A case study of a commercialresidential microgrid integrating cogeneration and electrical local users

Luigi Martirano (Senior Member IEEE) Serena Fornari

Electrical Engineering Department University of Rome ldquoSapienzardquo

Rome Italy martiranouniroma1it

Alessandro Di Giorgio Francesco Liberati Department of Computer Control and Management

Engineering University of Rome ldquoSapienzardquo

Rome Italy digiorgioliberatidisuniroma1it

AbstractmdashEuropean energetic policy aims to complete the liberalization market process and to improve a rational use of energy promoting strongly lsquoNearly Zero-Energy Buildingsrsquo NZEB and the use of highly efficient cogeneration CHP also for residentialofficecommercial buildings NZEB means a building that has a very high energy performance and the very low amount of energy required should be covered to a very significant extent by energy from renewable sources including CHP The actual promotion of renewable energies and distributed generation obliges to review the traditional ldquoload-drivenrdquo ldquotop-downrdquo power system Electric demand side management (DSM) focuses on changing the electricity consumption patterns of end-use customers through improving energy efficiency and optimizing allocation of power Demand response (DR) is a DSM solution that targets residential and commercial customers and is developed for demand reduction or demand shifting at a specific time for a specific duration Renewable power and CHP systems can be sized and managed more efficiently for loads of tens of kVA more than an individual consumer So it is necessary for small and medium consumers to aggregate their load profile in order to reach a threshold value of some ten of kW and a more demand flexibility like the Heating System where a unique boiler supplies more efficiently the building The actual regulatory rules donrsquot permit the aggregation of consumers in a unique Point of Delivery POD The paper presents a case study of a microgrid arranged for a complex of two commercialresidential buildings in order to overcome the regulatory barrier mentioned and propose a load management strategy aimed at controlling the power withdrawal at the POD The authors suggest the ecodesign of the residential and commercial low voltage distribution like a microgrid allows to guarantee a reduced impact as ever net load on the net supply at least in a first evolution

I INTRODUCTION Buildings account for 40 of total energy consumption in

the European Union EU [12345] The sector is expanding which is bound to increase its energy consumption Therefore reduction of energy consumption and the use of energy from renewable sources in the buildings sector constitute important measures needed to reduce the Unionrsquos energy dependency

and greenhouse gas emissions It is necessary to lay down more concrete actions with a view to achieving the great unrealised potential for energy savings in buildings and reducing the large differences between Member Statesrsquo results in this sector Buildings have an impact on long-term energy consumption Given the long renovation cycle for existing buildings new and existing buildings that are subject to major renovation should therefore meet minimum energy performance requirements adapted to the local climate As the application of alternative energy supply systems is not generally explored to its full potential alternative energy supply systems should be considered for new buildings regardless of their size pursuant to the principle of first ensuring that energy needs for heating and cooling are reduced to cost-optimal levels In the last years the EU has actively promoted the liberalization of the electricity markets extended to all the customers small and residential included and also political campaigns towards energy efficiency and renewable energies

A European Directive (Directive 201031EC) [6] promotes strongly the construction of lsquoNearly Zero-Energy Buildingsrsquo NZEB NZEB means a building that has a very high energy performance and the very low amount of energy required should be covered to a very significant extent by energy from renewable sources including CHP Another European Directive (Directive 20048EC of the European Parliament and of the Council of 11 February 2004 [4]) promotes strongly the use of high efficient cogeneration CHP also for residentialofficecommercial buildings

Renewable power and CHP systems can be sized and managed more efficiently for loads of tens of kVA more than a small individual consumer So it is necessary for small and medium consumers to aggregate their load profile in order to reach a threshold value of some ten of kW and a more flexibility The aggregation of different kind of load profiles like residential tertiary commercial night time cinemas etc allows to obtain a more virtuous squared profile and to manage and control the profile by load shedding activities that for individual consumers are impossible

978-1-4673-3059-613$3100 copy2013 IEEE

Moreover the Heating System in buildings is sized and managed more efficiently with a unique boiler and a common distribution system But the actual regulatory laws donrsquot permit the aggregation of different consumers in a unique Point of Delivery POD

II THE POWER SYSTEM OF THE FUTURE NEARLY ZERO-ENERGY BUILDINGS AND MICRO

COGENERATION Currently small and medium consumers (residential and

small tertiary loads) are supplied by the public utility through a Common Distribution System CDS with an independent POD for each consumer

Todayrsquos distribution system for LV customers appears inadequate to comply with the liberalization and energetic goals of the European Policy (CHP and NZEB) as mentioned in the previous paragraph

The proliferation of small distributed generation systems in the territory and the prospected development of new uses of electricity (as that related to charging of electric vehicles and hybrid) is taking a radical paradigm shift in the design and management of electrical systems

Architecture top-down which saw the power of multiple distributed loads on territory with the work of a few large generating plants operating in the logic of load following has to change toward a greater integration between energy sources and uses (smartgrids) The distribution power system is now in a position of being unable to accept the full range of sampling or injection by entities linked to it otherwise poor performance of the power system itself In an effort to meet the needs of programmable profiles imposed by the new network codes and to observe a behavior perceived as virtuous (square edge) from the system each consumer is called internally to identify appropriate control variables that allow opportunities for more effective interfacing with the electrical system

Main goals both economic (complete liberalization of the electricity market) and technical as the introduction of CHP also for residential buildings and the development of NZEBs need to recognize the constitution of union of small customers supplied by a same network node

The building or a group of buildings represents the natural limit of the aggregation like in the Heating System The aggregation of the consumers gravitates around an electric node (MVLV substation) in a common microgrid in order to reach up the threshold value of some ten of kVA and to get a more virtuous and flexible cumulative load profile

The microgrid needs the assistance of a common Building Automation and Control System BACS to manage and control the loads and the generation and to meter the consumptions

The best management of the system follows the rule to minimize the electric power exchange with the utility Directive approach seems to follow the rule of yearly energy exchange privileging the ldquoverticalrdquo operation The proposed approach allows both energeticeconomic and electricalsafetyquality goals

The microgrid for the building allows to install renewable energy power plants as solar PV modules or CHP systems (cogeneration) or CCHP systems (trigeneration) for a common service (Figure 1) The BACS organizing a collaborative and more efficient controlled load shedding complying with the benefit of the customers bunch toward free uses or more convenient costs allows to organize an effective Demand Side Management

The suggested microgrid allows to pursuit also electricalsafetyquality goals The most important is the possible adoption of safer grounding solutions for urban area (like IEC TN-systems)

Common renewable energy power plants by C(C)HP can be sized more efficiently for a customers bunch aiming to guarantee the internal consume of the whole production A common power plant permits a unique general meter reducing interface maintenance and operation problems

Customer aggregations reduce the number of single consumers and facilitate to electric utilities the possibility for innovative activities such as power control monitoring and detection of fraudulent customers

A network of advanced meters continuously tracks all utilities and monitor equipment conditions The software helps find and sustain energy savings accurately allocate or sub-bill costs optimize multi-site utility contracts and maximize reliability

They are available integrated solutions that by managing energy data furnish performance indicators analysis and control tools to cut energy and maintenance costs without compromising the comfort or productivity of the service

Intelligent management of energy efficiency optimizing costs and quality requires imagination that can reveal opportunities expose risks and support strategic decision making

The design of a C(C)HP has to be based on the heatcooling demand and its operation has to follow the

Figure 1 Prospected evolution of a microgrid supplying a NZEB

with a unique POD

PV HVAC

ELEVATORS

EGSC(C)HP

Bunch of customers

MVLDS

coolingheating load profile (thermal driven) Organizing a customers bunch with an electrical energy demand of at least 100 kVA or more guarantees a base load of some ten of kW

Acceptable operation of C(C)HP systems are for more hours daily of the base load demand at least 50 of its rating power during the higher cost time interval of the day A good minimum value of equivalent operation hours at maximum power is higher than a third of a year In a same loads area customers bunches combining shedable load demand of residential customers with night-time profile and load demand of commercial customers with day-time profile allows to balance the two complementary components

III LOAD PROFILE CONTROL FOR MICROGRIDS IN NEARLY ZERO-ENERGY BUILDINGS

Traditionally the building connected to the power system does not require any form of forecast of its energy needs or of the energy surplus compared with standard consumption required from the grid The proliferation of small distributed generation systems in the territory largely related to the development of renewable energy sources or cogeneration that require close proximity to final energy users is causing a radical paradigm shift in the design and management of electrical systems

Loads can be classified in a natural way as

bull Uncontrollable loads loads for which it is not possible to implement any control strategy such as the timing or maintain the absorption power within thresholds These loads depend on the habits of the occupants

bull Plannable loads loads for which it is possible to implement a control strategy such as choosing the starting time providing a delay in the start of the cycle and ensuring the closure of the cycle without interruption (eg household appliances)

bull Controllable load loads for which it is possible to provide both a time delay in starting the cycle and it can be switched onoff without damage and degradation of consumer quality of experience (eg boilers for hot water)

A key point to achieve control of the NZEB is the design of a proper load management strategy acting at BACS level Starting from the fact that loads currently used in households have different controllability degrees and future white appliances will be designed to be more flexible in terms of programs management a control algorithm is here presented and shown to be efficient for the fulfillment of a set of requirements related to the NZEB electricity consumption

The functional requirements FRs taken here as reference can be summarized as follows

FR1 CHP exploitation The BACS has to manage the loads in such a way to maximize the self-consumption from CHP at NZEB level

FR2 Flattering the power withdrawal at POD The BACS has to manage the loads so as to achieve a constant or piece-wise constant power withdrawal at POD level avoiding peaks and providing valley filling in the load profile

FR3 Reverse flow avoidance Due to the presence of the CHP in the architecture which has a thermal driven behavior it is not guaranteed that the NZEB will behave as a passive microgrid at all the times The BACS has to manage the loads in order to allow the power consumption to exceed the internal generation

FR4 Meeting user needs The BACS has to manage the loads in respect of consumer preferences and habits inside the building exploiting in the best way their different levels of flexibility

FR5 Reaction to Demand Side Management messages The BACS has to react to DSM requests from grid and market actors by providing a re-profiling service at POD level The nature of the request and the related economic aspects depend on the specific contract established for the provisioning of the power supply service

In order to meet all the FRs the following real time strategy is proposed As previously mentioned the load can be classified in three groups for which different actions are taken but all of them share a common feature each load is activated as a consequence of a consumer action which takes place in an asynchronous way with respect to the others in an uncontrolled scenario the resulting aggregated load profile depends on the power profile of each load and the timing in the sequence of requests

Now we assume that each time a consumer asks for the execution of a household appliance program or the heating process of the water in a boiler a request triggers the BACS which solves an optimization problem The output of the optimization task is given by a delayed start time for the appliance generating the request and the other ones still waiting for starting and finally the control for active boilers in the NZEB The decision taken is sent to the loads which are responsible for actuation

The optimality of control is lost every time a new request triggers the controller when it happens the optimization problem is updated and solved keeping the control optimal over the time This methodology has been investigated in the context of residential load management [12][13][14] and electromobility [15] and is referred as Event Driven Model Predictive Control

Figure 2 Load diagram for a standard

The mathematical formulation of the optidepends on the FRs Here we are mainly exploiting CHP and provide a desired aggreat POD level For this reason the problemfollows

BACS load management problem Forpower reference Pref(t) to be followed at thehousehold appliances with power profile pa

activation delay ∆tak a set of M boilers wi

pbm(t) demanded energy for water heating ∆

heating period ∆tbm solve

min Λ [P(u)-Pref]infin

where infin is the linfin norm defined in representing the maximum value of the atime) P(u) is the aggregated power withdrawis the control applied to the appliances and a proper weight diagonal matrix

If Pref is properly chosen it can be showcontrol u which results from the solution omanagement problem allows to meet all thintroduced in particular by choosing Pref

constant time sequence the controller will msuch a way as to minimize the displacemwithdrawal from a piece-wise constant behav

The optimization problem can be handlediscrete time framework using standard mreader is referred to [13][15])

IV AN EXAMPLE OF A COMMERCIALCOMMON MICROGRID INTEGR

COGENERATION AND ELECTRICAL LCASE STUDY

The paper presents a real case study energy building NZEB with a micro cogenerlinked to the main LV Power Center An innwith a unique POD is considered with the Mowned by the building According to the regupossible to consider also the traditional eledifferent PODs and with the substation owne

d unit Figure 3 Load profile for

imization problem interested in best

egated load profile m can be stated as

r a given time t a e POD a set of K a

k(t) and maximum ith nominal power ∆Eb

n and maximum

real space (here rgument over the wal at the POD u the boilers and Λ

wn that the optimal of the BACS load he FRs previously f as a piece-wise

manage the loads in ment of the power vior at POD level

ed and solved in a methodologies (the

L RESIDENTIAL RATING LOCAL USERS

of a nearly zero-ration CHP system novative microgrid MVLV substation ulatory barrier it is ectric service with ed and operated by

the distributor The building cunits common areas parking g

In order to estimate powerresidential units are subdivided

bull Economy

bull Standard with air condpower for lighting and

bull Luxury with air condmore power for lighting

Each unit is equipped with

The load profile is differentconsidering a singlecouple bsons behaviour

In Figure 2 is shown the loa

In the case study they are family behaviour (7 economy35 with a couple behaviour (1luxury) The individual units energy of about 300 MWhMWhyear for each unit

The heating system for rabout 400 MWh for year Thebuild an aggregate of the totarepresented the balance at thoperation in a winter day anstrategy

The system is completed consisting in a Turbec T100 miThe microturbine furnishes 10167 kW of thermal power con(about 35 m3h) with a total eff

Considering a thermal drivwith 2000 hoursyear of fugenerated by CHP is about 200consumption is of 300 MWhyearly consumption is 400MW

the building in a winter day

consists in 70 residentialoffice gardens etc

r energy and load profiles the d in 3 typologies

ditioned for one room and more washing machines

ditioned for all the rooms and g washing and dryer machines

electric boilers for hot water

tiated for the residential units by behaviour and a family with

ad diagram for a Standard Unit

considered 70 units 35 with a 19 standard and 9 luxury) and

17 economy 8 standard and 10 IU use an amount of electrical

hyear equivalent to about 6

residentialtertiary units spends authors prepared a tool able to

al load diagram In Figure 3 is he POD considering the CHP nd not considering any control

by a 100 kVA CHP system icroturbine natural gas powered 00 kW of electricity power and nsuming 350 kW of gas power ficiency of 78

ven management of the system ull power the yearly energy 0 MWh of electricity (the yearly h) and 340 MWh of heat (the

Wh)

Figure 4 Power balance at POD

The aggregation of individual appliance demand so as to produce an individual household demand profile is achievable by pressing the button Load Diagram present in the Output panel of interface GUI

The import of values with which to make the load charts is by reading an excel The excel file becomes the source of the program with the possibility of being changed by the user The file contains for each unit the following functions

Total power absorbed by uncontrollable loads sum sum [W]

Total power absorbed by controllable loads sum sum [W]

Total power absorbed by plannable loads sum sum [W]

Where

N is the number of uncontrollable loads

M is the number of controllable loads

K is the number of plannable loads

Piuc is the daily profile of the ith uncontrollable load It is a vector of 96 values where each value is for 15 minutes

PTiuc is the nominal power of the ith uncontrollable load

cuiuc is the coefficient of utilization of the ith uncontrollable load It is a vector of 96 values

piuc is the a vector of 96 values that indicates the activation of the ith load

The same method can be used for controllable and plannable loads The aggregation of the load shapes of various households so as to derive the end-use area load profile is realized by a vector time with which to make the time shift loads of single unit The time vector is based on a Gaussian distribution having zero mean and with a variance such that the probability of occurrence of a displacement of the loads over 4 hour is less than 1

The objective of the optimization of controllable and plannable loads is to make the profile of the electric load of the total units as flat in order to be able to exploit the electric power generated by a CHP

Figure 4 shows a comparison between the ldquoopen looprdquo balance at POD (ie without any control) and the closed loop balance at POD deriving from the implementation of the proposed control strategy The tracking of a proper power reference allows to achieve a balance which is more regular with respect to the non-controlled case Reverse power flow is significantly reduced although not completely eliminated (that depends on the constraints on power-shifting imposed by the user preferences which the control algorithm has to satisfy) A piece-wise constant power reference is chosen which is built on the base of the average power consumed in the day by the whole residentialcommercial complex the CHP profile and taking into account the portion of the load profile which

cannot be shifted (the non-controllable power) In particular from 1000 to 2200 the power reference must be chosen greater than the CHP electric rate in order to steer the system towards zero reverse power flow The resulting net power exchange only approximates (see figure 4) a piece-wise constant function because the control system is constrained by the presence of user preferences and non-controllable loads Finally we avoided choosing to much ldquothighrdquo user preferences for load shifting in such a way as to show the effectiveness and the potentialities of the proposed control algorithm (we chose a 15 minutes maximum delay for user sensitive loads -eg the 10 liters kitchen boiler- and 5 hours maximum delay for less user sensitive loads -eg the washing machine and the 5080 liters boilers-)

V CONCLUSIONS The paper presents a case study of a microgrid for a

lsquoNearly Zero-Energy Buildingrsquo NZEB The authors suggest the ecodesign of the residential and commercial low voltage distribution for the next future that allows to accomplish the goals of the NZEBs To avoid future chaotic phenomena in the existing distribution network the power flow of local generators has to be maintained local the users have to remain net-loads organized in Ever Net-Load Microgrids The actual distribution network for low voltage customers appears inadequate to comply with these improvements and it has to recognize the constitution of microgrids as union of Customers Groups The suggested microgrid allows to enhance safety high local power quality future dc distribution systems common emergency systems efficient load shedding actual maintenance service energy management and allows to guarantee a reduced impact as ever net load on the net supply

REFERENCES [1] Directive 9692EC of the European Parliament and of the Council

of 19 December 1996 concerning common rules for the internal market in electricity

[2] Directive 200177EC of the European Parliament and of the Council of 27 September 2001 on the promotion of electricity produced from renewable energy sources in the internal electricity market

[3] Directive 200291EC of the European Parliament and of the Council of 16 December 2002 on the energy performance of buildings EPBD

[4] Directive 20048EC of the European Parliament and of the Council of 11 February 2004 on the promotion of cogeneration based on a useful heat demand in the internal energy market

[5] Directive 200532CE of the European Parliament and of the Council of 6 July 2005 on the ecodesign requirements for energy-using products

[6] Directive 201031EC of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings

[7] G Parise L Martirano Prospected evolution for low voltage customers ecodesign of the electrical distribution system Industry Applications Society Annual Meeting 2008 IEEE-IAS 08 Edmonton Alberta Canada 5-9 October 2008

[8] D W Zipse The hazardous multigrounded neutral distribution system and dangerous stray currents PCIC 03

[9] G Parise L Martirano M Mitolo TN-Island Grounding System and the House of the Future 2006 41st IAS Annual Meeting 8-12 October 2006

[10] G Parise L Martirano L Parise Ecodesign of Ever Net-Load Microgrids IEEE Industry Applications Society Annual Meeting 2012 Las Vegas USA

[11] Brenna M Falvo MC Foiadelli F Martirano L Poli D Sustainable Energy Microsystem (SEM) preliminary energy analysis 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) Washington DC USA 16-20 January 2012

[12] Pimpinella L Di Giorgio A Mercurio A ldquoLocal Energy Management System Control Scheme and Loads Modelingrdquo Proc of the 18th Mediterranean Conference on Control and Automation MED10 304ndash308 Marrakech 23-25 June 2010

[13] Di Giorgio A Pimpinella L An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management Applied Energy (Elsevier) Special Issue ldquoSmart Gridsrdquo 96 92-103 (2012)

[14] Di Giorgio A Pimpinella L Liberati F ldquoA model predictive control approach to the load shifting problem in a household equipped with an energy storage unitrdquo Proc of the 20th Mediterranean Conference on Control and Automation MED12rdquo 1491-1498 Barcelona July 2012

[15] Di Giorgio A Liberati F Canale S ldquoIEC 61851 compliant electric vehicle charging control in Smartgridsrdquo 21th Mediterranean Conference on Control and Automation MED13rdquo Chania July 2013

[16] Brenna M Falvo M C Foiadelli F Martirano L Massaro F Poli D Vaccaro A Challenges in energy systems for the smart-cities of the future Energy Conference and Exhibition (ENERGYCON) 2012 IEEE International pp755-762 9-12 September 2012

[17] G Parise L Martirano L Parise M Mitolo Safety Evolution of Residential Microsystems 2nd ENERGYCON Conference amp Exhibition 2012 (Future Energy Grids and Systems Symposium Firenze 9-12 September 2012

Luigi Martirano (StMrsquo98-M02-SM11) was born in Cosenza Italy in 1973 He received the MS and PhD degrees in Electrical Engineering in 1998 and 2003 respectively In 2000 he joined the Department of Electrical Engineering of the University of Rome La Sapienza He is currently a researcher in electrical power systems and assistant professor of Building Automation and Energy Management He has authored more than 60 papers in international journals and conferences and one international patent His research activities cover power systems design planning safety lightings home and building automation energy management He is a senior member of the IEEEIAS member of the AEIT (Italian Association of Electrical and Electronics Engineers) and of the CEI (Italian Electrical Commission) Technical Committees CT205 (Home and Building Electronic Systems) and CT315 (Energy Efficiency) He has been Registered Professional Engineer

Serena Fornari was born in Rome Italy in 1987 She received the Bachelor Degree in 2010 in Energy Engineering and Master Degree with honors in Energy Engineering from the University of Rome ldquoSapienza in January 2013 She discussed a thesis on Analysis and management of electrical loads for domestic buildings Her main interests are in renewable energy systems power management systems and demand side management

Alessandro Di Giorgio was born in Rome in 1980 He received the master degree in Physics in 2005 and the PhD degree in Systems Engineering in 2010 He is currently an Assistant Professor of ldquoAutomatic Controlrdquo with the University of Rome Sapienza His research activity deals with the application of control systems theory to Smart Grids focusing on local energy management systems demand side management wind turbines electromobility interdependencies analysis and powerline communications over distribution grids He has been involved in several Italian and European research projects on these topics Francesco Liberati was born in Rome Italy in 1987 He received a graduate degree cum laude in systems engineering from the University of Rome La Sapienza in 2011 Since January 2010 he has been working at Consortium for the Research in Automation and Telecommunication (CRAT) Rome Italy His research interests include smart grids and critical infrastructure protection He is involved in Italian and European research projects

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Moreover the Heating System in buildings is sized and managed more efficiently with a unique boiler and a common distribution system But the actual regulatory laws donrsquot permit the aggregation of different consumers in a unique Point of Delivery POD

II THE POWER SYSTEM OF THE FUTURE NEARLY ZERO-ENERGY BUILDINGS AND MICRO

COGENERATION Currently small and medium consumers (residential and

small tertiary loads) are supplied by the public utility through a Common Distribution System CDS with an independent POD for each consumer

Todayrsquos distribution system for LV customers appears inadequate to comply with the liberalization and energetic goals of the European Policy (CHP and NZEB) as mentioned in the previous paragraph

The proliferation of small distributed generation systems in the territory and the prospected development of new uses of electricity (as that related to charging of electric vehicles and hybrid) is taking a radical paradigm shift in the design and management of electrical systems

Architecture top-down which saw the power of multiple distributed loads on territory with the work of a few large generating plants operating in the logic of load following has to change toward a greater integration between energy sources and uses (smartgrids) The distribution power system is now in a position of being unable to accept the full range of sampling or injection by entities linked to it otherwise poor performance of the power system itself In an effort to meet the needs of programmable profiles imposed by the new network codes and to observe a behavior perceived as virtuous (square edge) from the system each consumer is called internally to identify appropriate control variables that allow opportunities for more effective interfacing with the electrical system

Main goals both economic (complete liberalization of the electricity market) and technical as the introduction of CHP also for residential buildings and the development of NZEBs need to recognize the constitution of union of small customers supplied by a same network node

The building or a group of buildings represents the natural limit of the aggregation like in the Heating System The aggregation of the consumers gravitates around an electric node (MVLV substation) in a common microgrid in order to reach up the threshold value of some ten of kVA and to get a more virtuous and flexible cumulative load profile

The microgrid needs the assistance of a common Building Automation and Control System BACS to manage and control the loads and the generation and to meter the consumptions

The best management of the system follows the rule to minimize the electric power exchange with the utility Directive approach seems to follow the rule of yearly energy exchange privileging the ldquoverticalrdquo operation The proposed approach allows both energeticeconomic and electricalsafetyquality goals

The microgrid for the building allows to install renewable energy power plants as solar PV modules or CHP systems (cogeneration) or CCHP systems (trigeneration) for a common service (Figure 1) The BACS organizing a collaborative and more efficient controlled load shedding complying with the benefit of the customers bunch toward free uses or more convenient costs allows to organize an effective Demand Side Management

The suggested microgrid allows to pursuit also electricalsafetyquality goals The most important is the possible adoption of safer grounding solutions for urban area (like IEC TN-systems)

Common renewable energy power plants by C(C)HP can be sized more efficiently for a customers bunch aiming to guarantee the internal consume of the whole production A common power plant permits a unique general meter reducing interface maintenance and operation problems

Customer aggregations reduce the number of single consumers and facilitate to electric utilities the possibility for innovative activities such as power control monitoring and detection of fraudulent customers

A network of advanced meters continuously tracks all utilities and monitor equipment conditions The software helps find and sustain energy savings accurately allocate or sub-bill costs optimize multi-site utility contracts and maximize reliability

They are available integrated solutions that by managing energy data furnish performance indicators analysis and control tools to cut energy and maintenance costs without compromising the comfort or productivity of the service

Intelligent management of energy efficiency optimizing costs and quality requires imagination that can reveal opportunities expose risks and support strategic decision making

The design of a C(C)HP has to be based on the heatcooling demand and its operation has to follow the

Figure 1 Prospected evolution of a microgrid supplying a NZEB

with a unique POD

PV HVAC

ELEVATORS

EGSC(C)HP

Bunch of customers

MVLDS

coolingheating load profile (thermal driven) Organizing a customers bunch with an electrical energy demand of at least 100 kVA or more guarantees a base load of some ten of kW

Acceptable operation of C(C)HP systems are for more hours daily of the base load demand at least 50 of its rating power during the higher cost time interval of the day A good minimum value of equivalent operation hours at maximum power is higher than a third of a year In a same loads area customers bunches combining shedable load demand of residential customers with night-time profile and load demand of commercial customers with day-time profile allows to balance the two complementary components

III LOAD PROFILE CONTROL FOR MICROGRIDS IN NEARLY ZERO-ENERGY BUILDINGS

Traditionally the building connected to the power system does not require any form of forecast of its energy needs or of the energy surplus compared with standard consumption required from the grid The proliferation of small distributed generation systems in the territory largely related to the development of renewable energy sources or cogeneration that require close proximity to final energy users is causing a radical paradigm shift in the design and management of electrical systems

Loads can be classified in a natural way as

bull Uncontrollable loads loads for which it is not possible to implement any control strategy such as the timing or maintain the absorption power within thresholds These loads depend on the habits of the occupants

bull Plannable loads loads for which it is possible to implement a control strategy such as choosing the starting time providing a delay in the start of the cycle and ensuring the closure of the cycle without interruption (eg household appliances)

bull Controllable load loads for which it is possible to provide both a time delay in starting the cycle and it can be switched onoff without damage and degradation of consumer quality of experience (eg boilers for hot water)

A key point to achieve control of the NZEB is the design of a proper load management strategy acting at BACS level Starting from the fact that loads currently used in households have different controllability degrees and future white appliances will be designed to be more flexible in terms of programs management a control algorithm is here presented and shown to be efficient for the fulfillment of a set of requirements related to the NZEB electricity consumption

The functional requirements FRs taken here as reference can be summarized as follows

FR1 CHP exploitation The BACS has to manage the loads in such a way to maximize the self-consumption from CHP at NZEB level

FR2 Flattering the power withdrawal at POD The BACS has to manage the loads so as to achieve a constant or piece-wise constant power withdrawal at POD level avoiding peaks and providing valley filling in the load profile

FR3 Reverse flow avoidance Due to the presence of the CHP in the architecture which has a thermal driven behavior it is not guaranteed that the NZEB will behave as a passive microgrid at all the times The BACS has to manage the loads in order to allow the power consumption to exceed the internal generation

FR4 Meeting user needs The BACS has to manage the loads in respect of consumer preferences and habits inside the building exploiting in the best way their different levels of flexibility

FR5 Reaction to Demand Side Management messages The BACS has to react to DSM requests from grid and market actors by providing a re-profiling service at POD level The nature of the request and the related economic aspects depend on the specific contract established for the provisioning of the power supply service

In order to meet all the FRs the following real time strategy is proposed As previously mentioned the load can be classified in three groups for which different actions are taken but all of them share a common feature each load is activated as a consequence of a consumer action which takes place in an asynchronous way with respect to the others in an uncontrolled scenario the resulting aggregated load profile depends on the power profile of each load and the timing in the sequence of requests

Now we assume that each time a consumer asks for the execution of a household appliance program or the heating process of the water in a boiler a request triggers the BACS which solves an optimization problem The output of the optimization task is given by a delayed start time for the appliance generating the request and the other ones still waiting for starting and finally the control for active boilers in the NZEB The decision taken is sent to the loads which are responsible for actuation

The optimality of control is lost every time a new request triggers the controller when it happens the optimization problem is updated and solved keeping the control optimal over the time This methodology has been investigated in the context of residential load management [12][13][14] and electromobility [15] and is referred as Event Driven Model Predictive Control

Figure 2 Load diagram for a standard

The mathematical formulation of the optidepends on the FRs Here we are mainly exploiting CHP and provide a desired aggreat POD level For this reason the problemfollows

BACS load management problem Forpower reference Pref(t) to be followed at thehousehold appliances with power profile pa

activation delay ∆tak a set of M boilers wi

pbm(t) demanded energy for water heating ∆

heating period ∆tbm solve

min Λ [P(u)-Pref]infin

where infin is the linfin norm defined in representing the maximum value of the atime) P(u) is the aggregated power withdrawis the control applied to the appliances and a proper weight diagonal matrix

If Pref is properly chosen it can be showcontrol u which results from the solution omanagement problem allows to meet all thintroduced in particular by choosing Pref

constant time sequence the controller will msuch a way as to minimize the displacemwithdrawal from a piece-wise constant behav

The optimization problem can be handlediscrete time framework using standard mreader is referred to [13][15])

IV AN EXAMPLE OF A COMMERCIALCOMMON MICROGRID INTEGR

COGENERATION AND ELECTRICAL LCASE STUDY

The paper presents a real case study energy building NZEB with a micro cogenerlinked to the main LV Power Center An innwith a unique POD is considered with the Mowned by the building According to the regupossible to consider also the traditional eledifferent PODs and with the substation owne

d unit Figure 3 Load profile for

imization problem interested in best

egated load profile m can be stated as

r a given time t a e POD a set of K a

k(t) and maximum ith nominal power ∆Eb

n and maximum

real space (here rgument over the wal at the POD u the boilers and Λ

wn that the optimal of the BACS load he FRs previously f as a piece-wise

manage the loads in ment of the power vior at POD level

ed and solved in a methodologies (the

L RESIDENTIAL RATING LOCAL USERS

of a nearly zero-ration CHP system novative microgrid MVLV substation ulatory barrier it is ectric service with ed and operated by

the distributor The building cunits common areas parking g

In order to estimate powerresidential units are subdivided

bull Economy

bull Standard with air condpower for lighting and

bull Luxury with air condmore power for lighting

Each unit is equipped with

The load profile is differentconsidering a singlecouple bsons behaviour

In Figure 2 is shown the loa

In the case study they are family behaviour (7 economy35 with a couple behaviour (1luxury) The individual units energy of about 300 MWhMWhyear for each unit

The heating system for rabout 400 MWh for year Thebuild an aggregate of the totarepresented the balance at thoperation in a winter day anstrategy

The system is completed consisting in a Turbec T100 miThe microturbine furnishes 10167 kW of thermal power con(about 35 m3h) with a total eff

Considering a thermal drivwith 2000 hoursyear of fugenerated by CHP is about 200consumption is of 300 MWhyearly consumption is 400MW

the building in a winter day

consists in 70 residentialoffice gardens etc

r energy and load profiles the d in 3 typologies

ditioned for one room and more washing machines

ditioned for all the rooms and g washing and dryer machines

electric boilers for hot water

tiated for the residential units by behaviour and a family with

ad diagram for a Standard Unit

considered 70 units 35 with a 19 standard and 9 luxury) and

17 economy 8 standard and 10 IU use an amount of electrical

hyear equivalent to about 6

residentialtertiary units spends authors prepared a tool able to

al load diagram In Figure 3 is he POD considering the CHP nd not considering any control

by a 100 kVA CHP system icroturbine natural gas powered 00 kW of electricity power and nsuming 350 kW of gas power ficiency of 78

ven management of the system ull power the yearly energy 0 MWh of electricity (the yearly h) and 340 MWh of heat (the

Wh)

Figure 4 Power balance at POD

The aggregation of individual appliance demand so as to produce an individual household demand profile is achievable by pressing the button Load Diagram present in the Output panel of interface GUI

The import of values with which to make the load charts is by reading an excel The excel file becomes the source of the program with the possibility of being changed by the user The file contains for each unit the following functions

Total power absorbed by uncontrollable loads sum sum [W]

Total power absorbed by controllable loads sum sum [W]

Total power absorbed by plannable loads sum sum [W]

Where

N is the number of uncontrollable loads

M is the number of controllable loads

K is the number of plannable loads

Piuc is the daily profile of the ith uncontrollable load It is a vector of 96 values where each value is for 15 minutes

PTiuc is the nominal power of the ith uncontrollable load

cuiuc is the coefficient of utilization of the ith uncontrollable load It is a vector of 96 values

piuc is the a vector of 96 values that indicates the activation of the ith load

The same method can be used for controllable and plannable loads The aggregation of the load shapes of various households so as to derive the end-use area load profile is realized by a vector time with which to make the time shift loads of single unit The time vector is based on a Gaussian distribution having zero mean and with a variance such that the probability of occurrence of a displacement of the loads over 4 hour is less than 1

The objective of the optimization of controllable and plannable loads is to make the profile of the electric load of the total units as flat in order to be able to exploit the electric power generated by a CHP

Figure 4 shows a comparison between the ldquoopen looprdquo balance at POD (ie without any control) and the closed loop balance at POD deriving from the implementation of the proposed control strategy The tracking of a proper power reference allows to achieve a balance which is more regular with respect to the non-controlled case Reverse power flow is significantly reduced although not completely eliminated (that depends on the constraints on power-shifting imposed by the user preferences which the control algorithm has to satisfy) A piece-wise constant power reference is chosen which is built on the base of the average power consumed in the day by the whole residentialcommercial complex the CHP profile and taking into account the portion of the load profile which

cannot be shifted (the non-controllable power) In particular from 1000 to 2200 the power reference must be chosen greater than the CHP electric rate in order to steer the system towards zero reverse power flow The resulting net power exchange only approximates (see figure 4) a piece-wise constant function because the control system is constrained by the presence of user preferences and non-controllable loads Finally we avoided choosing to much ldquothighrdquo user preferences for load shifting in such a way as to show the effectiveness and the potentialities of the proposed control algorithm (we chose a 15 minutes maximum delay for user sensitive loads -eg the 10 liters kitchen boiler- and 5 hours maximum delay for less user sensitive loads -eg the washing machine and the 5080 liters boilers-)

V CONCLUSIONS The paper presents a case study of a microgrid for a

lsquoNearly Zero-Energy Buildingrsquo NZEB The authors suggest the ecodesign of the residential and commercial low voltage distribution for the next future that allows to accomplish the goals of the NZEBs To avoid future chaotic phenomena in the existing distribution network the power flow of local generators has to be maintained local the users have to remain net-loads organized in Ever Net-Load Microgrids The actual distribution network for low voltage customers appears inadequate to comply with these improvements and it has to recognize the constitution of microgrids as union of Customers Groups The suggested microgrid allows to enhance safety high local power quality future dc distribution systems common emergency systems efficient load shedding actual maintenance service energy management and allows to guarantee a reduced impact as ever net load on the net supply

REFERENCES [1] Directive 9692EC of the European Parliament and of the Council

of 19 December 1996 concerning common rules for the internal market in electricity

[2] Directive 200177EC of the European Parliament and of the Council of 27 September 2001 on the promotion of electricity produced from renewable energy sources in the internal electricity market

[3] Directive 200291EC of the European Parliament and of the Council of 16 December 2002 on the energy performance of buildings EPBD

[4] Directive 20048EC of the European Parliament and of the Council of 11 February 2004 on the promotion of cogeneration based on a useful heat demand in the internal energy market

[5] Directive 200532CE of the European Parliament and of the Council of 6 July 2005 on the ecodesign requirements for energy-using products

[6] Directive 201031EC of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings

[7] G Parise L Martirano Prospected evolution for low voltage customers ecodesign of the electrical distribution system Industry Applications Society Annual Meeting 2008 IEEE-IAS 08 Edmonton Alberta Canada 5-9 October 2008

[8] D W Zipse The hazardous multigrounded neutral distribution system and dangerous stray currents PCIC 03

[9] G Parise L Martirano M Mitolo TN-Island Grounding System and the House of the Future 2006 41st IAS Annual Meeting 8-12 October 2006

[10] G Parise L Martirano L Parise Ecodesign of Ever Net-Load Microgrids IEEE Industry Applications Society Annual Meeting 2012 Las Vegas USA

[11] Brenna M Falvo MC Foiadelli F Martirano L Poli D Sustainable Energy Microsystem (SEM) preliminary energy analysis 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) Washington DC USA 16-20 January 2012

[12] Pimpinella L Di Giorgio A Mercurio A ldquoLocal Energy Management System Control Scheme and Loads Modelingrdquo Proc of the 18th Mediterranean Conference on Control and Automation MED10 304ndash308 Marrakech 23-25 June 2010

[13] Di Giorgio A Pimpinella L An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management Applied Energy (Elsevier) Special Issue ldquoSmart Gridsrdquo 96 92-103 (2012)

[14] Di Giorgio A Pimpinella L Liberati F ldquoA model predictive control approach to the load shifting problem in a household equipped with an energy storage unitrdquo Proc of the 20th Mediterranean Conference on Control and Automation MED12rdquo 1491-1498 Barcelona July 2012

[15] Di Giorgio A Liberati F Canale S ldquoIEC 61851 compliant electric vehicle charging control in Smartgridsrdquo 21th Mediterranean Conference on Control and Automation MED13rdquo Chania July 2013

[16] Brenna M Falvo M C Foiadelli F Martirano L Massaro F Poli D Vaccaro A Challenges in energy systems for the smart-cities of the future Energy Conference and Exhibition (ENERGYCON) 2012 IEEE International pp755-762 9-12 September 2012

[17] G Parise L Martirano L Parise M Mitolo Safety Evolution of Residential Microsystems 2nd ENERGYCON Conference amp Exhibition 2012 (Future Energy Grids and Systems Symposium Firenze 9-12 September 2012

Luigi Martirano (StMrsquo98-M02-SM11) was born in Cosenza Italy in 1973 He received the MS and PhD degrees in Electrical Engineering in 1998 and 2003 respectively In 2000 he joined the Department of Electrical Engineering of the University of Rome La Sapienza He is currently a researcher in electrical power systems and assistant professor of Building Automation and Energy Management He has authored more than 60 papers in international journals and conferences and one international patent His research activities cover power systems design planning safety lightings home and building automation energy management He is a senior member of the IEEEIAS member of the AEIT (Italian Association of Electrical and Electronics Engineers) and of the CEI (Italian Electrical Commission) Technical Committees CT205 (Home and Building Electronic Systems) and CT315 (Energy Efficiency) He has been Registered Professional Engineer

Serena Fornari was born in Rome Italy in 1987 She received the Bachelor Degree in 2010 in Energy Engineering and Master Degree with honors in Energy Engineering from the University of Rome ldquoSapienza in January 2013 She discussed a thesis on Analysis and management of electrical loads for domestic buildings Her main interests are in renewable energy systems power management systems and demand side management

Alessandro Di Giorgio was born in Rome in 1980 He received the master degree in Physics in 2005 and the PhD degree in Systems Engineering in 2010 He is currently an Assistant Professor of ldquoAutomatic Controlrdquo with the University of Rome Sapienza His research activity deals with the application of control systems theory to Smart Grids focusing on local energy management systems demand side management wind turbines electromobility interdependencies analysis and powerline communications over distribution grids He has been involved in several Italian and European research projects on these topics Francesco Liberati was born in Rome Italy in 1987 He received a graduate degree cum laude in systems engineering from the University of Rome La Sapienza in 2011 Since January 2010 he has been working at Consortium for the Research in Automation and Telecommunication (CRAT) Rome Italy His research interests include smart grids and critical infrastructure protection He is involved in Italian and European research projects

本文献由ldquo学霸图书馆-文献云下载rdquo收集自网络仅供学习交流使用

学霸图书馆（wwwxuebalibcom）是一个ldquo整合众多图书馆数据库资源

提供一站式文献检索和下载服务rdquo的24 小时在线不限IP

图书馆

图书馆致力于便利促进学习与科研提供最强文献下载服务

图书馆导航

图书馆首页 文献云下载 图书馆入口 外文数据库大全 疑难文献辅助工具

coolingheating load profile (thermal driven) Organizing a customers bunch with an electrical energy demand of at least 100 kVA or more guarantees a base load of some ten of kW

Acceptable operation of C(C)HP systems are for more hours daily of the base load demand at least 50 of its rating power during the higher cost time interval of the day A good minimum value of equivalent operation hours at maximum power is higher than a third of a year In a same loads area customers bunches combining shedable load demand of residential customers with night-time profile and load demand of commercial customers with day-time profile allows to balance the two complementary components

III LOAD PROFILE CONTROL FOR MICROGRIDS IN NEARLY ZERO-ENERGY BUILDINGS

Traditionally the building connected to the power system does not require any form of forecast of its energy needs or of the energy surplus compared with standard consumption required from the grid The proliferation of small distributed generation systems in the territory largely related to the development of renewable energy sources or cogeneration that require close proximity to final energy users is causing a radical paradigm shift in the design and management of electrical systems

Loads can be classified in a natural way as

bull Uncontrollable loads loads for which it is not possible to implement any control strategy such as the timing or maintain the absorption power within thresholds These loads depend on the habits of the occupants

bull Plannable loads loads for which it is possible to implement a control strategy such as choosing the starting time providing a delay in the start of the cycle and ensuring the closure of the cycle without interruption (eg household appliances)

bull Controllable load loads for which it is possible to provide both a time delay in starting the cycle and it can be switched onoff without damage and degradation of consumer quality of experience (eg boilers for hot water)

A key point to achieve control of the NZEB is the design of a proper load management strategy acting at BACS level Starting from the fact that loads currently used in households have different controllability degrees and future white appliances will be designed to be more flexible in terms of programs management a control algorithm is here presented and shown to be efficient for the fulfillment of a set of requirements related to the NZEB electricity consumption

The functional requirements FRs taken here as reference can be summarized as follows

FR1 CHP exploitation The BACS has to manage the loads in such a way to maximize the self-consumption from CHP at NZEB level

FR2 Flattering the power withdrawal at POD The BACS has to manage the loads so as to achieve a constant or piece-wise constant power withdrawal at POD level avoiding peaks and providing valley filling in the load profile

FR3 Reverse flow avoidance Due to the presence of the CHP in the architecture which has a thermal driven behavior it is not guaranteed that the NZEB will behave as a passive microgrid at all the times The BACS has to manage the loads in order to allow the power consumption to exceed the internal generation

FR4 Meeting user needs The BACS has to manage the loads in respect of consumer preferences and habits inside the building exploiting in the best way their different levels of flexibility

FR5 Reaction to Demand Side Management messages The BACS has to react to DSM requests from grid and market actors by providing a re-profiling service at POD level The nature of the request and the related economic aspects depend on the specific contract established for the provisioning of the power supply service

In order to meet all the FRs the following real time strategy is proposed As previously mentioned the load can be classified in three groups for which different actions are taken but all of them share a common feature each load is activated as a consequence of a consumer action which takes place in an asynchronous way with respect to the others in an uncontrolled scenario the resulting aggregated load profile depends on the power profile of each load and the timing in the sequence of requests

Now we assume that each time a consumer asks for the execution of a household appliance program or the heating process of the water in a boiler a request triggers the BACS which solves an optimization problem The output of the optimization task is given by a delayed start time for the appliance generating the request and the other ones still waiting for starting and finally the control for active boilers in the NZEB The decision taken is sent to the loads which are responsible for actuation

The optimality of control is lost every time a new request triggers the controller when it happens the optimization problem is updated and solved keeping the control optimal over the time This methodology has been investigated in the context of residential load management [12][13][14] and electromobility [15] and is referred as Event Driven Model Predictive Control

Figure 2 Load diagram for a standard

The mathematical formulation of the optidepends on the FRs Here we are mainly exploiting CHP and provide a desired aggreat POD level For this reason the problemfollows

BACS load management problem Forpower reference Pref(t) to be followed at thehousehold appliances with power profile pa

activation delay ∆tak a set of M boilers wi

pbm(t) demanded energy for water heating ∆

heating period ∆tbm solve

min Λ [P(u)-Pref]infin

where infin is the linfin norm defined in representing the maximum value of the atime) P(u) is the aggregated power withdrawis the control applied to the appliances and a proper weight diagonal matrix

If Pref is properly chosen it can be showcontrol u which results from the solution omanagement problem allows to meet all thintroduced in particular by choosing Pref

constant time sequence the controller will msuch a way as to minimize the displacemwithdrawal from a piece-wise constant behav

The optimization problem can be handlediscrete time framework using standard mreader is referred to [13][15])

IV AN EXAMPLE OF A COMMERCIALCOMMON MICROGRID INTEGR

COGENERATION AND ELECTRICAL LCASE STUDY

The paper presents a real case study energy building NZEB with a micro cogenerlinked to the main LV Power Center An innwith a unique POD is considered with the Mowned by the building According to the regupossible to consider also the traditional eledifferent PODs and with the substation owne

d unit Figure 3 Load profile for

imization problem interested in best

egated load profile m can be stated as

r a given time t a e POD a set of K a

k(t) and maximum ith nominal power ∆Eb

n and maximum

real space (here rgument over the wal at the POD u the boilers and Λ

wn that the optimal of the BACS load he FRs previously f as a piece-wise

manage the loads in ment of the power vior at POD level

ed and solved in a methodologies (the

L RESIDENTIAL RATING LOCAL USERS

of a nearly zero-ration CHP system novative microgrid MVLV substation ulatory barrier it is ectric service with ed and operated by

the distributor The building cunits common areas parking g

In order to estimate powerresidential units are subdivided

bull Economy

bull Standard with air condpower for lighting and

bull Luxury with air condmore power for lighting

Each unit is equipped with

The load profile is differentconsidering a singlecouple bsons behaviour

In Figure 2 is shown the loa

In the case study they are family behaviour (7 economy35 with a couple behaviour (1luxury) The individual units energy of about 300 MWhMWhyear for each unit

The heating system for rabout 400 MWh for year Thebuild an aggregate of the totarepresented the balance at thoperation in a winter day anstrategy

The system is completed consisting in a Turbec T100 miThe microturbine furnishes 10167 kW of thermal power con(about 35 m3h) with a total eff

Considering a thermal drivwith 2000 hoursyear of fugenerated by CHP is about 200consumption is of 300 MWhyearly consumption is 400MW

the building in a winter day

consists in 70 residentialoffice gardens etc

r energy and load profiles the d in 3 typologies

ditioned for one room and more washing machines

ditioned for all the rooms and g washing and dryer machines

electric boilers for hot water

tiated for the residential units by behaviour and a family with

ad diagram for a Standard Unit

considered 70 units 35 with a 19 standard and 9 luxury) and

17 economy 8 standard and 10 IU use an amount of electrical

hyear equivalent to about 6

residentialtertiary units spends authors prepared a tool able to

al load diagram In Figure 3 is he POD considering the CHP nd not considering any control

by a 100 kVA CHP system icroturbine natural gas powered 00 kW of electricity power and nsuming 350 kW of gas power ficiency of 78

ven management of the system ull power the yearly energy 0 MWh of electricity (the yearly h) and 340 MWh of heat (the

Wh)

Figure 4 Power balance at POD

The aggregation of individual appliance demand so as to produce an individual household demand profile is achievable by pressing the button Load Diagram present in the Output panel of interface GUI

The import of values with which to make the load charts is by reading an excel The excel file becomes the source of the program with the possibility of being changed by the user The file contains for each unit the following functions

Total power absorbed by uncontrollable loads sum sum [W]

Total power absorbed by controllable loads sum sum [W]

Total power absorbed by plannable loads sum sum [W]

Where

N is the number of uncontrollable loads

M is the number of controllable loads

K is the number of plannable loads

Piuc is the daily profile of the ith uncontrollable load It is a vector of 96 values where each value is for 15 minutes

PTiuc is the nominal power of the ith uncontrollable load

cuiuc is the coefficient of utilization of the ith uncontrollable load It is a vector of 96 values

piuc is the a vector of 96 values that indicates the activation of the ith load

The same method can be used for controllable and plannable loads The aggregation of the load shapes of various households so as to derive the end-use area load profile is realized by a vector time with which to make the time shift loads of single unit The time vector is based on a Gaussian distribution having zero mean and with a variance such that the probability of occurrence of a displacement of the loads over 4 hour is less than 1

The objective of the optimization of controllable and plannable loads is to make the profile of the electric load of the total units as flat in order to be able to exploit the electric power generated by a CHP

Figure 4 shows a comparison between the ldquoopen looprdquo balance at POD (ie without any control) and the closed loop balance at POD deriving from the implementation of the proposed control strategy The tracking of a proper power reference allows to achieve a balance which is more regular with respect to the non-controlled case Reverse power flow is significantly reduced although not completely eliminated (that depends on the constraints on power-shifting imposed by the user preferences which the control algorithm has to satisfy) A piece-wise constant power reference is chosen which is built on the base of the average power consumed in the day by the whole residentialcommercial complex the CHP profile and taking into account the portion of the load profile which

cannot be shifted (the non-controllable power) In particular from 1000 to 2200 the power reference must be chosen greater than the CHP electric rate in order to steer the system towards zero reverse power flow The resulting net power exchange only approximates (see figure 4) a piece-wise constant function because the control system is constrained by the presence of user preferences and non-controllable loads Finally we avoided choosing to much ldquothighrdquo user preferences for load shifting in such a way as to show the effectiveness and the potentialities of the proposed control algorithm (we chose a 15 minutes maximum delay for user sensitive loads -eg the 10 liters kitchen boiler- and 5 hours maximum delay for less user sensitive loads -eg the washing machine and the 5080 liters boilers-)

V CONCLUSIONS The paper presents a case study of a microgrid for a

lsquoNearly Zero-Energy Buildingrsquo NZEB The authors suggest the ecodesign of the residential and commercial low voltage distribution for the next future that allows to accomplish the goals of the NZEBs To avoid future chaotic phenomena in the existing distribution network the power flow of local generators has to be maintained local the users have to remain net-loads organized in Ever Net-Load Microgrids The actual distribution network for low voltage customers appears inadequate to comply with these improvements and it has to recognize the constitution of microgrids as union of Customers Groups The suggested microgrid allows to enhance safety high local power quality future dc distribution systems common emergency systems efficient load shedding actual maintenance service energy management and allows to guarantee a reduced impact as ever net load on the net supply

REFERENCES [1] Directive 9692EC of the European Parliament and of the Council

of 19 December 1996 concerning common rules for the internal market in electricity

[2] Directive 200177EC of the European Parliament and of the Council of 27 September 2001 on the promotion of electricity produced from renewable energy sources in the internal electricity market

[3] Directive 200291EC of the European Parliament and of the Council of 16 December 2002 on the energy performance of buildings EPBD

[4] Directive 20048EC of the European Parliament and of the Council of 11 February 2004 on the promotion of cogeneration based on a useful heat demand in the internal energy market

[5] Directive 200532CE of the European Parliament and of the Council of 6 July 2005 on the ecodesign requirements for energy-using products

[6] Directive 201031EC of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings

[7] G Parise L Martirano Prospected evolution for low voltage customers ecodesign of the electrical distribution system Industry Applications Society Annual Meeting 2008 IEEE-IAS 08 Edmonton Alberta Canada 5-9 October 2008

[8] D W Zipse The hazardous multigrounded neutral distribution system and dangerous stray currents PCIC 03

[9] G Parise L Martirano M Mitolo TN-Island Grounding System and the House of the Future 2006 41st IAS Annual Meeting 8-12 October 2006

[10] G Parise L Martirano L Parise Ecodesign of Ever Net-Load Microgrids IEEE Industry Applications Society Annual Meeting 2012 Las Vegas USA

[11] Brenna M Falvo MC Foiadelli F Martirano L Poli D Sustainable Energy Microsystem (SEM) preliminary energy analysis 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) Washington DC USA 16-20 January 2012

[12] Pimpinella L Di Giorgio A Mercurio A ldquoLocal Energy Management System Control Scheme and Loads Modelingrdquo Proc of the 18th Mediterranean Conference on Control and Automation MED10 304ndash308 Marrakech 23-25 June 2010

[13] Di Giorgio A Pimpinella L An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management Applied Energy (Elsevier) Special Issue ldquoSmart Gridsrdquo 96 92-103 (2012)

[14] Di Giorgio A Pimpinella L Liberati F ldquoA model predictive control approach to the load shifting problem in a household equipped with an energy storage unitrdquo Proc of the 20th Mediterranean Conference on Control and Automation MED12rdquo 1491-1498 Barcelona July 2012

[15] Di Giorgio A Liberati F Canale S ldquoIEC 61851 compliant electric vehicle charging control in Smartgridsrdquo 21th Mediterranean Conference on Control and Automation MED13rdquo Chania July 2013

[16] Brenna M Falvo M C Foiadelli F Martirano L Massaro F Poli D Vaccaro A Challenges in energy systems for the smart-cities of the future Energy Conference and Exhibition (ENERGYCON) 2012 IEEE International pp755-762 9-12 September 2012

[17] G Parise L Martirano L Parise M Mitolo Safety Evolution of Residential Microsystems 2nd ENERGYCON Conference amp Exhibition 2012 (Future Energy Grids and Systems Symposium Firenze 9-12 September 2012

Luigi Martirano (StMrsquo98-M02-SM11) was born in Cosenza Italy in 1973 He received the MS and PhD degrees in Electrical Engineering in 1998 and 2003 respectively In 2000 he joined the Department of Electrical Engineering of the University of Rome La Sapienza He is currently a researcher in electrical power systems and assistant professor of Building Automation and Energy Management He has authored more than 60 papers in international journals and conferences and one international patent His research activities cover power systems design planning safety lightings home and building automation energy management He is a senior member of the IEEEIAS member of the AEIT (Italian Association of Electrical and Electronics Engineers) and of the CEI (Italian Electrical Commission) Technical Committees CT205 (Home and Building Electronic Systems) and CT315 (Energy Efficiency) He has been Registered Professional Engineer

Serena Fornari was born in Rome Italy in 1987 She received the Bachelor Degree in 2010 in Energy Engineering and Master Degree with honors in Energy Engineering from the University of Rome ldquoSapienza in January 2013 She discussed a thesis on Analysis and management of electrical loads for domestic buildings Her main interests are in renewable energy systems power management systems and demand side management

Alessandro Di Giorgio was born in Rome in 1980 He received the master degree in Physics in 2005 and the PhD degree in Systems Engineering in 2010 He is currently an Assistant Professor of ldquoAutomatic Controlrdquo with the University of Rome Sapienza His research activity deals with the application of control systems theory to Smart Grids focusing on local energy management systems demand side management wind turbines electromobility interdependencies analysis and powerline communications over distribution grids He has been involved in several Italian and European research projects on these topics Francesco Liberati was born in Rome Italy in 1987 He received a graduate degree cum laude in systems engineering from the University of Rome La Sapienza in 2011 Since January 2010 he has been working at Consortium for the Research in Automation and Telecommunication (CRAT) Rome Italy His research interests include smart grids and critical infrastructure protection He is involved in Italian and European research projects

本文献由ldquo学霸图书馆-文献云下载rdquo收集自网络仅供学习交流使用

学霸图书馆（wwwxuebalibcom）是一个ldquo整合众多图书馆数据库资源

提供一站式文献检索和下载服务rdquo的24 小时在线不限IP

图书馆

图书馆致力于便利促进学习与科研提供最强文献下载服务

图书馆导航

图书馆首页 文献云下载 图书馆入口 外文数据库大全 疑难文献辅助工具

Figure 2 Load diagram for a standard

The mathematical formulation of the optidepends on the FRs Here we are mainly exploiting CHP and provide a desired aggreat POD level For this reason the problemfollows

BACS load management problem Forpower reference Pref(t) to be followed at thehousehold appliances with power profile pa

activation delay ∆tak a set of M boilers wi

pbm(t) demanded energy for water heating ∆

heating period ∆tbm solve

min Λ [P(u)-Pref]infin

where infin is the linfin norm defined in representing the maximum value of the atime) P(u) is the aggregated power withdrawis the control applied to the appliances and a proper weight diagonal matrix

If Pref is properly chosen it can be showcontrol u which results from the solution omanagement problem allows to meet all thintroduced in particular by choosing Pref

constant time sequence the controller will msuch a way as to minimize the displacemwithdrawal from a piece-wise constant behav

The optimization problem can be handlediscrete time framework using standard mreader is referred to [13][15])

IV AN EXAMPLE OF A COMMERCIALCOMMON MICROGRID INTEGR

COGENERATION AND ELECTRICAL LCASE STUDY

The paper presents a real case study energy building NZEB with a micro cogenerlinked to the main LV Power Center An innwith a unique POD is considered with the Mowned by the building According to the regupossible to consider also the traditional eledifferent PODs and with the substation owne

d unit Figure 3 Load profile for

imization problem interested in best

egated load profile m can be stated as

r a given time t a e POD a set of K a

k(t) and maximum ith nominal power ∆Eb

n and maximum

real space (here rgument over the wal at the POD u the boilers and Λ

wn that the optimal of the BACS load he FRs previously f as a piece-wise

manage the loads in ment of the power vior at POD level

ed and solved in a methodologies (the

L RESIDENTIAL RATING LOCAL USERS

of a nearly zero-ration CHP system novative microgrid MVLV substation ulatory barrier it is ectric service with ed and operated by

the distributor The building cunits common areas parking g

In order to estimate powerresidential units are subdivided

bull Economy

bull Standard with air condpower for lighting and

bull Luxury with air condmore power for lighting

Each unit is equipped with

The load profile is differentconsidering a singlecouple bsons behaviour

In Figure 2 is shown the loa

In the case study they are family behaviour (7 economy35 with a couple behaviour (1luxury) The individual units energy of about 300 MWhMWhyear for each unit

The heating system for rabout 400 MWh for year Thebuild an aggregate of the totarepresented the balance at thoperation in a winter day anstrategy

The system is completed consisting in a Turbec T100 miThe microturbine furnishes 10167 kW of thermal power con(about 35 m3h) with a total eff

Considering a thermal drivwith 2000 hoursyear of fugenerated by CHP is about 200consumption is of 300 MWhyearly consumption is 400MW

the building in a winter day

consists in 70 residentialoffice gardens etc

r energy and load profiles the d in 3 typologies

ditioned for one room and more washing machines

ditioned for all the rooms and g washing and dryer machines

electric boilers for hot water

tiated for the residential units by behaviour and a family with

ad diagram for a Standard Unit

considered 70 units 35 with a 19 standard and 9 luxury) and

17 economy 8 standard and 10 IU use an amount of electrical

hyear equivalent to about 6

residentialtertiary units spends authors prepared a tool able to

al load diagram In Figure 3 is he POD considering the CHP nd not considering any control

by a 100 kVA CHP system icroturbine natural gas powered 00 kW of electricity power and nsuming 350 kW of gas power ficiency of 78

ven management of the system ull power the yearly energy 0 MWh of electricity (the yearly h) and 340 MWh of heat (the

Wh)

Figure 4 Power balance at POD

The aggregation of individual appliance demand so as to produce an individual household demand profile is achievable by pressing the button Load Diagram present in the Output panel of interface GUI

The import of values with which to make the load charts is by reading an excel The excel file becomes the source of the program with the possibility of being changed by the user The file contains for each unit the following functions

Total power absorbed by uncontrollable loads sum sum [W]

Total power absorbed by controllable loads sum sum [W]

Total power absorbed by plannable loads sum sum [W]

Where

N is the number of uncontrollable loads

M is the number of controllable loads

K is the number of plannable loads

Piuc is the daily profile of the ith uncontrollable load It is a vector of 96 values where each value is for 15 minutes

PTiuc is the nominal power of the ith uncontrollable load

cuiuc is the coefficient of utilization of the ith uncontrollable load It is a vector of 96 values

piuc is the a vector of 96 values that indicates the activation of the ith load

The same method can be used for controllable and plannable loads The aggregation of the load shapes of various households so as to derive the end-use area load profile is realized by a vector time with which to make the time shift loads of single unit The time vector is based on a Gaussian distribution having zero mean and with a variance such that the probability of occurrence of a displacement of the loads over 4 hour is less than 1

The objective of the optimization of controllable and plannable loads is to make the profile of the electric load of the total units as flat in order to be able to exploit the electric power generated by a CHP

Figure 4 shows a comparison between the ldquoopen looprdquo balance at POD (ie without any control) and the closed loop balance at POD deriving from the implementation of the proposed control strategy The tracking of a proper power reference allows to achieve a balance which is more regular with respect to the non-controlled case Reverse power flow is significantly reduced although not completely eliminated (that depends on the constraints on power-shifting imposed by the user preferences which the control algorithm has to satisfy) A piece-wise constant power reference is chosen which is built on the base of the average power consumed in the day by the whole residentialcommercial complex the CHP profile and taking into account the portion of the load profile which

cannot be shifted (the non-controllable power) In particular from 1000 to 2200 the power reference must be chosen greater than the CHP electric rate in order to steer the system towards zero reverse power flow The resulting net power exchange only approximates (see figure 4) a piece-wise constant function because the control system is constrained by the presence of user preferences and non-controllable loads Finally we avoided choosing to much ldquothighrdquo user preferences for load shifting in such a way as to show the effectiveness and the potentialities of the proposed control algorithm (we chose a 15 minutes maximum delay for user sensitive loads -eg the 10 liters kitchen boiler- and 5 hours maximum delay for less user sensitive loads -eg the washing machine and the 5080 liters boilers-)

V CONCLUSIONS The paper presents a case study of a microgrid for a

lsquoNearly Zero-Energy Buildingrsquo NZEB The authors suggest the ecodesign of the residential and commercial low voltage distribution for the next future that allows to accomplish the goals of the NZEBs To avoid future chaotic phenomena in the existing distribution network the power flow of local generators has to be maintained local the users have to remain net-loads organized in Ever Net-Load Microgrids The actual distribution network for low voltage customers appears inadequate to comply with these improvements and it has to recognize the constitution of microgrids as union of Customers Groups The suggested microgrid allows to enhance safety high local power quality future dc distribution systems common emergency systems efficient load shedding actual maintenance service energy management and allows to guarantee a reduced impact as ever net load on the net supply

REFERENCES [1] Directive 9692EC of the European Parliament and of the Council

of 19 December 1996 concerning common rules for the internal market in electricity

[2] Directive 200177EC of the European Parliament and of the Council of 27 September 2001 on the promotion of electricity produced from renewable energy sources in the internal electricity market

[3] Directive 200291EC of the European Parliament and of the Council of 16 December 2002 on the energy performance of buildings EPBD

[4] Directive 20048EC of the European Parliament and of the Council of 11 February 2004 on the promotion of cogeneration based on a useful heat demand in the internal energy market

[5] Directive 200532CE of the European Parliament and of the Council of 6 July 2005 on the ecodesign requirements for energy-using products

[6] Directive 201031EC of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings

[7] G Parise L Martirano Prospected evolution for low voltage customers ecodesign of the electrical distribution system Industry Applications Society Annual Meeting 2008 IEEE-IAS 08 Edmonton Alberta Canada 5-9 October 2008

[8] D W Zipse The hazardous multigrounded neutral distribution system and dangerous stray currents PCIC 03

[9] G Parise L Martirano M Mitolo TN-Island Grounding System and the House of the Future 2006 41st IAS Annual Meeting 8-12 October 2006

[10] G Parise L Martirano L Parise Ecodesign of Ever Net-Load Microgrids IEEE Industry Applications Society Annual Meeting 2012 Las Vegas USA

[11] Brenna M Falvo MC Foiadelli F Martirano L Poli D Sustainable Energy Microsystem (SEM) preliminary energy analysis 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) Washington DC USA 16-20 January 2012

[12] Pimpinella L Di Giorgio A Mercurio A ldquoLocal Energy Management System Control Scheme and Loads Modelingrdquo Proc of the 18th Mediterranean Conference on Control and Automation MED10 304ndash308 Marrakech 23-25 June 2010

[13] Di Giorgio A Pimpinella L An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management Applied Energy (Elsevier) Special Issue ldquoSmart Gridsrdquo 96 92-103 (2012)

[14] Di Giorgio A Pimpinella L Liberati F ldquoA model predictive control approach to the load shifting problem in a household equipped with an energy storage unitrdquo Proc of the 20th Mediterranean Conference on Control and Automation MED12rdquo 1491-1498 Barcelona July 2012

[15] Di Giorgio A Liberati F Canale S ldquoIEC 61851 compliant electric vehicle charging control in Smartgridsrdquo 21th Mediterranean Conference on Control and Automation MED13rdquo Chania July 2013

[16] Brenna M Falvo M C Foiadelli F Martirano L Massaro F Poli D Vaccaro A Challenges in energy systems for the smart-cities of the future Energy Conference and Exhibition (ENERGYCON) 2012 IEEE International pp755-762 9-12 September 2012

[17] G Parise L Martirano L Parise M Mitolo Safety Evolution of Residential Microsystems 2nd ENERGYCON Conference amp Exhibition 2012 (Future Energy Grids and Systems Symposium Firenze 9-12 September 2012

Luigi Martirano (StMrsquo98-M02-SM11) was born in Cosenza Italy in 1973 He received the MS and PhD degrees in Electrical Engineering in 1998 and 2003 respectively In 2000 he joined the Department of Electrical Engineering of the University of Rome La Sapienza He is currently a researcher in electrical power systems and assistant professor of Building Automation and Energy Management He has authored more than 60 papers in international journals and conferences and one international patent His research activities cover power systems design planning safety lightings home and building automation energy management He is a senior member of the IEEEIAS member of the AEIT (Italian Association of Electrical and Electronics Engineers) and of the CEI (Italian Electrical Commission) Technical Committees CT205 (Home and Building Electronic Systems) and CT315 (Energy Efficiency) He has been Registered Professional Engineer

Serena Fornari was born in Rome Italy in 1987 She received the Bachelor Degree in 2010 in Energy Engineering and Master Degree with honors in Energy Engineering from the University of Rome ldquoSapienza in January 2013 She discussed a thesis on Analysis and management of electrical loads for domestic buildings Her main interests are in renewable energy systems power management systems and demand side management

Alessandro Di Giorgio was born in Rome in 1980 He received the master degree in Physics in 2005 and the PhD degree in Systems Engineering in 2010 He is currently an Assistant Professor of ldquoAutomatic Controlrdquo with the University of Rome Sapienza His research activity deals with the application of control systems theory to Smart Grids focusing on local energy management systems demand side management wind turbines electromobility interdependencies analysis and powerline communications over distribution grids He has been involved in several Italian and European research projects on these topics Francesco Liberati was born in Rome Italy in 1987 He received a graduate degree cum laude in systems engineering from the University of Rome La Sapienza in 2011 Since January 2010 he has been working at Consortium for the Research in Automation and Telecommunication (CRAT) Rome Italy His research interests include smart grids and critical infrastructure protection He is involved in Italian and European research projects

本文献由ldquo学霸图书馆-文献云下载rdquo收集自网络仅供学习交流使用

学霸图书馆（wwwxuebalibcom）是一个ldquo整合众多图书馆数据库资源

提供一站式文献检索和下载服务rdquo的24 小时在线不限IP

图书馆

图书馆致力于便利促进学习与科研提供最强文献下载服务

图书馆导航

图书馆首页 文献云下载 图书馆入口 外文数据库大全 疑难文献辅助工具

Figure 4 Power balance at POD

The aggregation of individual appliance demand so as to produce an individual household demand profile is achievable by pressing the button Load Diagram present in the Output panel of interface GUI

The import of values with which to make the load charts is by reading an excel The excel file becomes the source of the program with the possibility of being changed by the user The file contains for each unit the following functions

Total power absorbed by uncontrollable loads sum sum [W]

Total power absorbed by controllable loads sum sum [W]

Total power absorbed by plannable loads sum sum [W]

Where

N is the number of uncontrollable loads

M is the number of controllable loads

K is the number of plannable loads

Piuc is the daily profile of the ith uncontrollable load It is a vector of 96 values where each value is for 15 minutes

PTiuc is the nominal power of the ith uncontrollable load

cuiuc is the coefficient of utilization of the ith uncontrollable load It is a vector of 96 values

piuc is the a vector of 96 values that indicates the activation of the ith load

The same method can be used for controllable and plannable loads The aggregation of the load shapes of various households so as to derive the end-use area load profile is realized by a vector time with which to make the time shift loads of single unit The time vector is based on a Gaussian distribution having zero mean and with a variance such that the probability of occurrence of a displacement of the loads over 4 hour is less than 1

The objective of the optimization of controllable and plannable loads is to make the profile of the electric load of the total units as flat in order to be able to exploit the electric power generated by a CHP

Figure 4 shows a comparison between the ldquoopen looprdquo balance at POD (ie without any control) and the closed loop balance at POD deriving from the implementation of the proposed control strategy The tracking of a proper power reference allows to achieve a balance which is more regular with respect to the non-controlled case Reverse power flow is significantly reduced although not completely eliminated (that depends on the constraints on power-shifting imposed by the user preferences which the control algorithm has to satisfy) A piece-wise constant power reference is chosen which is built on the base of the average power consumed in the day by the whole residentialcommercial complex the CHP profile and taking into account the portion of the load profile which

cannot be shifted (the non-controllable power) In particular from 1000 to 2200 the power reference must be chosen greater than the CHP electric rate in order to steer the system towards zero reverse power flow The resulting net power exchange only approximates (see figure 4) a piece-wise constant function because the control system is constrained by the presence of user preferences and non-controllable loads Finally we avoided choosing to much ldquothighrdquo user preferences for load shifting in such a way as to show the effectiveness and the potentialities of the proposed control algorithm (we chose a 15 minutes maximum delay for user sensitive loads -eg the 10 liters kitchen boiler- and 5 hours maximum delay for less user sensitive loads -eg the washing machine and the 5080 liters boilers-)

V CONCLUSIONS The paper presents a case study of a microgrid for a

lsquoNearly Zero-Energy Buildingrsquo NZEB The authors suggest the ecodesign of the residential and commercial low voltage distribution for the next future that allows to accomplish the goals of the NZEBs To avoid future chaotic phenomena in the existing distribution network the power flow of local generators has to be maintained local the users have to remain net-loads organized in Ever Net-Load Microgrids The actual distribution network for low voltage customers appears inadequate to comply with these improvements and it has to recognize the constitution of microgrids as union of Customers Groups The suggested microgrid allows to enhance safety high local power quality future dc distribution systems common emergency systems efficient load shedding actual maintenance service energy management and allows to guarantee a reduced impact as ever net load on the net supply

REFERENCES [1] Directive 9692EC of the European Parliament and of the Council

of 19 December 1996 concerning common rules for the internal market in electricity

[2] Directive 200177EC of the European Parliament and of the Council of 27 September 2001 on the promotion of electricity produced from renewable energy sources in the internal electricity market

[3] Directive 200291EC of the European Parliament and of the Council of 16 December 2002 on the energy performance of buildings EPBD

[4] Directive 20048EC of the European Parliament and of the Council of 11 February 2004 on the promotion of cogeneration based on a useful heat demand in the internal energy market

[5] Directive 200532CE of the European Parliament and of the Council of 6 July 2005 on the ecodesign requirements for energy-using products

[6] Directive 201031EC of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings

[7] G Parise L Martirano Prospected evolution for low voltage customers ecodesign of the electrical distribution system Industry Applications Society Annual Meeting 2008 IEEE-IAS 08 Edmonton Alberta Canada 5-9 October 2008

[8] D W Zipse The hazardous multigrounded neutral distribution system and dangerous stray currents PCIC 03

[9] G Parise L Martirano M Mitolo TN-Island Grounding System and the House of the Future 2006 41st IAS Annual Meeting 8-12 October 2006

[10] G Parise L Martirano L Parise Ecodesign of Ever Net-Load Microgrids IEEE Industry Applications Society Annual Meeting 2012 Las Vegas USA

[11] Brenna M Falvo MC Foiadelli F Martirano L Poli D Sustainable Energy Microsystem (SEM) preliminary energy analysis 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) Washington DC USA 16-20 January 2012

[12] Pimpinella L Di Giorgio A Mercurio A ldquoLocal Energy Management System Control Scheme and Loads Modelingrdquo Proc of the 18th Mediterranean Conference on Control and Automation MED10 304ndash308 Marrakech 23-25 June 2010

[13] Di Giorgio A Pimpinella L An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management Applied Energy (Elsevier) Special Issue ldquoSmart Gridsrdquo 96 92-103 (2012)

[14] Di Giorgio A Pimpinella L Liberati F ldquoA model predictive control approach to the load shifting problem in a household equipped with an energy storage unitrdquo Proc of the 20th Mediterranean Conference on Control and Automation MED12rdquo 1491-1498 Barcelona July 2012

[15] Di Giorgio A Liberati F Canale S ldquoIEC 61851 compliant electric vehicle charging control in Smartgridsrdquo 21th Mediterranean Conference on Control and Automation MED13rdquo Chania July 2013

[16] Brenna M Falvo M C Foiadelli F Martirano L Massaro F Poli D Vaccaro A Challenges in energy systems for the smart-cities of the future Energy Conference and Exhibition (ENERGYCON) 2012 IEEE International pp755-762 9-12 September 2012

[17] G Parise L Martirano L Parise M Mitolo Safety Evolution of Residential Microsystems 2nd ENERGYCON Conference amp Exhibition 2012 (Future Energy Grids and Systems Symposium Firenze 9-12 September 2012

Luigi Martirano (StMrsquo98-M02-SM11) was born in Cosenza Italy in 1973 He received the MS and PhD degrees in Electrical Engineering in 1998 and 2003 respectively In 2000 he joined the Department of Electrical Engineering of the University of Rome La Sapienza He is currently a researcher in electrical power systems and assistant professor of Building Automation and Energy Management He has authored more than 60 papers in international journals and conferences and one international patent His research activities cover power systems design planning safety lightings home and building automation energy management He is a senior member of the IEEEIAS member of the AEIT (Italian Association of Electrical and Electronics Engineers) and of the CEI (Italian Electrical Commission) Technical Committees CT205 (Home and Building Electronic Systems) and CT315 (Energy Efficiency) He has been Registered Professional Engineer

Serena Fornari was born in Rome Italy in 1987 She received the Bachelor Degree in 2010 in Energy Engineering and Master Degree with honors in Energy Engineering from the University of Rome ldquoSapienza in January 2013 She discussed a thesis on Analysis and management of electrical loads for domestic buildings Her main interests are in renewable energy systems power management systems and demand side management

Alessandro Di Giorgio was born in Rome in 1980 He received the master degree in Physics in 2005 and the PhD degree in Systems Engineering in 2010 He is currently an Assistant Professor of ldquoAutomatic Controlrdquo with the University of Rome Sapienza His research activity deals with the application of control systems theory to Smart Grids focusing on local energy management systems demand side management wind turbines electromobility interdependencies analysis and powerline communications over distribution grids He has been involved in several Italian and European research projects on these topics Francesco Liberati was born in Rome Italy in 1987 He received a graduate degree cum laude in systems engineering from the University of Rome La Sapienza in 2011 Since January 2010 he has been working at Consortium for the Research in Automation and Telecommunication (CRAT) Rome Italy His research interests include smart grids and critical infrastructure protection He is involved in Italian and European research projects

本文献由ldquo学霸图书馆-文献云下载rdquo收集自网络仅供学习交流使用

学霸图书馆（wwwxuebalibcom）是一个ldquo整合众多图书馆数据库资源

提供一站式文献检索和下载服务rdquo的24 小时在线不限IP

图书馆

图书馆致力于便利促进学习与科研提供最强文献下载服务

图书馆导航

图书馆首页 文献云下载 图书馆入口 外文数据库大全 疑难文献辅助工具

[4] Directive 20048EC of the European Parliament and of the Council of 11 February 2004 on the promotion of cogeneration based on a useful heat demand in the internal energy market

[5] Directive 200532CE of the European Parliament and of the Council of 6 July 2005 on the ecodesign requirements for energy-using products

[6] Directive 201031EC of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings

[7] G Parise L Martirano Prospected evolution for low voltage customers ecodesign of the electrical distribution system Industry Applications Society Annual Meeting 2008 IEEE-IAS 08 Edmonton Alberta Canada 5-9 October 2008

[8] D W Zipse The hazardous multigrounded neutral distribution system and dangerous stray currents PCIC 03

[9] G Parise L Martirano M Mitolo TN-Island Grounding System and the House of the Future 2006 41st IAS Annual Meeting 8-12 October 2006

[10] G Parise L Martirano L Parise Ecodesign of Ever Net-Load Microgrids IEEE Industry Applications Society Annual Meeting 2012 Las Vegas USA

[11] Brenna M Falvo MC Foiadelli F Martirano L Poli D Sustainable Energy Microsystem (SEM) preliminary energy analysis 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) Washington DC USA 16-20 January 2012

[12] Pimpinella L Di Giorgio A Mercurio A ldquoLocal Energy Management System Control Scheme and Loads Modelingrdquo Proc of the 18th Mediterranean Conference on Control and Automation MED10 304ndash308 Marrakech 23-25 June 2010

[13] Di Giorgio A Pimpinella L An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management Applied Energy (Elsevier) Special Issue ldquoSmart Gridsrdquo 96 92-103 (2012)

[14] Di Giorgio A Pimpinella L Liberati F ldquoA model predictive control approach to the load shifting problem in a household equipped with an energy storage unitrdquo Proc of the 20th Mediterranean Conference on Control and Automation MED12rdquo 1491-1498 Barcelona July 2012

[15] Di Giorgio A Liberati F Canale S ldquoIEC 61851 compliant electric vehicle charging control in Smartgridsrdquo 21th Mediterranean Conference on Control and Automation MED13rdquo Chania July 2013

[16] Brenna M Falvo M C Foiadelli F Martirano L Massaro F Poli D Vaccaro A Challenges in energy systems for the smart-cities of the future Energy Conference and Exhibition (ENERGYCON) 2012 IEEE International pp755-762 9-12 September 2012

[17] G Parise L Martirano L Parise M Mitolo Safety Evolution of Residential Microsystems 2nd ENERGYCON Conference amp Exhibition 2012 (Future Energy Grids and Systems Symposium Firenze 9-12 September 2012

Luigi Martirano (StMrsquo98-M02-SM11) was born in Cosenza Italy in 1973 He received the MS and PhD degrees in Electrical Engineering in 1998 and 2003 respectively In 2000 he joined the Department of Electrical Engineering of the University of Rome La Sapienza He is currently a researcher in electrical power systems and assistant professor of Building Automation and Energy Management He has authored more than 60 papers in international journals and conferences and one international patent His research activities cover power systems design planning safety lightings home and building automation energy management He is a senior member of the IEEEIAS member of the AEIT (Italian Association of Electrical and Electronics Engineers) and of the CEI (Italian Electrical Commission) Technical Committees CT205 (Home and Building Electronic Systems) and CT315 (Energy Efficiency) He has been Registered Professional Engineer

Serena Fornari was born in Rome Italy in 1987 She received the Bachelor Degree in 2010 in Energy Engineering and Master Degree with honors in Energy Engineering from the University of Rome ldquoSapienza in January 2013 She discussed a thesis on Analysis and management of electrical loads for domestic buildings Her main interests are in renewable energy systems power management systems and demand side management

Alessandro Di Giorgio was born in Rome in 1980 He received the master degree in Physics in 2005 and the PhD degree in Systems Engineering in 2010 He is currently an Assistant Professor of ldquoAutomatic Controlrdquo with the University of Rome Sapienza His research activity deals with the application of control systems theory to Smart Grids focusing on local energy management systems demand side management wind turbines electromobility interdependencies analysis and powerline communications over distribution grids He has been involved in several Italian and European research projects on these topics Francesco Liberati was born in Rome Italy in 1987 He received a graduate degree cum laude in systems engineering from the University of Rome La Sapienza in 2011 Since January 2010 he has been working at Consortium for the Research in Automation and Telecommunication (CRAT) Rome Italy His research interests include smart grids and critical infrastructure protection He is involved in Italian and European research projects

本文献由ldquo学霸图书馆-文献云下载rdquo收集自网络仅供学习交流使用

学霸图书馆（wwwxuebalibcom）是一个ldquo整合众多图书馆数据库资源

提供一站式文献检索和下载服务rdquo的24 小时在线不限IP

图书馆

图书馆致力于便利促进学习与科研提供最强文献下载服务

图书馆导航

图书馆首页 文献云下载 图书馆入口 外文数据库大全 疑难文献辅助工具

本文献由ldquo学霸图书馆-文献云下载rdquo收集自网络仅供学习交流使用

学霸图书馆（wwwxuebalibcom）是一个ldquo整合众多图书馆数据库资源

提供一站式文献检索和下载服务rdquo的24 小时在线不限IP

图书馆

图书馆致力于便利促进学习与科研提供最强文献下载服务

图书馆导航

图书馆首页 文献云下载 图书馆入口 外文数据库大全 疑难文献辅助工具