaining space heating
requirements are supplied by direct space heating devices. Note that the cost for this
aItemative is net signilicant1y different from the minimum cost solution. For any ofthe
three regions, the cost is within 10"/0 ofthe minimum cost solution. The reason for
this, as seen in Table 5.8, is that the minimum "Rand minimum Co solutions difièr only
by the amount ofground-to-air heat-pump which is limited to only 5% ofthe space
•
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems 110
t5 PO
~
s.s~-_':'---~- .... - JIi...-r :- 88
y 13,:,i- 88.... ' .....
.::>
~ 5....
, ~~.. ' , , -, ,
, , , :-84~~~ ' ...' , EfIIcs.ncy
4.S
V: ~2-- "
11 : Il, 4 , '
1 1 80
min cl> min %,. mln(e,. + %.J min e.Opllmlullon ctItotl.
,
FJgl1re 5.2 FII'5t, '1'), and Second, e, Principle efficiencies for different optimization criterion.
heating requirements. Later on, in this section, further discussion is given to design
programs and incentives which induce the maximum e and minimum cost solutions
to coincide;
(4) Minimization of the energy consumption at the resource leveI, is equivalent to
maximization ofthe First Principle efficiency, '1'). Item four shows that '1').... , for the
constrained case, is achieved by saturation with the ground-to-air and air-to-air heat
pumps, some direct-heating as weil as some e1ectric baseboard heaters. The latter are
increased until the hydroeIectric resource 1imit is reached, however no thennoeiectric
generation is required by the optimum solution. The costs, in this case, increase
substantially when compared with the minimum cost solution, (from around 24% to
880/0), depending on the region. The reason ofthis substantial increase is due to the
increased use ofair-to-air heat-pumps and e1ectric baseboards;
(5) Fmally the criterion combining elCergy and energy consumption at the resource level
(Item 5) yields a mixture of the solution reached by items three and four. This
• Economie and Exergetie Optimization Analysis of Space Heating Systems III
-: ;- '
· .. ........ .. . ..· . .· .
. ..- .· . .· .Region
New Yorle8 : :· .
10 : : ..· .
Q.S : :.· .· .
Ontario., .8.S : ":" _._. Ou"bec .: :.... . :
~ 8 : :."'. ~__J.~ : ~
~7.S : .; .; : :- :
'i 7 ~ ~ ~ ~ ~ ;,••~o : : : . .."",._.
/l.S ,......................................... .. ,-. ,· . . ..-. .6 : :~.~ : '~~~~· . . ..~ -,-- ...--..--_.:-,-': :
5_: ~.~..~..~.~..~.~..~..~'~..~.~..~..~.~..~~'\~.ç;;;-~.~::.~-~.-~:~.~-~.-:.~..~.~.:.:..~.~..~.~..~.~"~"~:'~"~'~"~"~'~"~'d'":mln:r" min {l'" + :r~
Opt/maation ~riamin e~
•Figure 5.3 Cost of the space heating for different optirnization criteria, for New YorIc,Ontario and Québec.
optimum solution imposes that all heat-pumps reach their Iimits, with the rernaining
space heating requiIements being provided by direct fossi! fuel heaters. Again, all the
e1ectric power is provided by hydro power generation. Note that the costs and the
efliciencies have intermediate values compared with items three and four as would
be expected.
•
Figures 5.2 and 5.3 SI'l1!IDI!lÏz.etheresults ofTable 5.10 in graphical form. for the constrained
cases. Figure 5.2 shows the FU'St and Second Principle efliciencies. Note that the variations
in 'Il are 8.4 percentage points, represenring a variation of9.8% over the average value ofthe
First Principle efliciency. The equivalent variation for e is 1.14 percentage points,
represenring a variation of21.7 % over the average value ofthe Second Principle efliciency.
The percent variation ofthe Second Principle efliciency is therefore much larger than the
variation in the FU'St Principle efliciency.
Figure 5.3 presents the cost ofspace heating for the oprimization criteria listed in Table 5.10
•
•
•
Economie and Exergetie Optimization Analysis of Space Heating Systems 112
in New York, Ontario and Québec. Note that the cost difference between the minimum cost
and the minimum exergy solution is less than halfa cent per kWh, or around [10, 7, 6] % of
the average cost for the four alternatives considered. Note, as we11, that the minimum energy
solution yields, for ail three regions studied, much lùgiler costs ( around [79, 37, 19] % for
New York, Ontario and Québec respectively) than the minimum exergy solution. T1ùs is an
interesting filet indicating since, for this example, that the maximization ofthe resources from
the Ftrst Principle not only is more cost1y but provides the worst Second Principle efficiency,
see Figure 5.2.
nus, the use ofthe Ftrst Principle ofThermodynamics as the sole optimization criterion does
not lead to a rational use ofresources from the perspective ofthe Second Principle wlùch is
viewed as a rational method ofenergy planning but results in the most expensive solution.
The minimization ofboth energy and exergy consumption at the resource level provides an
intermediate cost as weil as a compromise between FIrst and Second Principle efficiencies.
It is important to analyse such intermediate solutions since extreme cases ofmaximum E or
minimum cost may not be achievable in practice.
The question that natural1y follows is how to realise the above-mentioned strategies specially
the one that maximizes the natura1 resources as measured by the exergetic content. The
foUowing subsection discusses alternatives as to how to implement the maYimization of
exergetic efficiency in the space heating model.
The optimization ofthe space heating problem is now considered with weights in the energy
and exergy consumption at the resources level combined with the overall cost at the eustomer
level. This ana1ysis is done te determine the relative weights that must he assigned to cost and
to energy/exergy resources in order to achieve a desired solution (such as the minimum
exergy solution). This weight then indieates te the pIanner how fàr the minimum cost solution
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Economie and Exergetie Optimization Analysis of Space Heating Systems 113
Table 5.11 Minimum energy/ex.ergy weights (cIkWh) in the linear programming objective toforce the solution to be equal to the minimum "R solution.
Objective Function Dcsircd Québec Ontario NewSolution York
1. Eucrgy and cast (w e"+ct, ) min "0. na. 9.8 18.4
2. Excrgy and cast (w "0. +ct, ) minxa 422 51.3 72.2
3. En andcast w. (e.. + x. )+ ..... min x. 5.7 6.9 9.7na. = not achicvable
is from the desired solution. Some results ofsuch optimiZlltion are presented in Table 5.11.
To interpret the results ofTable 5.11, consider, for example, in row l, that, in New York,
it is necessary to weigh the total energy resources, Ca , by 18.4 c1kWh so that the minimum
solution for the objective fimction w Ca + Co will be equal to the desired solution (m this case
assumed to be the minimum "R solution). This value ofw is very high compared with the
average cost ofthe minimum "R whicb, as shown in Table 5.10, is 5.48 c1kWh. The results
ofall three cases shown in Table 5.11, imply that the minimum cost solution is relatively fàr
from the desired minimum ex.ergy solution and that to achieve the latter one must tax either
the resources, Ca or "R , or subsidize the coS!, Co-
The nex.t section discusses more practica1 ways to induce users to consume energy in patterns
which equal or approximate a given desired solution.
s.s Implementation ofDesired Optimum Solutions
In this thesis, the argument is made that the most ratioDa! way to use naturaI resources is to
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Economie and Exergetie Optimization Analysis of Space Heating Systems 114
maximize the overa1l Second Principle efficiency. This argument is made on the basis that
exergy is the appropriate measure ofthe potentiaI usefuIness ofnatura! resources since exergy
constitutes the ability ofenergy to he converted into any other form. Furthermore, as shown
in the previous sections, maximizing the First Principle efficiency alone is not sufficient, in
general, to achieve the best use ofnatural resources.
One way to implement this planning philosophy for system planners is to conceive economie
measures that would make the most efficient solution according to the Second Principle of
Thermodynamics the most economically attractive. Economie measures are strategies that
serve to stimulate society to adopt technologies and energy use patterns compatible with a
given philosophy. Another possible strategy is to increase the public consciousness about the
importance ofexergetie considerations in the planning ofthe utilization ofnatural resources.
The Iatter approach, although no less important, is however not easy to quantifY or analyse
and is not treated any further in this thesis.
In this subsection, a number ofeconomie measures are considered to induce users to conform
to the requirements ofthe minimum exergy solution, assuming that users tend to consume
energy in a manner consistent with minimum cost. The economie measures considered in this
thesis are:
(i) Subsidy in the initial capital cost investment, le;
Cn) Subsidy in the opportunity cost rate, p, at the end-use device level;
Cili) Subsidy ofthe fuel and the electricity tariffs, r;
The subsidies described by the items above modifY the average cost ofthe device over its Iife
time, given by equation 5.9 to ac;", where,
• Economie and Exergetie Optimization Analysis of Space Heating Systems 115
(5.15)[
4(ri - /u-,) :E (1 +sy
(ICI-MC,) (1 + (p-t1p)l' + _IC_I m, /1 + .:...jo..:..1__
• ni !h ni !h Tlic, = -'---.:...-.:...----------:-.....:..-------'-----'/1
The tenns AIC" AI'; and Arj represent the subsidies level in the capital cost, the opportunity
cost rate and in the energy and fuel/rate to the eustomers respectively. Note, in equation 5.15,
that the maintenance costs are not affected by the capital cast subsidy. Note, as weil, that a
given subsidy level in the capital cost will also change the opportunity cost, since the later is
a function ofthe initial capital.
•As noticed in Table 5.8 the difference between the minimum cast and maximum e solutions
in theend-use states (~, i =1 to 4) is the replacement ofsome direct heating by ground-to
air heat-pumps. Therefore, the subsidies considered in this example are applied only to the
ground-to-air heat pump so as to encourage customers to switch from direct heating. An
alternative approach wouId have been to talC direct heating however this was not considered
in this analysis. The minimum subsidy to conform with the minimum exergy is found by
Table 5.12 Minimum % subsidies for varying oPPOrtunity cost rates in the initial capital ofthe heat-pump ground-to-air to induce the minimum exergy and minimum cost solutions tohe identical in Québec.
Opportunity cost rate subsidy0 1 2 3 4("10 pcrycar)
1. Initial Capital Cast Subsidy ("10) 81 78 74 70 66
2. Initial cost average lifc:timc subsidy (dkWh) 3.08 2.97 2.84 2.68 2.50
3. Capital cost and opportunity cost (dkWh) S.s5 4.62 3.82 3.11 2.50
4. Opportunity cost-rate Iifdiwe subsidy (dkWh) 0.00 0.93 1.73 2.44 3.05
S. Total average lifc:timcsubsidy (dkWh) S.sS S.SS S.sS S.SS S.sS.The opportumty cost rate consl(lcrcci W8S 4 %perycar.•
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Economie and Exergetie Optimization Analysis of Space Heating Systems 116
progressively increasing the subsidies until the minimum cost solution with subsidies is
identical to the minimum exergy solution (note that the minimum exergy solution does not
involve economic considerations).
Tables 5.12 and 5.13 summarize the results oftrials with the various proposed subsidies for
the space heating problem. Table 5.12 shows the subsidies in the initial capital and
opportunity costs for Québec. Severa! points should be highlighted about the results shown
in Table 5.12:
(i) There are various possible combinlltions of initial capital and opportunity costs
subsidies which result in the same exergy solution. For each ofthem the totallifetime
subsidy is 5.55 clkWh.
(u") The initia\ capital cost subsidy in the ground-to-air heat-pump in Québec varies
between SI% and 66% ofthe cost ofthe initial investment for an opportunity cost
rate variation subsidy of0 to 4% per year.
(m") The initia\ cost subsidy over the lifetime ofthe ground-to-air heat-pump varies from
3.0S clkWh to 2.50 clkWh, as the subsidies in the opportunity cost rate increased
from 0 to 4% per year. An increase in the opportunity cost rate from 0 to 4% per year
corresponds to a lifetime subsidy of0 to 3.05 clkWh.
(IV) Note that the opportunity cast rate subsidy in % peryear can be trans1ated ioto clkWh
over the lifetime ofthe device. For example, comparing a subsidy in the opportunity
cost rate of2 with4%peryearimpliesin 1.73 and 3.05 clkWh respectively. Notethat
this correspondence is non linear.
Table 5.13 shows the subsidy in the initia\ capital ofthe heat-pump-ground-to-air and in the
electric rate in order to make the minimum exergy solution equal to the minimum subsidized
cost solution. Analysing Table 5.13 note that:
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Economie and Exergetie Optimization Analysis of Space Heating Systems 117
Table 5.13 Heat-pump ground-to-air initial capital subsidy and maximum rate for theminimum solution XR be the minimum cost solution.
Initial Capital Ratesubsidy
Observations(%) (clkWh) Québccrate (clkWh)
subsidv%
50 3.43 28 4.72
55 3.77 21 5.18
60 4.12 13 5.64
65 4.46 6 6.10
70 4.80 0 6.56No nccd for rate subsidy in Québec(rQB =6.52 clkWh).
75 5.15 0 7.02
80 5.49 0 7.48
85 5.83 0 7.94
90 6.17 0 8.40
95 6.52 0 8.86
Eve:n for 100"10 capital subsidy inNew York100 6.86 0 9.32 (rNY - 16.56 clkWh) and in Ontario (m -
9.56 <:/kWh) somc rate subsidy are required.
(i) Considering row 1, a 50"/0 subsidy in the initia1 capital cost ofthe ground-to-air heat
pump, together with a maximum rate of4.72 c/kWh makes the average Iife-cost of
the heat-pump competitive with direct heating. This implies that a large rate subsidy
in Québec that is 28% ofthe present average rate or 85% for New York. Note that
a subsidy of72% in the electric rate in New York is equivalent to (16.56 - 4.72 =
11.84 c\kWh).
(n) When the initial capital subsidy reaches 70"/0, the maximum rate required is 6.56
•
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Economie and Exergetie Optimization Analysis of Space Heating Systems 118
clkWh. Since this is approximately equal to the electricity rate in Québec. no rate
subsidy would be required in Québec. On the other band in Ontario and New York
subsidies of (9.56 - 6.56 = 3.00 clkWh) and (16.56 - 6.56 = 10.00 clkWh) are
required respectively.
(JÜ) Even with 100"/0 capital subsidy the maximum electric rate to make the heat-pump
ground-to-air competitive is 9.32 clkWh. Since the electricity tariffin New York and
in Ontario are 16.56 clkWh and 9.56 clkW h respectively, some rate subsidies are still
required even in this case when the heat-pumps are given free ofcharge.
5.6 Closure
This clJapter bas investigated the optimi711tion ofa space heating system subject to constraints
with four diiferent alternatives: electric baseboard, ground-to-air heat-pump, air-to-air heat
pump and direct fossi! fuel heating. The design is based on the minimization ofthe energetic
or ex:ergetic conswnption at the natural resource level and the cost to the eustomer as welI
as combinations ofthese.
Since ex:ergy is the abi1ity ofa given form ofenergy to be converted into any other fonD, it
is argued in this chapter that the most rational manner to optimize any energy system (not just
space heating systems) is byminimizing the exergy consumption at the natural resource level.
In other words, that electric energy systems should be designed by maximizing their 0vera11
ex:ergetic efliciency. The case studied here, showed that although, in some specia1 cases, the
maximum energy efliciency solution may coincide with the maximum ex:ergy efliciency
sohrtion, this is not tIlle in general. Thus, in general, to design energy systems rational1y, it
becomes essenriaJ te explicitly include exergy in the objective iùnction ofthe design problem.
•
•
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Economie and Exergetie Optimization Analysis of Space He'3ting Systems 119
In order to ensure that the system design corresponds to the minimum exergy solution, it is
hypothesized here that the given energy end-uses will he met by those alternatives that
minimize the cost to the customers. In other words, the end-users of energy will tend to
choose the cheapest alternatives according to their Iifetime costs. Ofcourse, in a real system
there is no guarantee that this hypothesis will he followed exaetly because ofreasons such as
human preferences, convenience, Jack ofinformation or concem for the environment but these
have not been modelled in this thesis.
Thus, diffoent cost inœntives were tested in order for the miniTD1Jm exergy and minimum cost
solutions to he identical. The costs incentives studied were subsidies in the initial capital cost
investment, opportunity cost rate and the energy tariffs. Although the minimum exergy
solution could be achievOO with different combinations of subsidies, those involving ooly
subsidies relatOO to capital investments appear to be easier to implement.
It is notOO that this chapter dealt with the optimal design ofan energy system with ooly one
end-use, namely space heating, thus, the resuIts serve ooly to illustrate the methodology.
Nevertheless, the approach tan he extendOO to more genera\ systems with multiple end-uses
(see following chapter).
•
•
•
Exergetic Optimal Regional Planning
Chapter6.
Exergetic Optimal Regional Planning
6.1 Introduction
In tbis chapter, severa! planning scenarios are analysed for two neighbouring energy systems,
name\y the Canadjan provinces ofQuébec and Ontario, each with a diffèrent generation mix
consisting of a combination of natural resources such as hydrauIic potential and nuc1ear
energy (Figure 6.1). The main kinds ofend-uses considered in the energy planning process
areheating, traetionand Jighting, eachofwhichismetbyavariety ofpossible end-use devices
such as: e1ectric baseboard heaters, heat-pumps and motors.
In contrast to the results shown in chapter S, where only one end-use (space heating) was
considered, the present chapter presents an energetic and exergetic analysis for a multiple
end-use case with multiple natural resources. The system is subject to a series ofconstraints
in the available energy and ex:ergy produced by each end-use device as weil as in the
120
• Exergetic Optimal Regional Planning 121
•
~J._I-QlI~llI-.1.c:.),.
--ul1 = ",œ_
n-N-o-......-r-m-s...... -~..--~ ..c__ -1 -""t--.k-{__r
li-< _'1.-"",-),~ "'_ '1.
, ...-I- Il -= +-- -=-oa y
H=,""t-r-t-r- l '"'t.- -~-r-~
io-{- ~
r-< .... .....'- -
~-- --.k-{-r-, ~ ......- ~ 1
11. ...."""- ......
-J __ -.JrtI.-el...~'Ill-.l~ ~
...JIM~I....... 11 = , -_."-l'''~ =:::-le&-...
rr-~,~~ 4-l~ -- . !o-(........""t-r-r_rf-
~K-. ....'l. ..-,....... Il'= = ~-y
H=.""t-r-f-.......~- K-
~--<- li'
--- -----..a--t-----.r- -<--~-
.....~ -..:;- ......-
:..v-u. z:ef1Mry le ••l-etrl.c coot1DQ futUca ga--r. - pont-p1aDt œ - d1nct ....ter bMtbg' 1'llnI.~ D. - _t'Uel.Dt IlOtorTa - uaDepoZ'hiUOD .s.Y1ce a - dKtJ:lc ••t ..:r beat1q DI - iD.u1c1ell:t IIOtœtD - UaDmb.1OD aDd clhtnbat10D 01 - ,.tzole_ aatual naouc. Co • aWc1nt llvll.W;DB ••PAc. beatiDQ fUDaC41 9a • lI&tDJ:al pa n.oarce :u. • 1h:fic1u.t IlOtot'U - alectr1c ba• .t>oa:d co - ~ Datua1 nlloa:c. SB - tpaca bMdJlglta_ • but-pap v~ad·to-a1% aa • IlDCl.u aurgy nlouce es: • coot:1D9Ipaa - but-pap ~o-a1: by - byœo ue:tgy n.oœce WB - _.tu beath;De • d1nct COOUD9 t'unac. 011 • OD.taJ:1o te. - ta_Ua; load
110 - ·':aoa1aa1oD. l1.D.
Figure 6.1 Mede! for regional planning.
intermediate energy conversion stages and in the natura! resources themselves.
A series ofsimulation results is presented inc1uding:
• (i) The 1995 Québec and Ontario system;
• Exergetic Optimal Regional Planning 122
•
•
(Ii) The optimization of the 1995 energy systems of both provinces taking into
consideration the F1I'St and the Second Principle ofThermodynamics efficiencies;
(Iii) The influence ofa transmission line connecting both provinces;
(iv) The influence ofstate constraints, that is, inequality lïnùts.
This chapter discusses, as weil, a proposition ofa type oftariffbased on the type-oj-use, as
opposed to the more common time-oj-use tariffs [Ge11ings & Talukdar, 1987; Baldick et al
1992; Me!ero, 1992; Cassanti & Esteves, 1990]. The main motivation for introducing type
oj-use tariffs is to force the system to maximize its overall exergetic efficiency. Simulations
were performed to test different tariffstructures to accomplish this objective.
6.2 Region Characterization and Model Description
The regional planning discussed here relates to the e!ectric energy systems ofthe Canadian
provinces ofQuébec and Ontario. Figure 6.1 shows an elaborate mode! ofthe various types
ofnatura1 resources, refineries, power-plants and end-use devices avai1able in both systems.
Note that hI! e1ectrical interconnection between the two regional systems is also present for
a possible intercbange ofe!ectric energy. For all processes, exergetic efficiency is calcu1ated
assnming the most efficient teebnology avai1able for converting that particular type ofenergy
towork.
FIVe end-usesl were considered,
1 Othcr eDd-uscs such as road llaaspo.ttation could also be considcrcd.
• Exergetic Optimal Regional Planning 123
(i) Space heating,
(ri) Cooking,
(Iii) Water heating,
(iv) Lighting,
(v) Traction.
The naturaJ resources considered for this regional planning study were:
(i) Hydra potential,
(ri) Petroleum,
• (Iii) NaturaJ gas,
(iv) Coal,
(v) Nuclear,
which cover the majority ofthe existing naturaJ resources.
Some important charaeteristics ofthe region under study are presented in Table 6.1. Note
that:
(1) The province ofQuébec genaates more tban 96% ofits e1eetricity from hydraeleetric
generatiOD, whereas Ontario generates much less in percent values, that is 29"/0. Since
the avaiIable work: in hydre potential or in e1eetricity is higher than in the other naturaJ
resources considered, it follows that Québec is a reIativeIy "exergetically rich
province" when compared with the province ofOntario.
• (2) Around 80% ofthe beating loaliin Ontario (mainly space heating, cooking and water
• Exergetic Optimal Regional Planning 124
Table 6.1 Important supply and load charaeteristics in Québec and Ontario in 1995.
Item Québec Ontario
1. Hydroeleetricity to total eleetric generation ratio (%) 96.1 29.0
2. Direct heating to total heating end-use ratiot (%) 45.4 80.4
3. Eleetric heatinlZ to eleetric load ratio (%) 29.7 18.7.t Space hcating, watcr hcating and cooking.
Sourcc:[Canada, 1993; Québec, 1993; Québec, 1995; Gcrlbard & Li , 1993ab; Law, 1993ab; Zhu& Lodoia, 1993ab]
•heating) is provided by direct oil or gas fumaces or stoves wlùle in Québec this figure
is only 45%. This tends to worsen the Second Principle efficiency in Québec relative
to Ontario.
(3) The eleetric heating load in Québec represents around 29"10 ofthe total eleetric load
while in Ontario this figure is estimated to be around 19"10. Once again, since this end
use is mainly in the form of \'laseboard heaters, the exergetic efficiency in Québec
worsens in comparison with Ontario.
It is important to point out, as we11, that the heating loads in Québec represent around 49"10
of the peak power. In other words, out of 33,270 MW of the peak power requirement
forecasted by Hydro-Québec for 1995, 15,960 MW were foreeasted as total peak operating
demand for resîdential space heating, commercial space heating, hot water for the commercial
sector and dual fuel space heating. The equivalent figure for energy consumed in heat related
loads is 42.8 TWh compared to a total of144.1 TWh (29.7%). This represents a very poor
load fàetor for eleetric heating loads. Thus, any economy in the energy consumed in heating
loads results in appiOximately double the savings in peak power [Québec 1993, 1995].
• Exergetic Optimal Regional Planning
6.2.1 Regional planning mode!
125
•
•
The mode! shown in the Fig<1I"e 6.1 is descnoed by 25 states for each province. Each state is
assumed to he represcnted by two quantities: energy and ex.ergy. The states are listed in Table
6.2. Note that:
(i) The first 12 states represent the energy/exergy end-uses. AlI end-uses are considered
to have two pOSSlole end-use devices, except for the space heating end-use that bas
four alternatives end-use devices;
(ri) The five natural resources, nuclear energy, hydro potential, petroleum, naturaI gas and
coal are represented by the states 13, 14,23,24 and 25 respectively. The naturaI
resources feed either the e!ectric system (power-plants and transmission lines),
represented by the states 18 to 22 or refineries and transportation systems,
represented by the states 15 to 17;
(m) Not all energy conversion devices shown in Figure 6.1 are represented by a state. A
set ofstates that represent a system is10 a certain extent a choice made by the energy
planner. In otherwords, different sets ofstates cao he chosen to represent an energy
system.
(v) The last state shown in Table 6.2, TL, represents the transmission line energy flow
connecting the two provinces;
For each province, a set of12 equationSZ forms part ofthe mode! shown in Figure 6.1. The
first five equations represent the relations between the end-use energy requirements and the
outputs ofthe end-use devices,
2A similar set ofrelatiOllS applies 10 the c:xcrgyvariables.
• Exergetic Optimal Regional Planning 126
Table 6.2 States considered for Québec and Ontario.
State Description
1 output ofspace heating furnace
2 output ofbaseboard e1ectric heater
3 output ofheat-pump air-to-air4 output ofheat-pump ground-to-air
5 output ofdirect cooking stove
6 output ofe1ectric cooking range
7 output ofdirect water heating furnace
8 output ofe1ectric water heater
9 output ofefficient motor
10 output ofinefficient motor
11 output ofinefficient Iight
12 output ofefficient Iight
13 nuclear energy resource
14 hydre energy resource
15 output ofoil transportation system
16 output ofnaturaI gas transportation system
17 output ofgas from coaI transportation system
18 output ofoil tired power plant and e1ectricity transmission
19 output ofgas tired power plant and e1ectricity transmission
20 output ofcoal tired power plant and e1ectricity transmission
21 output ofnucIear power plant and e1ectricity transmission
22 output ofbydro power plant and e1ectricity transmission
23 petroleum energy resource
24 naturaI gas resource
25 coal resource
TL transmission line fiow between Ouébec and Ontario,........-. .-The twelve first states COIlcspcmds to the r:=rgy/=gy output ofthe cod use dcvices.
•
•
• Exergetic Optimal Regional Planning 127
(6.1)
(6.2)
(6.3)
(6.4)
(6.5)
•where the symbols SH, CI<, WH, TR, LT in equations 6.1 to 6.5 represent the space heating,
the cooking, the water heating, the traction and the Iighting end-uses respectively. Later on
in this chapter an estimation ofthe end-use requirements for Québec and Ontario in 1995 is
presented.
The direct heating end-use states Ct , Cs, ~, must obey,
(6.6)
•
while the total e1ectricity delivered from alI natura1 resources to alI e1ectric end-use devices
requires that,
• Exergetic Optimal Regional Planning
e2 e3 e4 e6 es-+--+--+-+-+1'JDH 1'JHPga 1'JHPaa 1'JEC 1'JEW
e9 elo en el2 ell-+-+-+-:1:-1'Jat 1'JlM 1'Jzz. 1'JE!. 1'J7I.
128
(6.7)
•
•
Note that in equations 6.6 and 6.7 the parameters 1'JOH, 1'J00 1'Jow, 1'J1IPp> 1'JEC> 1'JEW. 1'JEM. 1'J1M,
1'J1I.> 'lJa and 1'JlL are the FII'St Principle efficiencies ofspace heating fumace, direct cooking
stove, direct water heater fumace, ground-to-air heat-pump, air-to-air heat-pump, e\ectric
cooking device, e\ectric water heater, efficient motor, inefficient motor, inefficient Iighting
device, efficient Iighting device, and the transmission line connecting both provinces,
respective\y. The Iast term in equation 6.7 represents the e\ectric energy to be transmitted to
Ontario from Québec and it is assumed positive for Québec and negative for Ontario.
In equations 6.8 to 6.12 the parameter 1'J represents the First Principle efficiency. The
subscripts 'IR, RE, pp and TI. refer respective\y to the transportation system, refineries,
power-plants and transmission Iines while the subscripts 01, gs, co, nu and hy refer to the
naturaI resources petroleum, naturaI gag, coaI, nuclear energy and hydroelectric potentia1. For
each naturaI resource, it follows from Figure 6.1 that,
el3 =e21
(6.8)1'JPP... 1'J7I....
el4 =e22
(6.9)1'JPPhy 1'J7I.1Iy
• Exergetic Optimal Regional Planning 129
(6.10)
(6.11)
•(6.12)
Equations 6.1 to 6.12 define the A matrix and the b vector for the energy system mode!. For
each province one such set ofequations applies. A similar set of 12 equations for each ofthe
two provinces must also be written for the exergy variables with the First Principle efiiciencies
replaced by the Second Principle efiiciencies.
To be able to perform the optùraation simulations for regional plllllllÎng, the end-use
requirements ofeach province must be estimated. This is the subject ofthe next section.
6.2.2 Estimation ofthe end-uses for Québec and Ontario for 1995
As discussed in chapter 3, the end-uses are considered to be the input to the energy system
planning mode! wbile the natural resources and the other states represent the variables to be
• Exergetic Optimal Regional Planning 130
optimized. Thus, in order to perfonn optimization studies, it is essential to estirnate the value
ofthe energy and exergy end-uses. In this section, the values ofthe main energy end-uses for
the Canadian provinces ofOntario and Québec are evaluated. The estùnations were based on
statistics from the provincial utilities and Canadian government bodies [Gerlbard & Li
1993ab; Zhu & Lodola, 1993ab, Law, 1993ab, Québec 1993; Québec, 1995; Statistics
Canada, 1994).
The energetic content ofthe end-uses is given by,
(6.13)
•where eu; is the end-use energy ~ c; is the energy supplied to the energy conversion device i
and Th is theFm Principle efficiency (or coefficient-of-perl'onnance) ofthe energy conversion
device i.
Similarly the exergetic content ofthe end-use is given by,
(6.14)
•
where X1Ij is the end-use exergy ~ Xj is the exergy supplied to the conversion device ~ and Ej
is the Second Principle efficiency orthe energy conversior ;evice i.
Notethat the end-uses in bath provinces were el'timated per sector whenever such data were
available. The three sectors considered in this study were:
• Exergetic Optimal Regional Planning 131
Table 6.3 End-use energy for Québec in 1995.
Electric Non-Electric TotalEnd-use Sources Sources
GWblvear % GWblyear % GWblvear %
1. Space heating 38,063 52.5 34,467 47.5 72,530 100.0
2. Cooking 643 99.7 2 0.3 645 100.0
3. Water heating 9,234 63.0 5,424 37.0 14,658 100.0
14. Lighting 3,011 100.0 0 0.0 3,011 100.0
S. Traction 51,543 100.0 0 0.0 51,543 100.0. .Source: [Québec, 1993; Québec, 1995 ]
• ti) The residential sector,
(u) The commercial sector,
(Iii) The indnstrial sector.
The majority ofthe available data for the commercial and indnstrial sectors ofOntario and
Québec does not include the efficiency of the energy conversion devices. Thus, here,
whenever these data were not available, it was assumed that each alternative at those two
sectors had the same efficiency as the corresponding alternative in the residential sector.
Tables 6.3 and 6.4 respectively slImmarize the end-use estimates from e\ectric and non
e1ectric sourœs in Québec and Ontario for 1995. In Appendix C, further details are provided
about the e:srimatil)n ofend-uses for each sector and province. Analysing Tables 6.3 and 6.4,
notethat:
(1) The encI-use space bearing requùement is around 20"/0 higher in Ontario than i Québec
but in Québec around 52.5% of me space heating requirements is e\ectric. The
• Exergetic Optimal Regional Planning
Table 6.4 End-use energy for Ontario in 1995.
132
•
E1ectric Non-E1ectricTotaI
End-use Sources Sources
GWb/vear % GWb/vear % GWb/vear %
1. Space heating 17,865 20.4 69,818 79.6 87,683 100.0
2. Cooking 1,896 58.0 1,375 42.0 3,271 100.0
3. Water heating 5,811 37.8 9,550 62.2 15,361 100.0
4. Lighting 2,634 100.0 0 0.0 2,634 100.0
S. Traction 54.119 100.0 0 0.0 54.119 100.0Source: [Gerlbard & Li, 1993ab; 1995; Low, 1993ab; Zhu & Lodola, 1993ab]
corresponding figure for Ontario is ooly 20.4%;
(2) Due to the Jack ofavailable data, most probably, the estimated difference in the end
use energy for cooking between Québec and Ontario is fairly large. In Ontario, ooly
around 58% ofthe cooking end-use is e1ectric, while in Québec it is aImost 1()()O/O
e1ectric;
(3) The overalI amount ofwater heating requirements for Ontario and for Québec is very
similar, a1though two thirds of the energy to supply that end-use in Ontario have
fossil origin while in Québec the equivalent figure is approximately one third.
(4) The amount ofthe Iighting end-use is estimated to be 14% higher in Québec than in
Ontario. This unexpected estimate results from insuflicient knowledge ofthe Iighting
needs in the industrial sector ofboth provinces;
(5) Fmally the end-use traction in Ontario is evaluated to be approximately 54,119 GWh
in 1995, while the equivalent figure for Québec is 51,543 GWh. In both provinces the
end-use traction in absolute values is second ooly to the end-use space heating.
• Exergetic Optimal Regional Planning 133
Table 6.5 Fraction ofthe electric consli'Dption covered by the regional planning study in %.
Ontario
78.1
Québec
88.5
•
•
Table 6.S shows the estimated fractions ofthe total electric load covered by this study, that
is, around 78"/0 and 89% for Québec and Ontario respectively. The types ofloads not covered
by the study are: e1ectrolysis, TV and other miscellaneous types ofloads not specified in the
utilities' forecasts. The miscellaneous loads contain some fraction of the five end-uses
considered in this study (sec Appendix C). The total load is not modelIed becanse the
available data were in some cases classified according to sectors rather than end-uses. For
example, the available data for Ontario's cooking end-uses includes the data for the three
sectors considered, whereas the available data for the cooking end-use for Québec
encompasses only the residential sector. This could explain the apparent inconsistency for the
cooking end-use in Québec and Ontario;
As mentioned earlier in this thesis, the evaluation ofthe end-use requirements is important
since they are the driving force ofthe energy system planning process. Another important
consideration in this process is to determine the limiting cases of the Fl1'St and Second
Principle system efficienciesgiven a set ofpossible system configurations. This is the subject
ofthe next section.
6.2.3 LimitiDg levels ofFPT and SPT efficiencies
In the results that follow, ail possible combinations ofenergy suppliers and end-use devices
are ana1ysed to calculatethe entIgetic and ecergetic efliciencies limiting cases. Tbese limiting
• Exergetic Optimal Regional Planning
Table 6.6 Cases lirniting the values ofthe First Principle efficiency, Tl.
134
•
Min TI Ma.xTIEnd-use
TI System Configuration TIf System Configurationcol.) ("/0)
thermoelcetric gencration hydroelcetric gencration1. Space heating 31.0 and bascboard e1cetric 223.7 and ground-to-air hcat-
hcatcr pump
2.Cooking 15.8 thermoelcetric gencration 44.6 hydroelcetric generationand e1cetric cooking range and e1cetric cooking range
3. Watr:r heating 26.7 thcnnoelcetric gencration 75.2 hydroeIcetric gencrationand e1cetric water heating and e1cetric water hcating
~. Traction 18.6 thermoelcetric gencration 69.9 hydroeIcetric gcnerationand inefficient moter and efficient moter
5.Lighting 1.9 thermoelcetric gencration 17.5 hydroeIcetric gencrationand inefficient li
.and efficient llRhtin2
t Or ooeffiaent-of-performance
cases deline, for each end-use, the system configuration corresponding to the highest system
Tl or E. Such extreme cases are useful ta establish a range of feasible efficiencies in more
realistic designs. Tables 6.6 and 6.7, respective1y, 5ummarize the cases lirniting the values of
Tl and E for the five end-uses under consideration in the regional planning problem. Analysing
Tables 6.6 and 6.7 note that:
(a) Thermoe1ecttic generation is a1ways part ofthe system configuration for either the
minimum Tl or the minimum E solutions. Thus, thermoe1ecttic generation a1ways bas
the least priority in any optirnizarion procedure;
(b) For every end-use, the minimum Tl and the minimum E solutions are identical. In other
words, the worst design from the FIrst Principle point-of,.view is aIso the worst design
viewed from the Second Principle;
(c) Thebest SPT design aLoo corresponds ta the best FPT design on1y when considering
• Exergetic Optimal Regional Planning
Table 6.7 Cases limiting the values ofthe Second Principle efliciency, E.
135
•
•
Mine MaxeEnd-use
e System Configuration e System Configuration(0/0) ("/0)
thcrmoel::etric genaation hydroelcetric genaation1. Space hcating 2.1 and bascboard elcetric 6.4 and ground-to-air heat-
hcatcr pump
2. Cooking 4.8 thcrmoelcetric genaation 10.1 direct cooking rangeand elcetric cooking range -3. Walcr hcating 5.3 thcrmoelcetric genaation 8.2 direct water hcating
and elcetric watcr hcating furnacc:
~.Traction 46.5 thcrmoelectric genaation 1 73.6 hydroelectric genaationand incfficient motar and efficient mator
~. Ligbting 0.2 thermoelcetric genaation 2.8 hydroe1cetric g:naatiOl"and incfficient Iilililin2 and efficient lllililin2
space heating, traction or lighting end-uses. Note that in this coDfiguration
hydroelectricity is always part ofthe soL:ion;
(d) The maximum SPT efliciencies for cooking and water heating end-uses occur when
ooly direct heating is used;
(e) Fmally, note th~~ wider range oflimiting values ofT) compared v.ith those ofE. For
example, the case-1imiting values [or tilt: cooking end-use vaIY from 44.6% to 15.8%.
The comparabletigures for the SPT analysisare 10.1% to 4.8%.
It is expected that realistic designs would have their FPT and SPT efliciencies falling within
the ranges as shown in Tables 6.6 and 6.7.
• Exergetic Optimal Regional Planning
6.3 Regional Planning Optimization Studies
136
•
•
In this section, severa! oprimjzarion studies ofregional planning are presented. The results are
summarize.;l in Table 6.8. Each study is characterized by the following paramett".rs and
variables:
{ï) Transmission line limits;
(Ji) Upper bound limits on system variables;
(üi) Objective function;
(iv) First and Second Principle system efliciencies.
Analysing Table 6.8, the following comments apply to each case study:
(1) The first case study (row one ofTable 6.8) corresponds to the 1995 Québec-Ontario
system. Note that no transmission line or upper bound limits are considered h=. !t
is assumed that no known objective function is optim;zed by the 1995 system.
However, one can argue that the natwal tendency ofany energy system is to approach
the minimum cost solution at the customer level. Note also that the FPT efliciency of
Québec is much higher than the corresponding value for Ontario, 57.7Ofc. versus
34.7%. In contrast, the SPT analysis shows less than three percentage points
difference indieating that according to the SPT perspective, Québec is not much more
eflicient than Ontario. The reasons for this are discussed in Section 6.3.1;
(2) Case study two introduces state variable Iimits and optimizes the F1I'st and the Second
Principle system efliciencies. Again, no transmission line between the two provinces
is considered œthis simulation. Two objective functi:lns are studied: the minimization
ofthe energetic and exergetic resources. For the minimiZllrion ofthe energeric nat;n'a\
resources (Min ~, it is clear ftom Table 6.8 that ail FPT and SPT efliciencies are
• Exergetic Optimal Regional Planning 137
Table 6.8 Summary ofcases studied in rcgional planning.
Upper TI 10Case
TransmissionBound Objective ("/0) (%)
SlIIliyUne limit Limil Function10' MW QB ON RE QB ON REl
1 0 b no 57.7 34.7 42.5 30.2 27.7 28.9
Mine" 72.8 41.4 51.8 29.9 32.1 31.02 0 b:
Min"" 55.7 41.4 47.0 36.2 32.1 33.9
Mine" 75.3 57.3 62.2 43.0 34.8 31.33' 10 b
Min"" 60.8 S6.J 55.1 48.7 34.9 34.5
Mine" 76.5 59.8 64.2 43.6 35.3 31.;;4 10 b*U
Min"" 43.6 55.3 31.9 48.1 35.6 35.4
5 JO b lieD 42.7 38.7 405 34.6 315 32.9
6 10 b Ile", & lia" 64.2 56.3 56.7 47.8 34.9 34.1
7 10 b 1110.& lia.: 60.8 S6.J 55.1 48.7 34.9 34.5. ., RE 1$ the rcgJon fClmlCd by the proVIDCCS Québec and OIItario.: The upper bouDd base case 1imits for the provincial states are dcsaibc:d in Table 6.10.• Except bydro resourccs, M1.a•Ô= 1.61.
•lerger than the 1995 case with the exception ofthe SPT efficiency in Québec that is
slightly sma1ler than the 1995 value. The Iast comment applies, as weil for the
minimizarion ofthe exergetic resources, except that, in this case, ail efficiencies are
greater than for the 1995 case. Note that, as expectecl, for minimum exergy, the SPT
efliàency is greater than the corresponding values for the minimum energy solution.
On the other band, for minimum energy, the FPT efliciency is greater than the
corresponding values for the minimum exergy case;
(3) Case study tbree simnJates the ÎIlfiUence ofthe transmission line capacity between the
two neighbouring provinces. The values ofthe FPT and SPT efliciencies shown in
Table 6.8 conespond to a transmission line capacity of10,000 MW. This study case
is further discussed in Section 6.3.3. Note that the value ofthe regional FPT efliciency
• Exergetic Optimal Regional Planning 138
•(4)
when the objective function is the minimization ofthe energy resources illcreases from
51.8% to 62.2% because of the acided tie-Iine energy exchange. Note that the
corresponding SPT eflic)ency for the region increases s1ightly from 31.0% to 31.3%,
but the provinces individually had their SPT efliciencies changed by a much greater
proportion. For example, Québec had its SPT efliciency increased by more than 13
percentage points. The reason for this is that a larger ofQuébec's end-use is now in
the form ofelectricity exports to Ontario. In the same manner, the value ofthe system
SPT efliciency when the objective function is the minimization of the exergetic
resources increases from 33.9"/0 to 34.5% with the addition ofthe tie-line between
Québec and Ontario;
Case study four investigates the influence ofincreasing thl' l1pper bound limits in ail
the state variables. The efliciencies shown in Table 6.8 correspond to a relaxation of
10% above the limits considered in the base case (see Section 6.3.5). Comparing the
corresponding values ofcases three and four note that a 10% relaxation in the state
limits increases the FPT efliciencies in ail cases, but not necessarily the SPT
efliciencies. The physical realiZJ!tion of a change in the limits in question is a non
trivial task requiring major investments and a change in the end-uses consumption
patterns;
Study cases S, 6 and 7 correspond to diffèrent experiments carried out to try to acbieve the
minimum exergy solution by the proper choice ofweigbting fàctors in the objective function.
The motivation for these elCperiments was to find a set ofweighting factors corresponding to
energy tariffs wbich, ifintplemented, would induce the end-uses and the utilities to consume
energy in a manner consistent with the minintum exergy solution.
•(5) The first experiment (case study 5) consisted of minimizing an objective function
whose weights were applied ollly ta the end-use devices and were equal to the inverse
of the SPT device efliciencies. This experiment was only partial1y successfil\ in
• Exergetic Optimal Regional Planning
reaching the minimum solution;
139
•
(6) The second experiment (case study 6) applied the following weights: the output of
every device in the system was weighted by the inverse ofthe SPT efliciency ofthe
device, while every resource was weighted by the inverse of the corresponding II
(fraction ofthe resourœ energy content corresponding to the available work). This
case came closer (Ontario's states, Îor this case, are identical to the minimum ex:ergy
solution) to meet the goal but the weighting factors were somewhat diflicult to
rationalize, since every variable in the system is charged a tariff including the
intennediate and the resource states;
(7) The final ex:periment summarized in Table 6.8 was complete1y successful in achieving
the minimum exergy solution. Fssentia11y, tariffs in the form ofweighting factors were
applied only to the outputs ofthe end-use devices and to the natural resources. The
end-uses output were weighted by the inverse ofthe device SPT efliciencies while the
resources were weighted by the inverse of II. Section 6.3.5 gives more details about
these results.
6.3.1 Québec-Ontario 1995 system
Table 6.8 shows that the Québec-Ontario region in 1995 had FPT and SPT efliciencies of
42.5% and 28.9"/0 respectiveIy. However, from both perspectives, the province ofQuébec is
more efficient than Ontario. On the other band, the SPT efficiency for Québec is not much
cliffe:ent from the corresponding value for Ontario in percentage values. The reason for this
becomes clearby ana1ysing Table 6.9 showing the details ofail the energy and ex:ergy states:
(a) Québec is re1ative1y richer in ex:ergetic resources (hydro) than Ontario bet it uses a
greater proportion for baseboard electric heating among other ex:ergetically inefficient
• Exergetic Optimal Regional Planning
Table 6.9 Energy and exergy states considered for Québec and Ontario for 1995.
140
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StateEnergy output in GWh Exergy output in GWh
Québec Ontario Québec Ontario
1 34,466 69,818 931 1,885
2 36,862 16,338 995 441
3 857 1,085 23 29
4 344 423 9 Il
5 2 1,375 0 165
6 43 1,896 77 228
7 5,424 9,550 434 764
8 9,234 5,811 739 465
9 20,872 35,871 20,872 35,871
10 30,668 18,248 30,668 18,248
Il 426 656 51 79
12 1,146 1,977 138 237
13 13,920 192,090 5,568 76,836
14 153,433 41,100 145,761 39,045
15 37,224 55,441 14,890 22,176
16 20,425 61,763 8,170 24,705
17 0 0 0 0
18 1,067 587 1,014 558
19 0 2,114 0 2,009
20 0 24,843 0 23,601
21 4,364 60,220 4,146 57,209
22 134,101 35,921 127,395 34,125
23 50,921 72,608 20,368 29,043
24 26,052 85,454 10,421 34,182
25 0 79,246 0 31,698
TI. 0 0 0 0
• Exergetic Optimal Regional Planning
uses;
141
•
•
(b) On the other band, although Ontario bas fewer hydro resources, it uses less electric
baseboard heating and more direct heating loads;
(c) The output energyleve1s ofend-uses 1 to 8, (heat-related), 11 and 12, (lighting), are
significantly larger !han the corresponding exergy values. The reason for this is the
relatively low SPT efficiency ofsuch end-uses;
(d) Traction (state~ 9 and 10) bas the same value for energy and exergy;
(e) Considering rows 13, 14,23,24 and 25 (natura! resources nuclear energy, hydro,
petroleum, natura! gas and coal), it is noted that Ontario uses much more fossi! fuel
and nuclear energy !han Québec.
One important issue that arises examining the Québec-Ontario 1995 energy and exergy
scenario is how to improve the use ofthe available natural resources. There is no simple
answer to this question. However, the following approaches are possible:
(i) By optimizing the system at the level ofthe utilities or the customer or bath. This can
be accomplished by systematic programing methods or by ad-hoc r·rograms;
(ü) By broadening the scope of the planning process to include as many end-uses as
possible. For example, ifroad transportation were included in the regional planning
model the overall SPT efficiency could be substantially improved by the replacement
ofinternal combustion engine vehicles (ICEV) by electric vehicles (EV);
(üi) By introducing govemment regulations, tax incentives and special exergy tariffs to
induce bath utilities and customers to adopt solutions consistent with the minimum
exergy plan.
• Exergetic Optimal Regional Planning
6.3.2 Base case constraints for regional planning
142
The assumed base case upperbound 1imits for the system states are listed in Table 6.10. The
lower bound Iinùts were considered to be ail equal to zero. The upper 1imits were defined as
afunction ofthe 1995 values. For example, states 1and 2, the outputs ofthe space heating
fumace and electric baseboard heater, respectively, were aIlowed to vary from zero to 100010
ofthe maximum ofthe 1995 values ofel a.'1d ~. Then,
(6.15)
•
•
where U1,2 is the upper bound limi'"..s Ïcr states 1and 2.
In choosing the upper bound 1imits of the system states, a certain amount of subjective
judgment was used. The rationale for the choices made in Table 6.10 is described be1ow:
(i) Heating fumaces and electric baseboards (states 1 and 2) have more flexible 1imits
than the her~-pump options (states 3 and 4) to reflect the substantially greater life
costs ofheat-pwnps. ln oth<:r words, the cost1ier the device, the lower the assumed
upper bound 1imit;
(u) Direct heating devices were estimated to have a 1imit 100010 above the corresponding
electric end-use device options. This reflects the fact that the direct heating options
are most like1y to be adopted by the QlStomers in the advent oftype-of-use tariffs due
to their relatively high SPT efficiencies and low cost;
(ili) Nuclear energy resources in both provinces were estimated to remain at their 1995
levels as a result ofenvironmental restrictions;
(IV) The upper limits on the hydroelectric resources in Québec and in Ontario were
estimated to be, respectively, up to 100% and 10010 above the 1995 levels. This
• Exergetic Optimal Regional Planning
Table 6.10 Upper bound (base case) state limits considered for regional planning.
143
•
•
Québec Ontario ObservationsStatc
GWh GWh Limits above 1995 values
el 73,724 139,636 100"10 ofthe maximum value ofthe el and C:! states oft1:le
C:! 73,724 139,636 lespcx:ti.e province
Cs 1,071 1,356 ~%m~maximumval~m~Cs~~statesm~
e, 1,071 1,356 respective province.
e:, 1,286 3,792 100"10 of the maximum value ofthe e:, and Co states ofthe
Co 1,286 3,792 respective province.
e, 18,468 19,100 100% ofthe maximum val~ of~ e,~ Cs states ofthe
Cs 18,468 19,100 lespcx:tive province.
Cs> 38,335 44Jt~:I ~% ofthe ."QllXÎmum val~ of~ Cs> and c,o states ofthe
elo 38,335 44,839 lespcx:tive pn'vince.
C,I 1,433 2,471 ~%of~maximum val~ ofthe C,I and c,: statesof~
c,: 1,433 2,471 respective province.
e" 13,920 192,0900%of~maximum val~ of~ c" state ofrespective~province.
c" 306,866 45,210 100% and 10"10of~ maximumval~ of~ c" state of~ respecti»e province.
c's 372,245 617,631 900%of~maximum valueof~ c's~ C,6 states of
C,6 372,245 617,631 ~ respective province.
c" 0 0 0"10of~maximum value.,r~ c" state mrespective~province.
c,. 268,201 120,441
c,. 268,201 120,441
C:!o 268,201 120,441 l00"loof~ maximum valueof~ c,. te C:!: statesof~respective province.
C:!I 268,201 120,441
C:!: 268,201 120,441
e:. 509,208 854,538 900%of~ llJ8YÏmnm valueof~ e:.~ e.. states of
C:!, 509,208 854,538 the respective province.
C:!s 0 854,5380% and 900%of~maximum valueof~ C:!s statem~.
• Exergetic Optimal Regional Planning
reflects the considerably higher hydroelectric potential in Québec;
144
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(v) The output ofnaturaI gas and oil transportation systems as weil as the output ofaIl
types ofelectric transnûssion Iines and power plants were aIIowed to vary up to 900"/0
of their 1995 values. This was done sa !hat the results of the oj.ltimization not be
constrained by these intermediate states. In other words, it was decided to restrict the
optimal design by 1imits on the naturaI resources and end-use devices only.
6.3.3 Impact of transmission line capacity
This section presents the results ofsimulatîng increasing transmission line 1imits between the
neighbouring provinces ofQuébec and Ontario. The intent is to try to improve the regional
efliciency by increasing cooperation. Two sets ofsimulations were done, the maximization
ofthe SPT (Table 6.11) and FPT (Table 6.12) efliciencies. In bath cases, the transmission line
1imit'~ varied in increments of 1,000 "MW up to a point where further increases did not
affect the optimum system efliciency. When considering the interchange ofenergy between
the two neighbouring provinces, the electric energy received by Ontario from Qu~ is
considered as a Québec end-use. On the other band, the electric energy received by Ontario
from Québec is treated as a resource for Ontario. These definitions are used to find the
provincial efliciencies in an interconnected system.
For example, from Table 6.11 it can be seen that, by adding a 10,000 MW transmission line
3 Note that sincc the Iinccapacity is in MW, in orcier ta fiDd ils yearIy c:ucrgy tnmsmission, a
load factor of60"/0 was assumed.
• Exergetic Optimal Regional Planning 145
•
•
Table 6.1 1 SPT efficiency, for max e, for increasing values oftransmission line capacity.
Transmission line dataObjective Funetionfrom Québec to Ontario
MaxeCapacity Optimum Flow1()lMW 1()lMW Ouébec Ontario R.eltion
0 0 36.2 32.1 33.9
1 1 38.0 32.3 34.0
2 2 39.6 32.6 34.1
3 3 41.2 32.9 34.1
4 4 42.6 33.3 34.2
5 5 43.9 33.6 34.3
6 6 45.2 33.9 34.3
7 7 46.4 34.2 34.4
8 8 47.5 34.5 34.4
9 9 48.5 34.9 34.5
10 9.2 48.7 34.9 34.5
II 9.2 48.7 34.9 34.5
one can improvethe optimum SPT efficiency ofthe system from the 1995 level of33.9"/o to
34.5%. Above a line capacity ofl1,OOO MW, the maximum SPT efficiencies ofthe provinces
and oft~ system are not aflècted. Thus, it does not pay to increase the line capacity beyond
11,000 MW for the purpose offurther increasing the optimum SPT efficiencies.
Note aIso, from Table 6.11, that the optimum SPT efficiency in Québec increases with higher
transmission f1ows. This is reasonable since a greater proportion of Québec's end-use is
devoted to supply Ontario with dectric energy, that is, an end-use with a high exergetic
content. From the same table it cao be seen that Ontario's optimal SPT grows, a1beit at a
lower rate. This behaviour is due to (t displacement ofless efficient thennoelectric sources
• Exergetic Optimal Regional Planning 146
•
•
Table 6.12 SPT efficiency, for max T'J, for increasing values oftransrnission line capacity.
Transmission line dataObjective Function
frOID Québec to OntarioMaxT'J
Capacity Optimum Flow1Q3MW 1Q3MW Québec Ontario R on
0 0 29.9 32.1 31.0
1 1 31.6 32.3 31.0
2 2 33.1 32.6 31.1
3 3 34.6 32.9 31.1
4 4 36.0 33.3 31.2
5 5 37.4 33.6 31.2
6 6 38.6 33.9 31.2
7 7 39.8 34.2 31.3
8 li 40.9 34.5 31.3
9 9 42.0 34.9 31.4
10 10 43.0 34.8 31.3
11 11 43.9 34.7 31.2
12 12 44.9 34.6 31.1
13 13 45.7 34.4 30.9
14 14 46.6 34.2 30.7
15 15 47.4 33.9 30.5
16 16 48.1 33.7 30.3
17 17 48.9 33.4 30.1
18 18 49.6 33.2 30.0
19 18.1 49.8 33.1 30.0
20 18.1 49.8 33.1 30.0
by imported hydroelectricity. The system efficiency saturates al 34.5% due to the IDOst
• Exergetic Optimal Regional Planning 147
•
•
35 - . . . · · · · · " · · · · · · · · · · · . · · . . . · . · · - - - · · · · · · - - - · - "
Min XR
34- -.-. · · · · - - , · · · . · · - - - · · " · · . · . · 0 - - -, - 0 - 0 · 0 0 0 · 0 · · ·.....
-!~33- 0 0 . · · · · · · . . · 0 · - · · · 0 0 0 0 - 0 0 · - - 0 - - · · . · . · 0 · 0 · 0 0 0 0 · · 0
0,
c..'0E...... ·l1.<0.32- 0 . 0 - · · · · - 0 · 0' · · · 0 · 0 - · · · • '0 · · 0 0 0 · 0 · 0 0 · .' . . · · · · · . · · · · ·c.5! :Min
~Q.. ·Œ - "'"..;,. - ·- ......... "'"31 · · . · · . . · · · . · · · · · · · ·.. · · -.,· · . · . · . · · · · · . · · · · '., ·
"·
. '- ·.30 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 5 10 15 2Transmission line capacity (1000 MW)
Figure 6.2 Second Principle efficiencies for increasing values oftransmission line 1imits.
efficient end-uses devices such as heat-pumps reaching their upper bounds (see Section
6.3.4).
Asecond set ofsimulations was aIso carrled out where the F11"St Principle system efficiency
was maximized (Table 6.12). Note that for this set ofsimulations the Québec's optimal SPT
efficiency increases from 29.9"/0 to 49.8%, again mainly because ofthe higher electricity
exports treated as end-uses. It is noted that the SPT efficiency under the conditions of
maximum FPT is, as expected, a1ways below the corresponding value when the objective is
to maximize the SPT system efficiency. It is interesting to note, however, (see Figure 6.2)
• Exergetic Optimal Regional Planning 148
•
•
that, under maximum FPT efficiency, the maximum line capacity beyond which the solution
does not change occurs at 19,000 MW ( compare Tables 6.11 and 6.12).
However, from Figure 6.2, it can be noted that the SPT efliciency actually worsens beyond
a line capacity of 10,000 MW under the minimum energy solution. This is due to the
rep\aœment ofsome direct heating in Ontario by baseboard e1ectric heating after heat-pumps
reach their leve1 ofsaturation.
6.3.4 Comparison of the 1995 case with the maximum SPT system
efliciency solution
This section descn"bes and compares in detail the 1995 case and the minimum xRbase case
(Table 6.8, case 3). These data are important to p1anners since they detail the exact changes
to the 1995 system to achieve a desired optimum solution.
Tables 6.13 and 6.14 respectïve1y represent for Québec an<LOntario the values ofthe states
for the 1995 case, the minimum "R solutionas weil as the upper bound IimiU. Analysing these
tables, the maximum SPT efficiency solution requires that the following changes be applied
to the 1995 case:
(i) Heat-pumps (3, 4), efficient motors (9) and efficient Iighting (12) must be set to their
maximum Iimits in both provinces;
(n) On the other band, deetric baseboard (2), e1ectric cooking range (6) or e1ectric water
heating (8) must be e1iminated from the optimum solution for both Québec and
Ontario;
(m) The GWh output of direct space heating fumaces (1) must be equal to the
•
•
•
Exergetic Optimal Regional Planning
Table 6.13 Comparison of 1995 and Min XR solutions in Québec.
Energy States e.. k=1•...25
State 1995 case MinxR UpperboundGWhJvear GWhJvear GWhJYe:JI
1 34.466 70.387 ï3.724
2 36.862 0 73.724
3 857 1.071 1.071
4 344 1.071 1.071
5 2 645 1.286
6 643 0 1.286
7 5.424 J4.658 13.468
8 9.234 0 18.468
9 20.872 38.335 38.335
10 3''1,668 13.205 38.335
11 426 140 1,433
12 1,146 1,433 1,433
13 13,920 0 13,920
14 153,433 150,333 306,866
15 37,224 63,054 372,245
16 20,425 63,054 372,245
17 0 0 0
18 1,067 0 268,201
19 0 0 268,201
20 0 0 268,201
21 4,364 0 268,201
22 134,101 131,391 268,201
23 50,921 80,426 509,208
24 26,052 80,426 509,20'3
25 0 0 0
149
• Exergetic Optimal Regional Planning
Table 6.14 Comparison of 1995 and Min xR solu~ons, in Ontario.
ISO
•
•
Energy states e., k=1,...25
State 1995 case MinxR UpperboundGWhlvear GWhlvear GWhlvear
1 69,818 84,952 139,636
2 16,338 0 139,636
3 1,085 1,356 1,356
4 423 1,356 1,356
5 1,375 3,271 3,792
6 1,896 0 3,792
7 9,550 15,361 19,100
8 5,811 0 1~,100
9 35,871 44,839 44,839
10 18,248 9,280 44,839
11 656 162 2,471
12 1,9n 2,471 2,471
13 192,090 0 192,090
14 41,100 45,210 45,210
15 55,441 76,760 617,631
16 61,763 76,760 617,631
17 0 0 0
18 587 0 120,441
19 2,114 0 120,441
20 24,843 0 120,441
21 60,220 0 120,441
22 35,921 39,513 120,441
23 72,608 97,908 854,538
24 85,454 97,908 854,538
25 79,246 0 854,538
• Exergetic Optimal Regional Planning 151
•
difference between the space heating requirement and the amount supplied by heat
pumps (3, 4). Thus, the output ofdirect space heating furnaces (1) must morethan
double in Québec while, in Ontario, it had to increase by more than 20"/0 compared
to the 1995 case;
(iv) Inefficient Iighting (11) must be used only when efficient lighting (12) bas been
saturated;
(v). No natural resource or intermediate conversion device reached its Iimits, ex:cept hydro
resources (14) in Ontario;
(vi) Nuclear energy (13) must decrease to zero in spite ofthe fàct that, nuclear energy
represents a major energy supplier in Ontario in 1995;
(vii) Hydro e1ectricity (14) decreases by 3,100 GWh in Québec. Using a 10ad factor of
60% this corresponds to approximately 600 MW reduetion in hydroelectric
generation! This is a surprising but a beneficial result that is even though e1ectricity
ex:ports increase, the overa1l e1ectricity generation decreases;
(viii) Th:: ;~ve is due to a substantial increase in the amount ofoil (23) and natural gas
(24) resources consumed. For ex:ample in Québec oil (23) must increase to
approximately 50,000 GWh to 80,000 GWh, while natural gas (24) increases from
approximately 26,000 GWh to 80,000 GWh;
(IX) The use ofcoal in Québec remains at the zero Ievel while in Ontario it drops to zero;
(x) No thermoe1ectricity is required in either ofthe provinces. Thus, the only oil-fired
plant in Québec would have to he shut down. On the other band, in Ontario, al1 ofits
1995 thermoe1ectricity, that is 87,765 GW"IJ, would have to he rephced by
hydroelectricity generated by either Ontario itseIfor by Québec.
(Xl) The overall energetic resources decreases from the 1995 value of715 TWh to 552
• Exergetic Optimal Regional Planning 152
•
TWh, in the minimum exergy solution. This is a reduction of approxirnately 23%
wlùch corresponds to approximately 10,000 MW ofthermoelectric generation.
Another important aspect :0 consider in the planning ofenergy systems is the sensitivity of
the optimum with respect to the upper bound state linüts. The next section discusses tlùs
topic.
6.3.5 Upper bound Iimits relaxation
In order to have a better understanding ofthe influence ofupper bound state limits on the
system behaviour, t1JA sensitivity ofthe objective function with respect to each state variable
limit was calculated. In tlùs section, such sensitivities are analysed fer both the base case
upper bounds described in Section 6.3.2 and for a modified base case. For the modified case,
an end-use devices and hydro resources were limited by a value 100/0 above t..if~ 1995 levels.
The 0Jébec-Ontario transmission line was limited to 1,000 MW, while an other stat~ limits
rernained unchanged. The upper bounds ofthe modified base case are much more restrictive
than in the bp.se case (see Table 6.10). Tois was done on purpose to check the influence of
the upper bound limits on the system exergetic behaviour.
The sensitivity ofthe objective function with respect to an active upper bound limit is given
by the corresponding Lagrange multiplier found during the optimization process. A selected
number ofsuch Lagrange multipliers for both the base case and the modified base case are
shown in Table 6.15. Note that:
•(i) The Lagrange multipliers ofthe direct heating end-use device options are nulI in the
~ case since their limits were not reached either in Québec or in Ontario;
• Exergetic Optimal Regional Planning 153
Table 6.15 Lagrange multipliers for selected states for minimum exergy.
Lagrange multiplier
State' Basecasc% ModificdBaseCaser
Québec Ontario Ontario Québec
1 Output ofspace heating fumacc 0 0 1.44 2.09
3 Output ofground-to-air bcat-pmnp 022 0.10 1.66 1.93
4 Output ofair-to-air hcat-pllIllp 1.02 0.93 2.45 2.85
5 Outputofdirect cooking steve 0 0 0.79 1.07
7 Output ofdirect water heating fumace 0 0 0.35 0.61
9 Output ofefficient-moter 0.05 0.05 0.05 0.05
12 Output ofc:(!iciCllt lighting 10.57 11.12 10.57 1228
14 H~resource 0 0.01 0 0.02
Transmission line flow bctwœnTL
Québec and Ontario 0 0.01
..• The states' dclinibOll1istlSfoundm Table 6.3.1The upper bouDd limils base case arc dcfiDcd in Table 6.11.1AIl Clld'IISCS dcviccs and hydro resourccs in bath provinces limited to 10% bcyond of1995 values,tnmsmissiOllIinc Québcc-OnIario limill,OOO MW, the=iDing states limited as base case.
•
(ü) In both provinces, efficient lighting bas the highest Lagrange multiplier. This implies
that a small increase in the UP!'ef bound of efficient lighting (12) wiIIlead to the
Iargest improvement in the system SPT efficiency when compared to increasing the
limits ofother states which are saturated. This filet is observed in both the base and
the modified base cases;
(üi) It is interesting to note that the sensitivity ofthe efficient motor with respect to ils
Iimit is the 10wesl among the states with non-zero Lagrange multipliers. This suggests
• somewhat paradoxic:illy that increasing the maximnm Iimit on efficient motoIS ,'IÏll
• Exergetic Optimal Regional Planning 154
•
have the least effect on the overall SPT efficiency, when compared to, for example,
the ground-to-air heat-pump. However, tIis res. 'lt is not illogical since both efficient
and inefficient motors have relative1y high and similar efficiencies;
(iv) The sensitivity ofthe optimal SPT efficiency with respect to the transmission flow
limit is very low indicating that, to the extent possible, it is preferable to increase the
limits of exergetically efficient end-uses devices than to increase the limits on the
transmission floW;
(v) According to Table 6.15 the prefeued order ofmodification ofthe upper bound levels
is as defined by the increasing order ofmagnitude ofthe Lagrange multipliers.
(iv) The sensitivity of hydro resources in Ontario is non zero, as opposed to the
corresponding value in Québec, indicating that these resources have reached their
assumed upper bound limits in Ontario but not in Québec.
Another important step to consider in energy planning is the implementation ofmeasures that
will induce the system to behave in a manner close to the min Xa solution. This is the subject
ofthe next section.
6.3.6 Exergetic or type-of-use tariffs
The rea'ization ofactions that leads te more exergetically efficient systems is discussed in this
section. Among the possible alternatives to achie-.i: a system that consumes its natura\
resources more efficiently according to the Second Principle ofThermodynamics one find:
talc incen~ programs, public awareness and the introduction of tariffs that reflect
• Exergetic Optimal Regional Planning 155
Table 6.16 Objective function for ext"I"8etic tariffdesign.
Objective fimction
Statc (i) (ü) (ili) (iv)lIe~ lie,. lIe~& lI(X"t Minx~
1 20.3 20.3 20.3 0.0
2 352 352 35.2 0.0
3 20.7 20.7 20.7 0.0-
4 13.7 13.7 13.7 0.0
5 7.8 7.8 7.8 0.0
6 15.s 15.5 15.5 0.0
7 9.6 9.6 9.6 0.0
8 13.8 13.8 13.8 0.0
9 12 12 12 0.0
10 1.6 1.6 1.6 0.0
11 131.9 131.9 131.9 0.0
12 39.6 39.6 39.6 0.0
13 0.0 2.5 0.0 1.0
14 0.0 1.1 1.7 1.0
15 0.0 1.0 0.0 0.0
16 0.0 1.0 0.0 0.0
17 0.0 1.0 0.0 0.0
18 0.0 1.1 0.0 0.0
19 0.0 1.0 0.0 0.0
20 0.0 1.1 0.0 0.0
21 0.0 1.1 0.0 0.0
22 0.0 1.1 0.0 0.0
23 0.0 2.5 2.5 1.0
24 0.0 2.5 2.5 1.0
25 0.0 2.5 2.5 1.0
51 0.0 l.l 0.0 0.0. .TAlI the œsoun:es have a wetgbting factor of lia. c:xœpt the hydro rcsoun:c that bas a factor of(1/a.)·1l, wb= Il was expcrimcntally fOUDd to bc cqual to 1.61.•
•
• Exergetic Optimal Regional Planning
the rationale ofthe SPT.
156
•
•
This section discusses ways to implement the maximum regional ex·.'igetic efliciency solution
through the concept oftype-of-use tariffs. This concept will charge CO:lSUIllers different rates
depending on the exergetic efliciencies ofthe end-use device. Such a tariffis analogous to the
more common tîme-of-use tariffs already existing. However, type-of-use tariffs would have
the tendency to induce consumers to use exergy more efliciently, thereby forcî."1g the system
doser te the minimum exergy solution. Thus, it is assumed that both utilities and end-users
will push the system to a minimum exergy solution in an attempt to minimize their cost.
Three possible objective functions were tested to simulate the concept of a type-of-use tariff
(see Table 6.16) where the objective function, t; is ofthe fonn,
(6.16)
The weigbting coefficients, wt , in the objective function represent' the type-of-llse tariffs. The
following types ofweighting coefficients were studied:
(i) The inverse ofthe SPT efliciency for ail the end-use conversion devices, lIE~
(ù) The inverse ofthe SPT efliciency at the end·use conversion devices, liED> combined
with the inverse ofthe estimated available exergy in the naturaI resources, 1/a.a.';
(Ù!) The inverse ofthe SPT efliciency, 1/EoIIo for each conversion device;
• The relative magoitudes ofthe weigbting factors are proportional 10 the tariffs.
5 In tbis case an the natural resoun:es have a weigbting factor of 1/0:", with the c:xccption of
the hydroe1cctricresoun:cwbc:re it is given by 1.6Uaa,...
• Exergetic Optimal Regional Planning 157
Table 6.17 Surnmary ofcases studied in regional planning.
Tl EObjective (%) (%)Function
QB ON RE QB ON RE"
(i) liED 42.7 38.7 40.5 34.6 31.5 32.9
(ri) lIEolI & lIexa 64.2 56.3 56.7 47.8 34.9 34.1
(w) liED & lIexa· 60.8 56.3 55.1 48.7 34.9 34.5
(iv) Min"R 1 60.8 1 56.3 1 55.1 1 48.7 34.9 34.5., RE 15 the rcgJon formcd by the proVInces Québec and Ontario.
t The upper bound base case limits for the provincial states are dcscribcd in Table 6.10.• Exccpt bydro rcsourccs, ô/a.... ô =1.61.
(iv) The coefficients for the minimUffi ; solution are also shawn in column 4 for
comparison.•
Table 6.16 shows, for each type, the corresponding weighting factors ofthe states in bath
provinces. Analysing Table 6.16, please note that:
(i) The assumed weighting factors for the first 12 states are the same for the first three
objective functions tested. The twe1ve first states correspond ta the end-use devices,
as defined in Table 6.2;
•
(ri) Among the end-uses, tr..crlon with an efficient motor bas the sma11er weighting factor,
1.2, whi1e inefficient lightiog the highest one 131.9. That is, the ~-of-use tariif for
inefficient lighting is the highest while, that ofthe efficient motor is the lowest;
(w) In the minimum exergy solution, column four, a1l natural resources (13, 14,23,24,
25) are weighted equally.
• Exergetic Optimal Regional Planning 158
•
•
(iv) For the type (m), object.ve function note that aIl the end-uses devices have higher
weighting fuctors than the natuIë'1 resources, with the exception ofthe traction re1ated
end-uses (states, 9, 10). This indicates that the end-use devices should he charged
relatively more than the natura1 resources. The pœfelled tarifffor the traction end-use
makes sense within the context of the exergetic tariffs since the traction end-use is
100% exergy ~nd sk-::uid then he rewarded.
Table 6.17 summarizes the FPT and SPT efficiencies for the three types oftariffs as weil as
the minimum "R optimal solution. As shown previously in Table 6.8 the objective function (m)
above, produces the identical resu1ts as the minimization of the exergetic resources. This
indieates that the optimal solution achieved by minimizing the exergetic consumption at the
natura1 resources leve1 could be achieved by assigning tariffs proportional to the weights for
eacb ofthe end-use devices and naturaI resources.
0.4 Condudîng Remarks
This chapter had presented a series of simulation resu1ts on the optimum planning of a
regional energy system composed ofthe Canadian provinces ofQuébec and Ontario. The
system had been redesigned by minimizing ofthe total energetic or exergetic consumption at
the naturaI resources leve!. These optimum designs are then compared with eacb other and
with the existing 1995 system.
Mede! for regional planning
The general en~/exergy mode1 described in previous chapters was applied to this regional
planning study. This study encompasses five types of naturaI resources ( hydre, nuclear,
petroleum, naturaI gas and coal) and five types ofend-uses ( space heating, cooking, water
• Exergetic Optimal Regional Planning 159
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•
heating, traction and lighting). In addition, the most common end-use devices such as: power
plants, refineries, efficient motors, heat-pumps, Iighting were considered by this mode!.
Estimation ofend-uses
An estimation of realistic model parameters, in particular the provincial end-uses was
perfonned. A1though this estimation is approximate, it is based on observed end-use patterns,
on published data and is representative ofthe rea1 system.
Estimation ofstate upper bound stlIt<:s' limits
An estimation ofthe Iimits for each ofthe states was performed. This estimation was based
on the variations ofthe assumed 1995 values.
Optimization studies
A series ofoptimal regional planning studies was performed. Two main objective functions
were used, that is, the minimization ofthe energetic and the exergetic resources at the system
1eveI. The importance ofexexgetic optimiZlltion is emphasized throughout the chapter. It was
demonstrated that the optimization performed on the basis ofthe First Principle aIone does
not usua11y maYimize the exergetic resources in a multiple end-use and naturaI resources
constrained case.
Exergy conservation
It was argued that the exergy conservation is, in general, more important than the energy
conservation, since exergy is the measure ofthe avai1able work, in a given process or source
ofenergy. Exergy encompasses a measure ofquality of .le energy use, and should al least
he regarded equa1ly together with energy in regional planning.
Influence ofQuébec-Ontario transmissio~ line capacity
The influence ofincreasing the capacity of the transmission line connecting the two provinces
• Exergetic Optimal Regional Planning 160
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•
was tested. It is shown that the ideal transmission line capacity is different (almost double)
if the objective funetion for optimization purposes is changed from minimum exergy to
minimum energy consumption at the resource leve1. Thus, the minimum exergy solution
requires a lower investment in transmission lines.
Major differences between minimum e:s.ergy and 1995 cases
The adoption of a minimum exergy solution was compared to the 1995 energy/exergy
consumption leveis. It was noted that all available exergetically efficient end-use devices were
pan ofthe optimal solution. This implies a switch to direct heating fumaces, efficient motors
and Iighting to supply the end-use demand. On the other hand, options such e\ectric baseboard
and, eleetric water heating were not chosen by the optimization procedure. It is also
interesting to note that no nuclear, oil, coal or natura! gas power-plants were necessary for
both provinces in the minimum exergy case. It was shown that the adoption of the
minimization of the exergetic resources will save approximate\y 23% of the 1995 energy
consumption or ncarly 10,000 MW ofthermoelectric generation.
Realiz&bility of minimum e:s.ergy solution
The results ofoptimizing the system by minimizing the exergy al the natura\ resource level
should he seen as a long term goal rather than a plan ofaction to be implemented in the short
tenD. Some ofthe changes stipuIated by the minimum exergy solution such as the shut down
ofnuclear power plants and thermoelectric systems involve additional economic, politica\ and
social considerations outside the scope ofthis thesis.
Sensitivity analysis
A sensitivity ana1ysis was perlbrmed by the examinarion ofthe Lagtange multipliers ca\culate.l
in the optimization process. This ana\ysis allows the energy planner to rank the relative
incrernenta1 impact ofincreasing the hmits ofthe outputs ofthe various end-use devices in the
overa\l SPT or FPT efficiencies. The sensitivity ana\ysis showed that the relaxation on the
• Exergetic Optimal Regional Planning 161
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•
end-use device limits is incrementally, a more efficient measure than the relaxation of the
hydro resourees in Ontario or the increase in the transmission line limit connecting Québec
te Ontario. However, it is known that the relaxation on some ofthe upper bounds limits is not
a simple task when compared to the increase ofthe ù"3llSIlÙssion line levels connecting the
two neighbouring systems.
Type-of-use tariffs
It is demonstrated that it is possible to achieve the minimum exergy solution by the proper
choice of the weighting factors in the objective function. The weighting factors are
proportional to the inverse ofthe Second Principle efficiency for end-use deviees and to the
inverse ofthe fraction ofavaiIable work (exergy) for natura1 resources. The weighting factors
are rationaIized as type-of-use tariffs. It is believed that type-of-use tariffs might be
implemented in steps starting, for example, with only two or three categories such as heat
re1ated and non heat related loads. As metering technologies and other regu1ation constraints
permit, other type-of-use categories could be implemented. This is anaIogous to migrating
!Tom time-of-use, with only two periods to hourly spot priees. The main motivation for
introducing a type-of-use tariff is to force the system to maximize its overaII exergetic
efficiency.
Implications of type-of-use tarilTs in the economic sectors
The impact ofthe ad~ption oftype-of-use tariffs in the diffèrent economic sectors will resuIt
in an overaII smaIIer tariffburden to those sectors already using traction as a major end-use.
This is the case in the industrial sector as opposed to residentiaI and commercial sectors.
Changïng the planning scope
It is important to point out that the overaII SPT efficiency could be substailtially increased by
other means than the ones mentioned above. This would be possible, for example, ifother
types ofend-uses such as the end-use road transportation could be suppIied massiveIy by
• Ex-.=rgetic Optimal Regional Planning 162
•
•
e1ectric traction. Ifthis were done ",ithout changing substantially the generation limits, then
part of the end-uses devices must change to more exergetically efficient alternatives and at
the same rime re1ease sorne electric power.
•
•
•
Conclusions and Recommendations for Future Research
Chapter 7. Conclusions and
Recommendations for Future Research
7.1 General Conclusion
This thesis bas presented a system apprcaeh fOi" the planning of e1ectric energy systems
inc\uding a new peispedÏVe, name1y, the consideration of system efficiency as measured not
only by the more commonly used FIISt Principle ofThermodynamics but, aIso, by the Second
Principle ofThermodynamics. It is shown that the extension ofthe efficiency criterion to
include the Second Principle would result in important changes in the way e1ectric energy
systems are designed and operated.
7:J. Specitic Conclusions
This thesis bas extended the knowledge of planning ofe1ectric enp.!"gy systems through the
following contributions:
163
• Conclusions and Recommer.dations for Future Research
(1) Exergetie ana1ysis in the eontext oflntegrated Resource Planning;
164
•
•
(2) Development ofan energetie and exergetie general model for the design and ana1ysis
ofelectrie energy systems;
(3) Demonstration ofthe impact ofexergetie considerations on the planning process of
electrie energy systems;
(4) Integration ofenergetie, exergetie and economie ana1ysis;
(5) Energetie and exergetie regional optimization study;
(6) A proposition of a new kind of electrie rate, type-oj-use tariffs, that incorporate
exergetie considerations.
The specifie conclusions are now det3i1ed reported in the same order as above.
7.2.1 Exergetic anaIysis in the context ofIntegrated Resource Planning.
Exergetie analysis is extremely helpful to achieve one of the most diflicult objectives of
Integmted Resource Planning whieh is the rational matching ofresources and end-uses. The
term end-use does not describe the kWh consumed by a load but, rather, its useful output or
its service. The rational matching of resources and end-uses is possible becanse one can
interpret exergetie efliciency as a measure ofthe quality ofuse ofa given naturaI resource.
Exergetie analysis then, provides the energy p1anner with a very important perspective that
incorporates bath energy use and quaIity ofthis use in a quantitative way. This thesis argues
that exergy coDSelVlltion is, in general, more important than energy conservation :iÎDce exergy
measures avaiIable work in a given process or source ofenergy. Thus, in general, te perform
the planning ofenergy sYstems rationally, it becomes essential to explicitly include exergy in
• Conclusions and Recommendations for Future Research 165
•
•
the objective function ofa design problem. At least exergy shou1d be regarded on an equal
footing with energy in the lntegrated Resource Planning process.
7..2.2 Development ofan energetic and exergetic general model for the
design and analysis of electric energy systems.
A model was developed to descnoe the general energetic and exergetic interconnection
relationships among the three main constituent parts of an electric energy system (natura!
resources, energy conversion processes and end-uses). The model pennits the classification
ofthe mains system parts into classes. For example, one Sl!ch class is composed ofthe various
types of space heating devices (e.g., baseboard, heat-pump air-to-air, central oil-fired
fumace). The end-uses, considered the independent variables of the model, cao also be
classified by sectors (residential, commercial, industrial or institutional).
The principal advantages ofthis model are to:
(a) Provide flexibility to study and design a broad spectrum of electric energy system
scenarios ofvarying size and complexity. This fie:xibiIity was provided through a user
ftiendly software environment;
(b) Simulate system planning scenarios based on different perspectives such as: energy,
exergy, cost or combinations ofthese;
(c) Optimize system designs, energetically or exergetically;
(d) Design tariffs that induce systems to he more exergetically efficient.
• Conclusions and Recommendations for Future Research 166
•
•
7.2.3 Demonstration of the impact of exergetic considerations on the
planning process ofdectric energy ~'Ystems.
The :JPplication ofthe exergetic anaIysis in the electric energy systems was tested i., different
cases, namely:
(i) The ana1ysis of the main electric energy system end-uses. (a) space heating, (b)
cooking, (c) water heating, (d) traction, (e) lighting. This ana1ysis was performed for
different system cvnfigurations including the following naturaI resource options:
hydraulic potentiaI, nuclear energy, petroleum, coal and naturaI gas. The limiting
values of FPT and SPT efficiencies were calcu1ated for the most representative
combinations ofend-uses and naturaI resources;
(ü) The e.U:lgetiC and exergetic impact ofperformance improvement (PI) measures at the
residential sector of electric power systems was investigated at different levels,
namely, the electric appliance being improved, the eustomer, the electric and gas/oil
utilities and the overall natural resources. Such PI measures include the introduction
ofmore efficient e1ectrica1 app1iances, water-heaters or light bulbs. Special attention
is devoted to the influence ofheat-gains due to CToss-effects on heating and cooling
loads.
(iü) The energetic and exergetic impact ofa major adoption of eleetric vehicles (EV) in
the Canada energy system was investigated. Different scenarios were evaluated to
sinndat'.l the increased electric demand due to the adoption ofEV technology. These
scenarios inc1ude variations on the system load filetor and changes in the electric load,
including the adoption ofmore efficient energetica11y and exergetica11y space heating
alternatives. The amount ofpetroleum that would be disp1aced ifEY were adoptee!,
as we11 as the demand to build new powergenerationuuitswere evaluated. Simulation
ofthe simu1taneous adoption ofEY and more exergetica11y efficient ~heating
devices was performed. It was shown that the need to bui1d new e1ectric energy
• Conclusions and Recommendations for Future Research 167
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•
generation fàcilities is nonexistent for most of the Canadian provinces ifa fraction of
the space heating loads were converted to direct oil/gas space heating fumaces (e.g.,
27"10 for Québec) or to more efficient options ofspace heating.
7.2.4 Integration ofenergetic, exergetic and economic analysis.
The integration of energetic, exergetic and economic analysis was performed for a space
heating system with four different alternatives: electric baseboard, ground-to-air heat-pump,
air-to-air heat-pump and direct fossi! fuel heating. The design was based on the minimization
ofthe energetic or exergetic consumption at the natura! resource level and the cost to the
customer as weIl as combinations ofthese fàctors.
In order to ensure that the system design corresponds to the minimum exergy solution, it was
hypothesized here that the given energy end-uses will be met by those alternatives that
minimize the cost to the customers. In other words, the end-users of energy will tend to
choose the cheapest alternatives according to their Iifetime costs.
Thus, different cost incentives were tested, for three different regions, that is New Yorlc,
Québec and Ontario, in order for the minimum exergy and minimum cost solutions to be
identical. The costs' incentives studied were subsidies in the initial capital cost investment,
opportunity cost rate and the energy tariffs. Although the minimum exergy solution couid be
achieved with different combinations ofsubsidies, those involving only subsidies related to
capital investments appear to be easier to implement.
• Conclusions and Recommendations for Future Research
7.2.5 Energetic and exergetic regïonal optimization studies.
168
•
•
A series ofsimulation was carnee! out on the optimum planning ofa regional energy system
composee! ofthe Canadian provinces ofQuébec and Ontario. The system was ree!esignee! by
minimizing the total energetic or exergetic consumption at the natural resources level. These
optimum designs are then comparee! with each other and with the existing 1995 system.
This study encompasses five types ofnatural resources ( hydre, nuclear, petroleum, natural
gas and coal) and five types ofend-uses ( space heating, cooking, water heating, traction and
lighting), as we11 as sorne intermedia%e conversion processes such as: power plants, refineries
and energy transportation and transmission systems.
A series ofoptimal regional planning studies was performee!. Two main objective funetions
were usee!, that is, the minimization ofthe energetic and the exergetic resources at the system
level. It was demonstratee! that the optimization performee! on the basis ofthe Fast Principle
alone does not in general maximize the exergetic resources in a multiple end-use and naturaI
resources constrainee! case.
The influence ofincreasing the capacity ofthe transmission line connecting the two provinces
was testee!. It is shown that the ideal transmission line capacity is different (aImost double)
if the objective funetion for optimi7Jltion purposes is changee! from minimum exergy to
minimum energy consumption at the resource level. Thus, the minimum exergy solution
requires a lower investment in transtnission lines.
The adoption of a minimum exergy solution was comparee! to the 1995 energy/exergy
consumption Ievels. It was notee! that ail available e:œrgetically efficient end-use devices were
part ofthe optimal solution. This implies a switch to direct heating fumaces, efficient motors
and Iighting to supply the end-use demand. On the other hand, options such as e1ectric
• Conclusions and Recommendations for Future Research 169
•
•
baseboard and, electric water heaters were not chosen by the optimization procedure. It is
aIso interesting to note!hat no nuc1ear, oil, coal or natura! gas power-plants were necessary
for both provinces in the minimum exergy case. It was shown that the adoption of the
minimization ofthe exergetic resources wouid save approximately 23% ofthe 1995 energy
consumption or nearly of 10,000 MW ofthermoelectricity generation.
The resuIts ofoptimizing the system by minimizing the exergy at the natura! resource level
shouid he seen as a long term goal rather!han a plan ofaction to be implemented in the short
term.
A sensitivity analysis was petformed by the examination ofthe Lagrange muitipliers caIculated
in the optimization process. T1üs analysis a:Jows the ellergy planner to rank the relative
incremental impact ofincreasing the Iimits ofthe outputs ofthe various end-use devices in the
overaIl SPT or FPT efficiencies. The sensitivity analysis showed !hat the relaxation on the
end-use device Iimits is incrementally, a more efficient measure !han the relaxation ofthe
hydro resources in Ontario or the increase in the transmission line Iimit connecting Québec
to Ontario. However, it is known !hat the relaxation on some ofthe upper bounds is not a
simple task when compared to the increase ofthe transmission line levels connecting the two
neighbouring systems.
It is important to point out that the overaIl SPT efficiency couid he substantially increased by
other means !han the ones mentioned above. T1üs wouid he possible, for example, ifother
types ofend-uses such as the end-use road transportation couid he supplied massively by
electric traetïon. Ifthis were done without changing substantially the generation Iimits, then
part ofthe end-uses devices must change to more exergetically efficient alternatives and al
the same lime release some electric power.
• Conclusions and Recommendations for Future Research 170
•
•
7.2.6 A proposition of a new kind of e1ectric rate, type-of-use tariffs,
that incorporate exergetic considerations.
This thesis discusses a proposition ofa type oftariffbased on the type-of-use, as opposed to
ilie more common time-oj-use tariflS. The main motivation for introducing type-oj-use tariffs
is to force the system to maximize ifs 0vera1l exergetic efliciency. Simulations were performed
to test different tariffstructures to accomplish tlùs objective in the regional planning basis.
It was demonstrated that it is possible to achieve the minimum exergy solution by the proper
choice of the weighting factors in the objective function. The weighting factors are
proportional to the inverse ofthe Second Principle efficiency for end-use deviees and to the
inverse ofthe fraction ofavailable wade (exergy) for natura! resourees. The weighting factors
are rationalized as type-oj-use tariffs. It is believed tbat type-oj-use tariffs might be
implemented in steps starting, for example, with ooly two or tbree categories such as heat
related and non heat related loads. As metering technologies and other resulation constraints
permit, other type-oj-use categories could he implemented. This is analogous to migrating
from time-oj-use, with ooly two periods, to hourly spot priees. The main motivation for
introducing a type-of-use tariff is to force the system to maximize its overall exergetic
efficiency.
The impact ofthe adoption oftype-oj-use tariffs in the different economic sectors will result
in an 0vera1l smaller tariffburden to those sectors aIready using traction as a major end-use.
This is the case in the industrial sector as opposed to residential and commercial sectors.
• Conclusions and Recommendations for Future Research
7.3 Recommendations for Future Work
• Exergetic analysis and Integrated Resources Planning (IRP)
171
•
The scope ofelectric energy plamùng should as much as possible encompasses other loads
not usua\Iy considered 50ch as the end-use road transportation.
Som~ ofthe changes srlpulated by the minimum exergy solution such as the declined use of
nuclear power plants and thermoe1ectric systems involve additional economic, politica\ and
social considerations which must be carefully analysed.
The relationship exergetic :malysis and environmental concerns must be further studied. The
general public should be made aware about the relevance of exergetic analysis in energy
systems.
• End-use forecast by economic sectors
The load forecast needs to be performed in terms of end-uses for each of the economic
sectors (residential, commercial and industrial). Today, for the most part, only the residential
sector's forecasts are performed in terms ofend-uses. The commercial and industrial sectors'
forecasts have net been ana\ysed according to their end-use, but rather in terms ofthe energy
consumption oftheir 5Ob-sectors.
• Tests oftype-of-use tarilTs
Simulations ofthe influence ofthe adoption of type-of-use tarifiS are required in order to
fuIIy comprehend their impact in the patterns ofenergy consumption and their influence and
he1p the system te become more exergetically efficient. Different type-of-use schemes should
• Conclusions and Recommendations for Future Research 172
•
•
he tested including different end-use sets such as heat-related-loads, traction and Iighting. The
simulations of type-oj-use must involve evaluations by ecollOmiC sector such as industrial,
commercial and residential. Certainly a pilot ccperience with type-oj-use tariffs will shed more
light into its relevance and practicality for inducing exergetically more efficient systems.
•
•
•
References
References
Almeida, K. C., (1994), A General Parametric Optimal Power Flow, Department of
Electrical Engineering, McGill University, PbD thesis, 299 p. Montréal, Québec, Canada.
Alvarez, C., Be1enguer, E. (1993), "Object Oriented Environment for Distribution
Applications", llth Power Systems Computation Conference, Volume 1, pp. 155-161,
Avignon, France, September.
Amann, C. A, 1990, "Technical Options for Energy Conservation and Controlling
Environmental Impact in Highway Vehic1es", Conference on Energy and the Environment
in the 2Ist Century, Massachusetts Institute ofTechnology, Cambridge, March.
Asano, H., Sagai, S., Imamnra, E., Ito, K., Yokoyama, R (1992), "Impacts ofTune-of-Use
Rates on the Optimal Sizing and Operation of Cogeneration Systems", IEEE Power
Engineering Society, 92 WM 132-1 PWRS, W"mter Meeting.
Asano, H. (1989), "Demand-Side Management by Real-Tune Pricing for Electric Power
173
• References
Service", Energy Systems Management, Japan, pp. 257-262.
174
•
Baldick, R, Kaye, R. J., Wu, F. F. (1992), "Electricity Tariffs Under Imperfect Knowledge
ofParticipant Benefits", IEEE Transactions on Power Systems, Volume 7, No. 4, November,
pp. 1471-1482.
Bejan , A (1988), AdvancedEngineering Thrermodynamies, Wùey, New York.
Benie, T. W. (1983), Power System Economies, Institute ofEiectrical Engineers, Engiand.
Bleviss, D. L. (1988), The New Oil Crisis andFuel Economy Technologies, Quorum Books,
New York, USA
Boustead, 1., Hanecek, G. F. (1979), Handhook ofIndustriaI Energy Analysis, John Wùey
& Sons, New York.
Broehl, J. H. (1987), "An End Use Approach to Demand Forecasting", LoadManagement,
The Institute ofEiectrie and Electronie Engineers Press, New York, pp. 1I7-121.
Bussmann, W. V. (1990), "Potential Gains in Fuel Economy, a Statistical Analysis of
Technologies Embodied in Model Year 1988 and 1989 Cars", paper presented at the
Cor.frrence on Energy and the Environment in the 21st Century, Massachusetts Institute of
Tecbnology, Cambridge, USA, March.
Canada, Energy Mines and Natural Resources, (1992), EIeetric Power in Canada 1992, p.
176.
Canada, Statistics (1994), Quarterly&port on &ergySupply-Demandin Canada.
• References 175
•
•
Canadian Eleetric Association, (1992), The 1992 Canadian Uti/iry Trade Al/y Symposium,
Cassanti, W. A, Esteves Jr., L. (1990), Experiencia Pi/ota Tarifa Amarela. (pilot Experience
Yellow Tarifi), IEEE The First International Conference on Power Distribution, (in
Portuguese), Belo Horizonte, Brazil.
Charetter, A, Bellemare, R., Angers, P. (1994), "Représentativité de L'Efficacité Déclarée
des Moteurs à Induction et son Incidence sur L'Analyse de Rentabilité", Canadian Electric
Association, Toronto, March.
Clark, E. L. (1986), "Cogeneration - Efficient Energy Source", Annual Review Energy,
Volume 11, pp 275-294.
Crouse, W. L., Anglian, D. L. (1987), Automotive Mechanics, McGraw Hill, pp. 123-33.
DeCicco, J., Ross, M (1994), "Improving Automotive Efficiency", Scientific American,
December, pp. 52-57.
Difligio, C., Duleep, K G. , Greene , D. L. (1992), Energy: An International Journal,
Volume Il, No. 65.op. cited by Wang & DeLuchi (1992).
Dillon, T. S., Chang, E. (1993), "Application of the Object-Oriented Approach to Power
Systems Problems", IIth Power System Computation Conference, Volume 1., Avignon,
France, pp. 21-30.
Eleetric Power Research Institute, (1986), "Impact of Rate Structure on Demand-Side
Management Programs", EPRI Report EM-479I, Volume 1, Phase 1, September.
• References 176
•
Eleetrie Power Researeh Institute, (1990), "Industrial Load Shaping- an Application of
Demand-Side Management", EPRJ Report CU-6726, Volume. 1, May.
E1ectrie Power Research Institute, (1992), "Prototype Expert System for Load Management",
EPRJ Report 1R-J00732, Volume 1, July.
Endrenyi, J. (1978), ReliabilityModeling in Electric Power Systems, John WJ1ey & Sons.
Fisher, J. C. (1974), Energy Crises in Perspective, WJ1ey & Sons.
Gardner, D. T. & Robinson, J. B. (1993), "To Wbat End ? A Conceptual Framework for the
Analysis ofEnergy Use", Energy Studies Review, Volume 5, No. l, Canada
GeIbard, E., Li, C. (1993), "1992 Residential Seetor End-Use Forecast", Main Report,
Ontario Hydro, Toronto.
GeIlings, C. W. (1993), "Saving Energy with Electricity", Energy Engineering, Volume 90,
No. 2, pp. 6-25.
Gensym Corporation, (1992), G2 Reference ManuaI, Version 3.0, Cambridge,
Massachusetts, July.
Gtace, A., (1992), Optimiza1ion ToolboxforusewithMatlab, The MathWorks Ine., USA.
Henriques, D. (1992), "Promoting a New Energy Etbie for British Columbia", Proceedings
XII International Unionfor Eleetroheat, Montréal, Québec, pp. 541-546.
• Hirst, E. (1992), "A Good Integrated Resource Plan: Guidelines for E1ectrie Uti1ities and
• References 177
•
ReguIators", Oak Ridge Tennessee: Oak Ridge National Laboratory. December, Op. citOO
by Rosen et al. 1992.
Hobbs, B. F., Rouse, H. B. , Hoog, D. T. (1993), "Measuring the Economie Value of
Demand-Side and Supply Resources in IntegratOO Resouree Planning Models", IEEE
Transactions on Power Systems, Volume 8, No.3, August. pp. 979-987.
HoIman, J. P. (1980), Thermodynamics, 3rd. 00., McGraw Hill, New York.
H~ébec (1993), Forecast E/eetricityDemand in Québec - Development Plan, Volume
6, p. 172.
Kaminslà, T., Grier, D. (1994), "Heat Pump R&D Needs for Canadian Conditions",
Canadian E/ectrica/ Association, Toronto, Match.
Kaygusuz, K, Ayhan, T. (1993), "Exergy Analysis ofSolar-Assistoo Heat-Pump Systems for
DomestieHeating", Energy:The International Journal, Volume 18, No.10, pp. 1077-1085.
Klenke, W. (1991), "UsefuI Work, Exergy and Thermodynamie Potentia!s", International
Chemica/ Engineering, Volume 31, No. 4, Oetober, pp. 654-660.
Krenz, J. H.(1980), Energyfrom Opulence to Sufftciency, Praeger.
LaFranee, G., Hudon , M (1992), "The Impact of Environmentai Externalities on the
Penetration of Electrotechnologies", XII Congress International Union for EIeCtToheat,
Montréal, Québec, Canada, June, pp. 783-790
• LaFrance, G. (1995), "Les Fondements d'une Politique Énergétique", Semïnar Presented st
• References
Public Dehate on Energy in Québec, May, Montréal, Canada.
178
•
•
Laperriere, A, McGugan, C. (1994) "Technological Advances in Electric Water Heaters",
Canadian Electric Association, Toronto, Canada
Latorre, C. O. F., Nobre E. C., Burgoa C. A (1989), "Diagn6stico do Potencial de
Conservaçào de Energia na IndUstria (Diagnosis ofthe Energy Conservation Potential on the
Industria1 Sector)", IEEE The First International Conference on Power Distribution, Belo
Horizonte, Brazil, (m Portuguese) p.S.
Litchfield, J.; Hemingway, L. , Raph2ls, P. (1994), "Integrated Resource Planning and the
Great Whale Public Review", Baclcground Paper, No.7, The Great Whale Public Review
Support Office, Montréal, Québec, Canada.
Low, S. (1993), "1992 Industrial Sector End-Use Forecast", Main Report, Ontario Hydro,
Toronto, 1993.
Lozano, M. A, Valero, A (1993), "Theory ofEnergetic Cost", Energy: an Intemational
Journal, No. 9, Volume 18.
McGonegal, W. (1992a), "Conceptor G-Van Electric Vehic1e Testing", Enviromnent
Canada, November.
McGonegal, W. (1992b), "Bedford Griffon Electric Vehic1e Testing", Enviromnent Canada,
July.
McGonegal, W. (1993), "Volta Electric Vehic1e", Enviromnent Canada, January.
• References 179
•
•
McGonegal, W. (1995), Mobile Source Emission Centre, Environment Canada. Ottawa,
(persona! commUIÙcation).
McGovem, 1. A (199Oa), "Exergy Analysis- a Different Perspective on Energy, Part 1: The
Concept ofExergoj', Proceedings ofthe Imtitute ofMechanical Engineers, Volume 24, pp.
253-262.
McGovem, J. A (1990b), "Exergy Analysis- a Different Perspective on Energy, Pan 2:
Rationa! Efficiency and sorne Examples ofExergy Analysis", Proceedings ofthe Institute of
Mechanical Engineers, Volume 24, pp. 263-268.
Maxwell, J. C. (1871), Theory ofBeat, }"" ed., Longmans Green: London.
Melero, 1. R L. (1993), Short Term AnaIysisofElectrical Energy Markets Under Real Time
Pricing. Master Thesis, Massachusetts Institute ofTechnology, 124 p., Massachusetts, USA
Minick, M R, Runnels, J.E. (1987), "Load Management Assessment- an Dil Buming
Utility's Perspective", LoadManagement, IEEE, pp. 155-161.
Moreau, A, Stricker S. (1994), "Assessment ofthe Impact ofInternal Heat Gains on The
Thermal Loads in the Residential Sector", Electricity 1994, (Toronto: Canadian Electrical
Association) p. 19.
Nakiéenovié, N., Grübler, A (1993), "Energy Conversion, Conservation and Efficiency",
Energy: an International Jourrv:zl, Volume 18, No.s, pp. 421-435.
NieuwJaar, E. (1993), "Exergy Evaluation of Space-Heating Options", Energy:The
InternationaIJourrv:zl. Volume 18., No.7, pp. 779-790.
--
• References 180
•
•
Northwest Power Planning Council, (1991), Northwest Conservation and Electric Power
Plan, Volume I, April, Washington, USA
Northwest Power Plan Council, (1991), Northwest Conservation andElectric Power Plan,
Volume fi, Part 1, Washington, USA
Northwest Power Plan Council, (1991), Northwest Conservation andE/ectric Power Plan,
Volume fi, Part fi, Washington, USA
Oliveira F., D., Galiana F. D. (1995a) "AModel forthe Planning ofElectric Energy Systems.
Including Energetic Considerations", The Institute ofE/ectrica/ andE/ectronic Engineers
Power Industry Computer Applications Conference, May, Utah, pp. 539-546.
Oliveira F., D., Galiana F. D. (199Sb), "System-Wide Energetic and Energetic Analysis of
perfonnance Improvement Strategies Including Cross-Effects", paper submitted to Energy
Studies Review, March.
Oliveira F., D., GrJiana F. D. (1995c), "Electric Energy System Planning and the Second
Principle ofThermodynamics", Encyclopaedia ofLife Support Systems - Water, Energy,
Environment, Food and Agriculture, Ministery ofEnergy and Natura1 Resources, Abu Dhab~
UAE, June.
Parent, D., Châtigny, R (1994), "Comparative Field Testing and Cyc\ing Monitoring of
Residentiai Air Source Heat Pump", Canadian E/eetrica/ Association, March, Toronto,
Canada, p. 22.
PerIman. M, Moore, G. (1991), "On-site Generation Through Waste Heat RecoveIY",
Canadian E/ectrica/Association, No. 890I-U-762, Montréal, Québec, Canada
• References 181
•
Pinheiro, S. F. (1989), "Col15e1Vaçào de Energia Elétrica- Recurso Energético Planificave!",
(E1ectric Energy Conservation - Resource that can be Planned), I Congresso Brasileiro de
PlanejamenJo Energético, (m Portuguese), May, Volume 3, pp. 95-108., Campinas. Brazil.
Québec Govemment, (1992a) "Energy in Qu8ec 1992", Ministère de l'Énergie et des
Resources, Canada.
Québec Government, (1992b), "Forecast Electricity Demand in Québec, Development Plan
for 1993", Volume 6, Montréal, Québec, Canada.
Québec, (1192), L'Évolution de lA Demande D'Énergie Finale au Québec Scénario 1991
2011, Ministere de l'Énergie et des Ressources du Québec.
Québec, Government o~ (1995a), Final Report Committee ofExperts and Information. 20
p., Montréal, Québec, Canada, May.
Québec, Govemment o~ (1995b), "Implantation au Québec de la Planificacion Intégrée des
Resources", Montréal, Québec, Canada.
Rabi V. A (1991), "The Opportunity in DSM", EJectric Power Research Institute Journal,
OetoberlNovember, pp.4-15.
Rosen, R A (1992), "Evaluation ofEnergy Utilization Efficiency in Canada Using Energy
and Exergy Analyses", Energy: an International Journal, Volume 17, No.4.
Rosen, R A, Kroll, H., Nichols, D., Talbolt, N., Wulsberg K. (1993), "IRP Concepts and
Approaches", Tellus Institute - Hydro-Québec, September, Québec, Canada
• References 182
•
Rosen, R A, Nichols, D., Talbot, N., KroIl, H.L., Shapiro, L. (1993), "Electric IRP in North
America", Tel/us Institute & Hydro-Québec, Boston pA3.
Ross, M., DeCicco, 1. (1994), "Measuring the Energy Drain on Your Car", Scientific
American, December, pp. 112-115.
Runnels, 1., Whyte, D. (1985), "Evaluation ofDemand-Side Management", Proceedings of
the IEEE, Volume 73, No.10, October.
Sears, P. W., Zemansky, M W. (1953), University Physics, Adissan Wesley, Cambridge,
Massachusetts.
Society of Automotive Engineers, (1990), "Fuel Economy Measurement Raad Test",
Procedure SAE 11082, Hantlbook Engines, Fuels, Lubricants, Emissions and Noise, pp.
24.206-24.216.
Society ofAutomotive Engineers, (1993), "E1ectric Vehicle Energy Consumption and Range
Test Procedure", SAE J 1634.
Society ofAutomotive Engineers, (1992), "Passenger Cars, Trucks, Buses and Motorcycles",
SAE Hantlbook On-Highway Vehides & Ofj-HighwayMachinery, Procedure SAE 11082,
pp. 24.206-24.216.
Sorensen, H. A (1983), Energy Conservation Systems, John Wiley & Sons, pp. 386-389.
StoIl, H. G. (1989), Least-eost EIectric UtiIity Planning, John Wiley & Sons.
• Talukdar, S., Gellings C. W. (1987), "Load Management Concepts", LoadManagemi!m,
• References
IEEE, pp. 3-29.
183
•
•
The Engineering Society for Advancing Mobility Land Sea Air and Space, (1992). Halldhook
1992. On-Highways Vehic/es & Off-High Machinery, "Electric Vehicle Test Procedure
Society ofAutomotive Engineers J227a", Volume 4, pp. 28.01-28.06.
Unnewehr, L. E., Nasar, S. A (1982), Electric Vehicle Technology, Wùey & Sons, New
York, USA
Wang, Q., DeLuchi, M. A, (1992), "Impact of Electric Vehicles on primary Energy
Consumption and Petroleum Displacement", Energy: an International Journal. Volume 17,
No 4, pp. 351-366.
Wepfer, W. J. (1979), Application ofthe SecondLaw to the Analysis andDesign ofEnergy
Systems, PhD thesis, University ofWisconsin Madison.
Zhu, J. L., Lodola 1. C. (1993), "1992 Commercial Seetor End-Use Forecast", Main Report,
Ontario HYŒO, Toromo, CmuWa
•
•
First and Second Principle Efficie:1cies for Different System Configurations
AppendixA.
First and Second Principle Efficiencies for
Different System Configurations
184
• First and Second Principle Efficiencies for Different System Configurations
Table Al. FPT efficiency, TJ, ofend-use devices for various system configurations (%).
185
•
•
1
End-use device [ Oil
1Gas
1
Coal [ Nuclear [ Hydro
1
1. Space heating fumace 57.2 57.2 57.2 n.a n.a.
2. Baseboard 31.0 31.7 31.4 31.4 87.4
3. Heat-pump air-to-air 52.7 53.9 53.3 53.3 148.6
4. Heat-pump ground-to-air 79.4 81.1 80.3 80.3 223.7
5. Direct coolàng fumace 33.7 33.7 33.7 n.a n.a.
6. E1ectric cooking 15.8 16.2 16.0 16.0 44.6
7. Direct water-heating fumace 40.8 40.8 40.8 n.a n.a.
8. Electric water-heating 26.7 27.2 27.0 27.0 75.2
9. Efficient motor 24.8 25.3 25.1 25.1 69.9
10. Inefficient motor 18.6 19.0 18.8 18.8 52.4
11. Inefficient lighting 1.9 1.9 1.9 1.9 5.2
12. Efficient lighting 6.2 6.3 6.3 6.3 17.5
• First and Second Principle Efficiencies for Different System Configurations
Table A2. SPT efficiency, €, ofend-use deviees for various system configurations (%).
186
•
•'"
End-use Deviee Oil Gas Coal Nuclear Hydro
1. Space heating fumace 3.9 3.9 3.9 n.a. n.a.
2. Baseboard 2.1 2.1 2.1 2.1 2.5
3. Heat-pump air-to-air 3.6 3.6 3.6 3.6 4.2
4. Heat-pump ground-to-air 5.4 5.5 5.4 5.4 6.4,
'.5. Direct cooking furnace 10.1 10.1 10.1 n.a. n.a.
6. Electric cooking 4.8 4.9 4.8 4.8 5.6
7. Direct water-heating fumace 8.2 8.2 8.2 n.a. n.a.
8. Electric water-heating 5.3 5.5 5.4 5.4 6.3
9. Efficient motor 62.0 63.4 62.7 62.7 73.6
10. Inefiicient motor 46.5 47.5 47.0 47.0 55.2
11. Inefiicient lighting 0.2 0.2 0.2 0.2 0.3
12. Efficient Iighting 2.3 2.4 2.4 2.4 2.8
•
•
•
Energetic and Exergetic Savings at DifferentSystem Levels for DSM Performance Improvement
Appendix B.
Energetic and Exergetic Savings at
Different System Levels for
DSM Performance Improvement
(i) Efficient electric water heater (Tables B.I and B.2);
(ii) Replacement of incandescent by compactfluorescent Iight bulbs (Tables B.3 and BA).
187
• Energetic and Exergetic Savings at DifferentSystem Levels for DSM Performance Improvement
188
•
•
Table BI. Energetic savings at different system levels for PI 'Efficient Electric WaterHeater'.
Energy savingsin equivalent kWblyear/customer
ConfigurationAppliancc Cooling Spacc DweUing E1cetric Gas/Oil Net
Hcoting Uli1ity Uli1ity ResourccSnvings
CI 438 36 -287 187 219 0 219
C2 438 36 -96 378 443 0 443
C3 438 36 -355 119 555 -401 154
C4 438 36 -287 187 631 0 631
CS 438 36 -96 378 1278 0 1278
C6 438 36 -355 119 1600 -401 1199
Table B.2 Exergetic savings at different system levels for PI 'Efficient Electric Water Heater'.
Exergysavingsin equivalent kWblyear/customer
PmfigurationNet
Appliancc CoolingSpacc
DweUingE1cetric Gas/Oil
ResourccHcating Uli1ity Uli1itySnvings
CI 416 34 -273 177 208 0 208
C2 416 34 -91 359 421 0 421
C3 416 34 -BI 319 527 -148 379
C4 416 34 -273 177 233 0 233
CS 416 34 -91 359 473 0 473
C6 416 34 -131 319 592 -148 444
• Energetic and Exergetic Savings at DifferentSystem Levels for DSM Performance Improvement
189
•
Table B.3. Energetic savings for PI 'Replacement ofIncandescent by Compact FluorescentLight Bulbs'.
Energy savingsin cquivalcnt kWhlycar/customcr
ConfigullltionGas/Cil Net
Appliancc CoolingSpacc
Dwclling E1cctric Utilily RcsourccHcating Utilily Savings
Cl 51S 40 -322 236 276 0 276
C2 51S 40 ·107 451 527 0 527
C3 51S 40 -397 161 653 -454 19S
C4 51S 40 ·322 236 g06 0 S06
C5 51S 40 -107 451 1539 0 1539
C6 51S 40 -397 161 1905 -454 1451
Table B.4 Exergetic savings for PI 'Replacement ofIncandescent by Compact FluorescentLight Bulbs'.
Energy savingsin cquivalcnt kWhlycar/customcr
ConfigurationGas/o.1 Net
Appliancc CooUng SpaccDwcIIing
ElcctricUtilily Rcsourcc
Hcatin8 Utilily Savinga
CI 493 38 -306 22S 263 0 263
C2 493 38 -lm 429 501 0 SOI
C3 493 38 -147 384 6.."0 -168 452
C4 493 38 ·306 22S 298 0 298
cs 493 38 -102 429 569 0 569
C6 493 38 ·147 384 705 ·168 S37
•
•
•
Estimation of the End-uses for Ontario and Québec in 1995
Appendix C.
Estimation of the End-uses for
Ontario and Québec in 1995
190
• Estimation of the End-uses for Ontario and Québec in 1995 191
C.l Ontario End-uses
C.l.l Space-heating end-use in Ontario
The end-use space heating for Ontario was calculated considering that:
(i) The space heating alternative non-forced air was considered to have the efficiency of
the e\ectric baseboard,
(ü) The proportion of the different space heating alternatives in the commercial and
industrial sectors were assumed to be the same as the residential sectors.
Table C.l Energy consumption for the space heating end-use devices in Ontario, 1995.
Non-Direct Hc:lt Hc:lt-
forccdoiVgas Pump pump Totll1
Scctor air air- ground-Oil Gas to-air to-air
Encrgy supplicd, 7066 9167 36782 415 130 53560GWh
Eflicicncyt, % 100 73 73 170 256 78l. Residential
End-use, GWh 7066 6692 26851 623 333 41565% 17 16 65 2 1 100
Encrgy supplicd, 3920 19626 1450 115 23 25134GWh
2. CommcrciaI 3920 14327 1058 196 59 19599End-use, GWh% 20 73 5 1 0 100
Encrgy supplicd, 5322 26648 1969 157 31 34127GWh
3. Industria1 5322 19453 1437 266 80 26558End-use, GWh% 20 73 5 1 0 100
. . .t for the hcat pumps the cfliClcncy IS the cocfliClent-of-pcrformance.Sourcc::(Gclbard & Li 1993ab; Zhu & Lodola, 1993a,b,Low, 1993ab].
•
• Estimation of the End-uses for Ontario and Québec in 1995 192
C.l.2 Cooking end-use in Ontario
The end-use cooking for Ontario was calculated considering that:
(i) The energy conversion device nùcrowave was considered together with electric
ranges,
(ii) The end-use cooking at the industriai sectcr was Cl),1SÏdered to be 50% ofthe food
and beverage industriai sector electric demand.
Table C2 Energy consumption for the cooking end-use devices in Ontario, 1995.
Sector Electric Direct GasTotalCookinll:
Energy1771 195
1966supplied, GWh
1. Residentiai Efficiency, % 51 43 50
End-use, GWh 903 84 987
% 91.3 8.7 100.0
Energy881 1357
2238supplied, GWh
2. Commercial449 584 1033End-use, GWh
% 44 57 100
Energy 1068 1644 2712supplied, GWh
3. Industriai544 707 1252End-use, GWh
% 44 57 100.Sourcc:[GcIbard& Li, 199300; Law 1993ab; Zhu & Lodola, 1993ab].
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• Estimation of the End-uses for Ontario and Québec in 1995 193
C.l.3 Water heating end-use in Ontario
Table C.3 Energy consumption for the water-heating end-use devices in Ontario, 1995.
Sector Electric Direct Oil orTotalGas heating
Energy supplied, GWh 5392 14589 19981
Efficiency, % 86 52 611. Residential
End-use, GWh 4610 7586 12196%
38 62 100
Energy suppliee!, GWh 1405 3777 5182
2. Commercial End-use, GWh 1201 1964 3165%
38 62 100.Soun:c:[GcIb:llÙ & Li, 1993ab; Zhu & Lodola, 1993ab].•
C.l.4 Lighting end-use in Ontario
The end-use lighting for Ontario was calculated considering that:
(i) The inefficient and efficient lighting energy conversion devices were considered to be
alternatives such as incandescent and fluorescent or lighting respectively.
(u) The proportion the efficient and inefficient lighting energy conversion devices in the
industrial sector were considered to be the same as in the commercial sector.
•
Estimation of the End-uses for Ontario and Québec in 1995 194
Table C.4 Energy consumption for the lighting end-use devices in Ontario, 1995.
1Sector
1Inefficient
1
Efficient1
Total1Lighting Lighting
Energy supplied, GWh 4622 370 4992
Efficiency, % 6 20 71. Residential
End-use, GWh 259 75 334
% 77 23 100
Energy supplied, GWh 6807 7475 14282
2. Commercial End-use, GWh 381 1525 1906
% 20 80 100
Energy supplied, GWh 281 1848 2129
3. Industrial End-use, GWh 16 377 393
% 4 96 100.SOIl1'CC:[Gclbard & Li, 1993ab; Zhu & Lodola, 1993ab; Low, 1993ab].•
• Estimation of the End-uses for Ontario and Québec in 1995 195
C.l.5 Traction end-use in Ontario
The end-use traction for Ontario was caIculated considering that:
(i) The efficiency and proportion of the efficient and inefficient motor for each ofthe
sectors were assumed;
(ù) The proportion the efficient and inefficient lighting energy conversion devices in the
industrial sector were considered to be the same as in the commercial sector.
Table C.S Energy consomption for traction end-use devices in Ontario, 1995.
1Sector
1
Inefficient1
Efficient1
Total1motors motors
Energy suppliee!, GWh 6161 4369 10530
Efficiency, % 65 75 691. Residential
End-use, GWh 72824005 3277
% 55 45 100
Energy suppliee!, GWh 10156 6094 16250
Efficiency, % 72 80 752. Commercial
End-use, GWh 121887313 4875
% 60 40 100
Energy suppliee!, GWh 8772 31145 39917
Efficiency, % 79 89 873.Industrial
End-use, GWh 346496930 27719
% 20 80 100.Sourcc:[Gclbard & Li, 1993ab; Zhu & Lodola, 1993ab; Law, 1993ab).
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• Estimation of the End-uses for Ontario and Québec in 1995
C.2 Québec End-uses
196
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•
Sï.'1ce the efficiency ofthe typica1 energy conversion device for the different end-use was not
available for the province of Québec, then the correspondent values of the province of
Ontario were assumed, for the Tables C.6 to C.IO.
<:2.1 Space heating end-use in Québec
Table C.6 Energy consomption for space heating end-use devices in Québec, 1995.
Non- Direct Beat Beat- Totalforced oiVgas Pmnp pump
Scclor air air- ground-OiJ Gas to-air to-air
Energy supplicd, GWh 22978 4342 6512 336 87 34254
Efficicncy'. % 100 73 73 170 2S6 931. Rcsidcntial
End-use, GWh 22978 3169 4754 5n 222 31694
% 73 10 15 2 1 100
Energy supplicd, GWh 8173 . 15806 5598 99 28 29704
2.Commcrciai End-use, GWh 8173 11538 4086 168 72 24038
% 34 48 17 1 0 100
Energy supplicd, GWh 5711 11045 3912 69 20 20757
3. Industrial End-use, GWh 5711 8063 2856 118 50 16798%
34 48 17 1 0 100t for the heat pomps 1he cflictency IS the eocfIiClent-of-performance.Souree:(SlatislcsCanada. 1994; Québec 1993; Québec. 1995].
C2.2 Cooking end-use in Québec
The avaiIable data for the end-use cooking for the province of Québec do not include,
explicitly, data for the commercial and industria1 sectors. For this reason, Table C.7 presents
• Estimation of the End-uses for Ontario and Québec in 1995 197
data for cooking only for the residential seetor.
Table C.7 Energy consumption for the cooking end-use devices for the residential sector in
Québec, 1995.
1Item L~leetric
1Gas
1Total
1
Energy supplied, GWh 1261 5 1266
Residential Efficiency, % 51 43 51
SeetorEnd-use, GWh 643 2 645
% 99.7 0.3 100.0..So=:[St:lUSl1cs Canada, 1994;Qucbec: 1993; Qucbec, 1995].
• C2.3 Water heating end-use in Québec.
Table C.S Energy consumption for the water heating end-use devices, for the residential andcommercial seetors in Québec, 1995.
Direct
Item Eleetric oiVgas Total
Oil Gas
Energy supplied, GWh 9000 1973 2960 13933
Efficiencyt, % 86 52 52. 741. Residential
End-use, GWh 7695 1026 1539 10260%
10075 10 15
Energy supplied, GWh 1800 4059 1438 7296
2. Commercial E".1d-use, GWh 1539 2111 748 4397%
35 48 17 100. .t for the hcat pumps the efiiCtCDCY IS the coefiiCtCDt-of-perfonn:mcc.Souroe:[Statistics Canada, 1994;Québec: 1993; Québec, 1995].•
• Estimation of the End-uses for Ontario and Québec in 1995 198
C.2.4 Lighting end-use for Québec in 1995.
Table C.9 Energy consumption for the Iighting end-use in Québec, 1995.
ItemInefficient Efficient TotalLighting Lighting
Energy supplied, GWh 3951 317 4268
Efficiency, % 6 20 71. Residential
End-use, GWh 221 65 286%
77 23 100
Energy supplied, GWh 3433 3769 7202
2. Commercial End-use, GWh 192 769 961%
20 80 100
Energy suppliee!, GWh 233 1532 1764
3. Industrial End-use, GWh 13 312 325%
4 96 100. . .Sourcc:[StatJstics Canada, 1994;Qucbcc 1993; Qucbcc, 1995).
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• Estimation of the End-uses for Ontario and Québec in 1995 199
C.2.5 Traction end-use for Québec in 1995.
Table C.IO Energy consumption for traction end-use devices in Québec, 1995.
SectorInefficient Efficient
TotalMotors Motors
Energy supplied, GWh 4335 3074 7408
Efficiency, % 65 75 691. Residential
End-use, GWh 2817 2305 5123
% 55 45 100
Energy supplied, GWh 8284 4970 13254
Efficiency, % 72 80 752. Commercial
End-use, GWh 5964 3976 9941
% 60 40 100
Energy supplied, GWh 27705 16395 44100
Efficiency, % 79 89 833. Industrial
End-use, GWh 21887 14591 36479
% 20 80 100. . . .Sourcc:[Statisbcs Canada, 1994;Qucbec 1993; Qucbcc, 1995].
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