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Thermoeconomic optimization of an energy hub. Alessandra Cuneo Mario Luigi Ferrari. Alberto Traverso Aristide F. Massardo. Thermochemical Power Group (TPG) - DIME – University of Genoa, Italy. Speaker: Alessandra Cuneo. Nice, 1 – 3 October 2014. Aims of the study. - PowerPoint PPT Presentation
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Sustainable Place, 1-3 October, 2014, Nice, France
Thermochemical Power Group (TPG) - DIME – University of Genoa, Italy
Thermoeconomic optimization of an energy hub
Alessandra Cuneo Mario Luigi Ferrari
Alberto Traverso Aristide F. Massardo
Speaker: Alessandra Cuneo
Nice, 1 – 3 October 2014
Sustainable Place, 1-3 October, 2014, Nice, France
Aims of the studyAims of the study
Illustrate the operation of a real energy hub
Optimize the management strategy of the different prime movers to satisfy the energy demand
Two different layouts, with and without a conventional stratified thermal storage
2
Sustainable Place, 1-3 October, 2014, Nice, France
Microturbine
Internal combustion engine
Storage vessel
LaboratoryLaboratory
SAVONA
Sustainable Place, 1-3 October, 2014, Nice, France
ECoMP softwareECoMP software
AIMS
thermo-economic time-dependent analysis of poly-generative plants
optimization of energy systems
Modular structure (48 modules)
Each component described by subroutines containing: - off design performance curves - functions for capital costs - variable costs - mass and energy flows
4
Sustainable Place, 1-3 October, 2014, Nice, France
ECoMP optimization strategyECoMP optimization strategy
mGT ICE
Percentage loads of the prime movers (mGT, ICE) have been chosen as decision variables
Min value Max value
mGT % load 0 % (OFF) 100 % η = F (% load)
ICE % load 0 % (OFF) 100 % η = F (% load)
*
1 ,var virtvirtvirtvirtacqel
N
i ifueli QEFcEccFC
Fuel cost
Electricity cost “Virtual” cost
The cost functions to minimize are:
Sustainable Place, 1-3 October, 2014, Nice, France
Thermal storage modelThermal storage model• Virtual costs are associated to emptying and filling operations
• Virtual terms promote filling operation and prime movers nominal conditions
• Penalty costs associated to overload and total emptying conditions
Cin Cout
STORAGE
Emptying out cost
Filling up cost
FUEL NETWORK
PRIME MOVER USER
CUCF
real
fuelin LHV
cc
nom
fuelout LHV
cc
Sustainable Place, 1-3 October, 2014, Nice, France 7
Plant main assumptions and load demandPlant main assumptions and load demand Electricity cost [€/kWh] 0.2
Electricity price [€/kWh] 0.1
Thermal energy [€/kWh] 0.1
Gas [€/kg] 0.25
0 2000 4000 6000 8000 10000 120000
50
100
150
200
Load Demand
Electrical Thermal
Time [s]
[kW
]
Sustainable Place, 1-3 October, 2014, Nice, France 8
Thermal Demand ComparisonThermal Demand Comparison
1 5 9 13 17 21 25 29 33 370
50
100
150
200Without thermal storage
Pth mgt
Pth ice
Thermal Demand
Time[k
W]
1 4 7 10 13 16 19 22 25 28 31 34 370
50
100
150
200
250
With thermal storage
Storage
Pth ice
Pth mgt
Thermal Demand
Time
[kW
]
mGT works more
Storage help the management in the
peak
Sustainable Place, 1-3 October, 2014, Nice, France 9
Electrical Demand ComparisonElectrical Demand Comparison
1 5 9 13 17 21 25 29 33 370
20406080
100120
With thermal storage
Pel icePel mgtEl demand
Time
[kW
]
0
20
40
60
80
100
120Without thermal storage
Pel mgt
Pel ice
Electrical Demand
Time[k
W]
Decrease electricity bought from the grid
Sustainable Place, 1-3 October, 2014, Nice, France 10
mgT ICE mgT ICENO STORAGE STORAGE
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
nominal condition off design swicth off
Tim
e Pe
rcen
tage
Energetic resultsEnergetic results
mGT works more at design point only.
Efficiency improvementand increase of
machines lifetime
Sustainable Place, 1-3 October, 2014, Nice, France 11
Without thermal
storageWith thermal
storage
Revenues [€] 633.70 650Costs [€] 81.20 78.73Profit [€] 522.5 571.97
Economic resultsEconomic results
NO STORAGE STORAGE0
500
1000
1500
2000
2500
3000
3500
Electricity Produc-tion [kW]
Electricity sold to the grid [kW]
Electricity bought from the grid [kW]
Fuel Consumption [kg]
Sustainable Place, 1-3 October, 2014, Nice, France 12
ConclusionsConclusions The Energy Hub was analysed via a thermo-economic approach
The impact of thermal storage was investigated, quantifying the impact on the system behaviour, both in energy and economic terms
Thermal storage allows to decrease the fuel consumption of 6% and to increase profits of 10%. However, such results are highly dependent on the energy demands.
In this work we use a simple marked-based approach, if we use a MPC to evaluate the rule of the thermal storage we could have an increase profits of 44%.
On going work
Implementation and testing of advanced predictive control algorithms
Comparison of different storage technologies (electrical, hot thermal, cold thermal)
Sustainable Place, 1-3 October, 2014, Nice, France
48 Modules available:• Cogenerative• Conventional• Renewable generators• Storage
Two optimization levels:• Management strategy optimization• Size optimization
WECoMPDemo version available
WECoMP is a software developed by TPG at University of Genoa for time-dependent thermo-economic analysis of energy systems
For more information:Site: www.tpg.unige.it/WECoMP.php
Email: [email protected]
Sustainable Place, 1-3 October, 2014, Nice, France
Thermochemical Power Group (TPG) - DIME – University of Genoa, Italy
Thermoeconomic optimization of an energy hub
Alessandra Cuneo Mario Luigi Ferrari
Alberto Traverso Aristide F. Massardo
Speaker: Alessandra Cuneo
Nice, 1 – 3 October 2014
