Vision of the Excess Electricity and Power-to-Gas in ...
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©Francois Marechal -IPESE-IGM-STI-EPFL 2014
IPESEIndustrial Process and
Energy Systems Engineering
Vision of the Excess Electricity and Power-to-Gas in Energyscope
Prof François Marechal EPFL Valais Wallis
CH-1950 Sion
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EPFL, CENStefano Moret January 21st, 2019 !2
What is energyscope ?The energyscope.ch project
Sources: [1] Swiss Federal Council. Perspectives Énergétiques 2050 - Analyse Des Variantes d’offre d’électricité Du Conseil Fédéral. May 2011. [2] Swiss Federal Office of Energy (SFOE). Swiss electricity statistics 2011. DE/FR. Tech. rep. Bern, Switzerland, 2012.
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EPFL, CENStefano Moret January 21st, 2019 !2
What is energyscope ?The energyscope.ch project
Fukushima, March 25th, 2011
Sources: [1] Swiss Federal Council. Perspectives Énergétiques 2050 - Analyse Des Variantes d’offre d’électricité Du Conseil Fédéral. May 2011. [2] Swiss Federal Office of Energy (SFOE). Swiss electricity statistics 2011. DE/FR. Tech. rep. Bern, Switzerland, 2012.
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EPFL, CENStefano Moret January 21st, 2019 !2
What is energyscope ?The energyscope.ch project
Fukushima, March 25th, 2011
Sources: [1] Swiss Federal Council. Perspectives Énergétiques 2050 - Analyse Des Variantes d’offre d’électricité Du Conseil Fédéral. May 2011. [2] Swiss Federal Office of Energy (SFOE). Swiss electricity statistics 2011. DE/FR. Tech. rep. Bern, Switzerland, 2012.
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How to fill this gap by 2035?
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EPFL, CENStefano Moret January 21st, 2019 !3
Energyscope
• Online platform energyscope.ch[1]
• Excel version of the model[2]
The energyscope.ch project
[1] S. Moret et al. “Swiss-EnergyScope.Ch: A Platform to Widely Spread Energy Literacy and Aid Decision-Making”. In: Chemical Engineering Transactions 39 (2014), pp. 877–882 [2] V. Codina Gironès et al. “Strategic Energy Planning for Large-Scale Energy Systems: A Modelling Framework to Aid Decision-Making”. In: Energy 90, Part 1 (Oct. 2015), pp. 173–186.
Dr V. Codina Gironès, EPFL
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EPFL, CENStefano Moret January 21st, 2019 !4
Energyscope
• Energy-based model
• “Snapshot” modeling approach: optimization of the system in a target future year
• Simplified yet complete energy system: inclusion of heating and mobility ! could complement more complex models
• Multiperiod formulation: seasonality of demand and energy storage
• Concise structure and low computational time ! uncertainty applications
A new mixed integer linear programming version
Sources: [1] S. Moret, F. Babonneau, M. Bierlaire, and F. Maréchal. “Decision support for strategic energy planning: a complete robust optimization framework ”, 2018 (Under review)
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EPFL, CENStefano Moret January 21st, 2019 !5
Energyscope
Why yet another energy model?[1]
• Most models are not open-source or are – at least partly – commercial
• Most model tend to focus only (or mostly) on the electricity sector
• Need of optimizing both investment & operation strategy in the system
• Complex formulation and high computational time ! difficult to consider uncertainty
Mixed Integer Linear Programming model : https://www.github.com/stefanomoret/SES_MILP
Sources: [1] S. Moret, F. Babonneau, M. Bierlaire, and F. Maréchal. “Decision support for strategic energy planning: a complete robust optimization framework ”, 2018 (Under review)
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©Francois Marechal -IPESE-IGM-STI-EPFL 2014
IPESEIndustrial Process and
Energy Systems Engineering
•Not Times-Markal – Transition is not modelled – Not economic equilibrium – Economic drivers are too uncertain •Not energyplan – Seasonality is considered – Optimisation instead of rule based – Solution generator instead of simulation • Fast Scenario generator
What is not energyscope!6
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EPFL, CENStefano Moret January 21st, 2019 !7
EnergyscopeApplication to Switzerland
Sources: [1] S. Moret, “Strategic energy planning under uncertainty”, 2017
• 20-year time horizon ! 2050 as target year
• Additional constraints for CH
• Model complexity: • 1633 decision variables • 118 binaries • 56 integers • Solved in seconds
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EPFL, CENStefano Moret January 21st, 2019 !8
EnergyscopeModel validation fitted with the SFOE data as reference
Sources: [1] S. Moret, “Strategic energy planning under uncertainty”, 2017
Model validation: Switzerland, year 2011
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©Francois Marechal -IPESE-IGM-STI-EPFL 2014
IPESEIndustrial Process and
Energy Systems Engineering
• Use of biomass to further decrease the CO2 emissions
• Deployment of PV panels
• 50% electricity is in excess during summer months. => seasonal storage is needed (& dams are not sufficient)
Integrating in the energy system
24/10/16
!9
NEP scenario
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©Francois Marechal -IPESE-IGM-STI-EPFL 2014
IPESEIndustrial Process and
Energy Systems Engineering
• BIO-SNG = operating 100%
• Power 2 gas takes the excess => new flexible system design
Wood Biomass for Renewable Electricity Storage
24/10/16
!10
Summer Mode
Winter Mode
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
GWh
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6000MW
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Elec. demand (GWh)Elec. supply (GWh)Wood in (MW)Elec. in (MW)Gas out (MW)
Installed power total WOOD (MW) = 1215
Electrolysis (MW) = 1755 Gas Production (MW) = 2065
SNG production (PJ) = 42.4 Wood consumption (PJ) = 38.3 Electricity storage (PJ) = 17.8
100 MW
75 MW
100 MW
170 MW
144 MW
Codina Gironès, Víctor, et al. "On the assessment of the CO2 mitigation potential of woody biomass." Frontiers in Energy Research 5 (2018): 37.
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©Francois Marechal -IPESE-IGM-STI-EPFL 2014
IPESEIndustrial Process and
Energy Systems Engineering
Annual Total Cost [109 CHF]
Annual
CO2 E
missions [106
kg C
O2-e
quiv.]
5
10
15
20
25
30
35
40
26 27 28 29 30
NEP
PM
BAU
38 39 40
F1P1 F1P4 F1P2 F1P3
• Design of new energy scenarios. Minimizing energy dependency of Switzerland : i.e. minimise the CO2 emissions
Wood Biomass for the energy transition
24/10/16
!11
New Energy Policies Scenario for 2050 as reference
100 PJ used
-38 % CO2 + 23 % cost
x4 x4 x1.52050 BAU scenario
2050 NEP scenario
-63 % CO2
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©Francois Marechal -IPESE-IGM-STI-EPFL 2014
IPESEIndustrial Process and
Energy Systems Engineering
• Design of new energy scenarios. Goal: Minimizing energy dependency of Switzerland + Not allowing import and export of electricity.
Wood Biomass for Renewable Electricity Storage
24/10/16
!12
• Increasing PV installed capacity. • Using of bio-SNG & electrolysis for electricity storage.
11 12 13 14 15 16 17 18 19 200
500
1000
1500
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PV installed capacity [GW]Annualized
investment cost [109 C
HF]
Elec PVChemical ConverisonDecentralized HPAdvanced Cogen.Decentralized Boiler
11 12 13 14 15 16 17 18 19 208.2
8.4
8.6
8.8
9
9.2
9.4
9.6
9.8
Annual
CO2 Em
issions [106
kgC
O−equiv.]
1
2
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100 PJ biomass used
x2 - x1.5 x2/3
Codina Gironès, Víctor, et al. "On the assessment of the CO2 mitigation potential of woody biomass." Frontiers in Energy Research 5 (2018): 37.
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©Francois Marechal -IPESE-IGM-STI-EPFL 2014
IPESEIndustrial Process and
Energy Systems EngineeringPower2gas perpsectives
!13
Figure 2: Conceptual Scheme of Boiler Design: plot (a) - Case I, plot (b) - Case II, plot (c) - Case III, plot(d) - Case IV
15
I II
III IV
6700 h/year
2000 h/year
Storing renewable electricity : Power to X
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EPFL, CENStefano Moret January 21st, 2019 !14
Energyscope & Energy storage : competing optionsApplication to Switzerland: JASM project
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EPFL, CENStefano Moret January 21st, 2019 !15
Energyscope
Latest developments: hourly resolution, storage (daily & seasonal, thermal & electrical), electric mobility (V2G)
Typical days version when hourly resolution needed
Sources: [1] G. Limpens et al, in preparation
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EPFL, CENStefano Moret January 21st, 2019 !16
EnergyscopeApplication to Switzerland: JASM project
Cost optimal
CO2 optimal
2015
Heat pumps
ElectrolysisGaseification
Synthetic fuels in public transport
]
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EPFL, CENStefano Moret January 21st, 2019 !17
EnergyscopeApplication to Switzerland: JASM project towards low CO2 emissions Switzerland
RERE
94 TWh
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EPFL, CENStefano Moret January 21st, 2019 !18
EnergyscopeCO2 emissions reduction
Sources: [1] Xiang Li et al, in preparation
cost uncertainty of the options
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EPFL, CENStefano Moret January 21st, 2019 !19
Generating different optionsDifferent assumptions leads to different solutions
6000 GWh Hydro storage storage 4 kt CO2/year
Electrical mobility
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EPFL, CENStefano Moret January 21st, 2019 !20
Power2gas energyscope vision
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©Francois Marechal -IPESE-IGM-STI-EPFL 2014
IPESEIndustrial Process and
Energy Systems Engineering
• EnergySCOPE is a solution generator –allows to show competing/synergetic/enabling options –allows to test assumptions
Conclusions!21