Analysis of the role of energy storages in Belgium and Netherlands with TIMES
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Analysis of the role of energy storages in Belgium and Netherlands with TIMES
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Analysis of the role of energy storages in Belgium and Netherlands with TIMES
- 1. Energy Storage Mapping And Planning Modelling Work Package Vito/EnergyVille Frank Meinke-Hubeny Larissa Pupo Nogueira de Oliveira Jan Duerinck IER Stuttgart Markus Blesl Julia Welsch ETSAP Workshop CIEMAT â Madrid 17.11.2016
- 2. Overview and Background ESTMAP project Frank Meinke-Hubeny, Vito/EnergyVille Evaluation of the role of energy storages in Europe with TIMES PanEU Markus Blesl and Julia Welsch, IER University of Stuttgart Analysis of the role of energy storages in Germany with TIMES PanEU Julia Welsch and Markus Blesl, IER University of Stuttgart Analysis of the role of energy storages in Belgium and Netherlands with TIMES Larissa P. N. de Oliveira and Jan Duerinck; Vito/EnergyVille Overview of Powerfys Model results (Ecofys) Frank Meinke-Hubeny, Vito/EnergyVille Discussion
- 3. GRAND ENERGY CHALLENGES ⢠Establish a clean, low carbon energy system based on renewable resources ⢠Ensure continuation of stable and high quality energy services ⢠Keep energy generation cost efficient and affordable for all EU citizens
- 4. ENERGY STORAGE IS A KEY ENABLER ⢠Flexibility for an energy system in which electricity generation increases ⢠Mitigation of consequences from increasing share of intermittent energy sources ⢠Solutions for declining base load and shift to decentralized generation
- 5. Energy Storage Mapping And Planning Key knowledge and information on Europeâs energy storage potential Spatial energy storage database for electricity, gas and heat technologies Case demonstration of European energy systems analysis and planning Contribute to Energy Storage development
- 7. TANKS LAKES RESERVOIRS SALT HOST ROCK AQUIFERS MODULAR ESTMAP DATA SCOPE PUMPED HYDRO STORAGE NATURAL GAS STORAGE HYDROGEN STORAGE HYDROGEN STORAGE NATURAL GAS STORAGE COMPRESSED AIR ENERGY STORAGE NATURAL GAS STORAGE THERMAL ENERGY STORAGE COMPRESSED AIR ENERGY STORAGE UNDERGROUND PUMPED HYDRO STORAGE BATTERIES FLYWHEEL CAPACITATORS LNG HYDROGEN STORAGE UNDERGROUND THERMAL ENERGY STORAGE Reservoirs Technologies Subsurface / Above ground Existing / Potential Electricity, Gas, Heat
- 9. Above ground data collection (PHS)
- 10. Geographical energy storage database > 4200 potential and proven natural energy storage capacities > 700 planned and developed energy storage facilities Number of potential storage sites
- 11. Schematic overview of interrelations in Modelling WP
- 12. Flow of information for energy systems analysis and planning DBase ESTMAP Geographical database Salt Formation depth height area Select potentially suitable reservoirs for analysis input Storage site and reservoirs database reservoir characteristics Salt Formation Define notional storage facilities per technology Site characterization Feasibility determination Reservoir properties Generic technical design parameters Site-specific performance parameters Analysis input deck Future potential capacities + Proven capacities in existing facilities intake discharge efficiency capex opex etc.
- 13. GIS, TIMES and PowerFys have been combined to demonstrate potential analysis on ESTMAP database Database GIS mapping TIMES model PowerFys model Description ⢠Compile a database with existing and future potential energy storage ⢠Integrate contributions from geological and technical institutes and open source information ⢠EU ⢠Calculate connection costs for future storage facilities ⢠Develop storage maps depicting analysis results, after TIMES and PowerFys model runs TIMES PanEU: ⢠Optimize configuration of storage sites & power plants ⢠Time resolution of day, night and peak time slices ⢠EU-28, NO, CH ⢠2010 â 2050 TIMES regional: ⢠Time resolution of 280 (GER) and 60 (BE & NL) time slices ⢠DE, BE & NL ⢠Optimize operation of energy storage and power generation assets ⢠Optimize storage use ⢠Assess cross- border electricity flow & congestion ⢠Calculate marginal energy costs ⢠Hourly resolution ⢠DE, BE and NL ⢠2050 Outcomes ⢠Storage locations ⢠Storage specifications ⢠Storage connection costs ⢠Optimal configuration of storage sites and power plants ⢠Hourly storage use ⢠Generation mix ⢠Marginal costs
- 14. Scenario Definitions 2030 2050 Combined binding emissions target (2030) Renewable target 2030 Combined emissions target (2050) Renewable target 2050* % vs. 1990 % gross final energy consumption % vs. 1990 % gross final energy consumption EU -40% 27% -80% 75%* Sources: (COM, 2013 (169)) and (COM, (2011) 885) Note: * based on 'High Renewable Energy Sources (RES)' scenario, Roadmap 2050 Baseline Scenario PV Scenario ⢠Predefined PV generation capacity : 50% higher compared to the baseline results in 2050 BattCost Scenario Baseline Scenario BattCost Scenario Investment costs Investment costs 2010 2050 2010 2050 Battery Lithium Ion Input 100 ⏠đđ 30 ⏠đđ 100 ⏠đđ 60 ⏠đđ Battery Lithium Ion Storage 752 ⏠đđđ 85 ⏠đđđ 752 ⏠đđđ 170 ⏠đđđ Battery Lithium Ion Output 100 ⏠đđ 30 ⏠đđ 100 ⏠đđ 60 ⏠đđ General Assumption ⢠Spirit of a true âEnergy Unionâ till 2050 ⢠Guidance from EU policy H2020, Roadmaps 2030 and 2050
- 15. Further information about ESTMAP ⌠⢠Vito, IER ⢠Project Flyer ⢠Website (http://estmap.eu) Frank Meinke-Hubeny frank.meinke-hubeny@vito.be Larissa Pupo Nogueira de Oliveira larissa.oliveira@vito.be Jan Duerinck jan.duerinck@vito.be
- 16. Overview and Background ESTMAP project Frank Meinke-Hubeny, Vito/EnergyVille Evaluation of the role of energy storages in Europe with TIMES PanEU Markus Blesl and Julia Welsch, IER University of Stuttgart Analysis of the role of energy storages in Germany with TIMES PanEU Julia Welsch and Markus Blesl, IER University of Stuttgart Analysis of the role of energy storages in Belgium and Netherlands with TIMES Larissa P. N. de Oliveira and Jan Duerinck; Vito/EnergyVille Overview of Powerfys Model results (Ecofys) Frank Meinke-Hubeny, Vito/EnergyVille Discussion
- 17. Belgium and Netherlands TIMES Model - Methodology: Temporal resolution Jan Duerinck
- 18. Belgium and Netherlands TIMES Model - Methodology and Results Larissa Pupo Nogueira de Oliveira
- 19. Methodology Main Structure for Storage Processes BE & NL: disaggregated approach DE & PanEU: aggregated approach~FI_Process Sets Region TechName TechDesc Tact Tcap Tslvl *Process Set Membership Region Name Technology Name Technology Description Activity Unit Capacity Unit TimeSlice level of Process Activity .ELE.CEN.TCH.STGTSS. BE STGSPH1L1 FFAC_PHS_1LAKE_001 - Storage PJa PJa DAYNITE .ELE.CEN.TCH.STGTSS. NL STGSLCSA245 FFAC_LCCAES_SALT_245 - Storage PJa PJa DAYNITE .ELE.CEN.TCH.STGTSS. NL STGSLCSA246 FFAC_LCCAES_SALT_246 - Storage PJa PJa DAYNITE .ELE.CEN.TCH.STGTSS. NL STGSLCSA247 FFAC_LCCAES_SALT_247 - Storage PJa PJa DAYNITE .ELE.CEN.TCH.STGTSS. NL STGSLCSA248 FFAC_LCCAES_SALT_248 - Storage PJa PJa DAYNITE .ELE.CEN.TCH.STGTSS. NL STGSLCSA249 FFAC_LCCAES_SALT_249 - Storage PJa PJa DAYNITE ⌠.PRE.CEN.TCH.STGTSS. NL STGSUGRE307 FFAC_UGS_RES_307 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSUGRE308 FFAC_UGS_RES_308 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSUGRE309 FFAC_UGS_RES_309 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSUGRE310 FFAC_UGS_RES_310 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSUGRE311 FFAC_UGS_RES_311 - Storage PJa PJa DAYNITE ⌠.PRE.CEN.TCH.STGTSS. NL STGSUGSA245 FFAC_UGS_SALT_245 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSUGSA246 FFAC_UGS_SALT_246 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSUGSA247 FFAC_UGS_SALT_247 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSUGSA248 FFAC_UGS_SALT_248 - Storage PJa PJa DAYNITE ⌠.PRE.CEN.TCH.STGTSS. NL STGSH2SA245 FFAC_H2_SALT_245 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSH2SA246 FFAC_H2_SALT_246 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSH2SA247 FFAC_H2_SALT_247 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSH2SA248 FFAC_H2_SALT_248 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSH2SA249 FFAC_H2_SALT_249 - Storage PJa PJa DAYNITE .PRE.CEN.TCH.STGTSS. NL STGSH2SA250 FFAC_H2_SALT_250 - Storage PJa PJa DAYNITE ~FI_Process Sets TechName TechDesc Tact Tcap Tslvl .ELE.CEN.TCH.STGTSS. EUSTGPSN01 Pump Storage PJ PJa Daynite .ELE.CEN.TCH.STGTSS. EUSTGPSN01_S Pump Storage Seasonal PJ PJa Season .ELE.CEN.TCH.STGTSS. EUSTGCAESADIA01 CAES adiaba (salt caverns) PJ PJa Daynite .ELE.CEN.TCH.STGTSS. EUSTGCAESDIA01 CAES diabat (salt caverns) PJ PJa Daynite .ELE.CEN.TCH.STGTSS. EUSTGCAESADIA01_O CAES adiabat (tanks) PJ GW Daynite -Database can be used with both approaches! - In addition to the exercise of evaluating regions with different dimensions and potentials.
- 20. Methodology Storage Potential Database Pump Storage â one reservoir Pump Storage â two reservoir Country Potential [GWh] Connecting Cost ďż˝ ⏠đđđđ ďż˝ Country Potential [GWh] Connecting Cost ďż˝ ⏠đđđđ ďż˝ AT 409 6,2 IE 30 5,9 BE 0 - IT 1.626 6,7 BG 378 6,9 LT 0 - CH 0 - LU 0 - CY 51 5,7 LV 0 - CZ 183 6,5 MT 0 - DE 297 6 NL 0 - DK 0 - NO 6.616 23,5 EE 0 - PL 47 5 ES 0 - PT 1.229 4,4 FI 104 8 RO 0 - FR 1.913 5,2 SE 1.098 11,6 GR 288 11,6 SI 18 5,6 HR 291 7,5 SK 0 - HU 3 5,5 UK 1.702 8,4 Country Potential [GWh] Connecting Cost ďż˝ ⏠đđđđ ďż˝ Country Potential [GWh] Connecting Cost ďż˝ ⏠đđđđ ďż˝ AT 16 6,2 IE 0 - BE 0 - IT 86 7,7 BG 0 - LT 0 - CH 0 - LU 0 - CY 0 - LV 0 - CZ 3 6 MT 0 - DE 5 15,2 NL 0 - DK 0 - NO 212 11,7 EE 0 - PL 0 - ES 0 - PT 28 5,6 FI 0 - RO 0 - FR 49 2,9 SE 0 - GR 0 - SI 0 - HR 0 - SK 0 - HU 0 - UK 85 4
- 21. Methodology Storage Potential Database Compressed Air Natural Gas Country Potential [GWh] Connecting Cost ďż˝ ⏠đđđđ ďż˝ Country Potential [GWh] Connecting Cost ďż˝ ⏠đđđđ ďż˝ BG 5,4 6 NL 30 7,7 DE 575 7,9 PL 3 16,6 DK 32 8,6 GR 19 21,7 RO 22 8,4 Country Potential reservoir [million m 3 ] Potential cavern [million m 3 ] Country Potential reservoir [million m 3 ] Potential cavern [million m 3 ] AT 9.264 0 GR 0,002 4.000 BG 0 1.460 IT 8.863 0 DE 172.000 221.000 HU 29.011 0 DK 0 12.000 NL 65.250 12.000 DE 0 0 PL 2.000 4.000 DK 0 0 RO 3.000 8.000 HR 25 0 SI 306 0 UK 34 0,004
- 22. Optimized electricity output of power plants in Belgium -20 0 20 40 60 80 100 120 Statistics Base Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost 2010 2015 2020 2025 2030 2035 2040 2045 2050 TWh Net Electricity ElectricityStorage(excl.PumpHydro) Netimports Others/Wastenon-ren. Hydrogen OtherRenewables Biomass/Wasteren. Solar Windoffshore WindOnshore Hydro(incl.PumpStorage) Nuclear GasCCS Gasw/oCCS Oil LigniteCCS Lignitew/oCCS CoalCCS Coalw/oCCS ⢠Major transition in the years from 2020 to 2030, during phase out of nuclear generation ⢠Nuclear phase out is compensated mainly through ⢠Increase in gas generation plant output, ⢠Decline in energy demand and ⢠Massive increase in net energy import from neighbouring countries
- 23. Optimized electricity capacity of power plants in Belgium 0 5 10 15 20 25 30 35 40 45 50 Statistics Base Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost 2010 2015 2020 2025 2030 2035 2040 2045 2050 GW Capacity ElectricityStorage(excl.PumpStorage) Others/Wastenon-ren. OtherRenewables Biomass/WasteRen. Solar Wind Hydro(incl.PumpStorage) Nuclear NaturalGas Oil Lignite Coal ⢠Overall capacity increases from 2030 to 2050 ⢠Most growth can be attributed to the increasing wind generation capacity ⢠âImposedâ higher PV generation capacity (MorePV scenario) results in a reduction of 2 GW of wind capacity (14 GW in baseline scenario to 12 GW in MorePV scenario) ⢠Majority of additional PV capacity does not replace other RES capacity, but is added to overall capacity
- 24. 0 1 2 3 4 5 6 7 8 9 10 Statistics Base Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost 2010 2015 2020 2025 2030 2035 2040 2045 2050 GWh Storage Content Pump Storage Optimized amount and types of storage sites in Belgium ⢠New capacity in electrical storage output does not play a role in Belgium in the model results ⢠Storage is limited to the existing pumped hydro storage with a steady 6.5 GWh of storage content
- 25. Optimized electricity output of power plants in Netherlands -20 30 80 130 180 230 Statistics Base Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost 2010 2015 2020 2025 2030 2035 2040 2045 2050 TWh Net Electricity ElectricityStorage(excl.PumpHydro) Netimports Others/Wastenon-ren. Hydrogen OtherRenewables Biomass/Wasteren. Solar Windoffshore WindOnshore Hydro(incl.PumpStorage) Nuclear GasCCS Gasw/oCCS Oil LigniteCCS Lignitew/oCCS CoalCCS Coalw/oCCS ⢠Netherlands largely differs from the Belgium - only 4 TWh originate from nuclear generation ⢠Majority of generated by gas and coal plants in base year ⢠Transition to a more RES based energy system starts with offshore wind energy, in later years onshore wind and solar generation ⢠Net transfer capacity from the year 2035 onwards (approx. 12 TWh in 2035, increasing to 19-20 TWh in 2040, 21 TWh in 2045 approximately)
- 26. Optimized electricity capacity of power plants in Netherlands 0 10 20 30 40 50 60 70 80 90 100 Statistics Base Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost 2010 2015 2020 2025 2030 2035 2040 2045 2050 GW Capacity ElectricityStorage(excl.PumpStorage) Others/Wastenon-ren. OtherRenewables Biomass/WasteRen. Solar Wind Hydro(incl.PumpStorage) Nuclear NaturalGas Oil Lignite Coal ⢠Transition to a more RES based energy system starts with ⢠Growing share of offshore wind energy, ⢠Onshore wind and solar generation in later years
- 27. Optimized amount and types of storage sites in Netherlands 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Statistics Base Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost 2010 2015 2020 2025 2030 2035 2040 2045 2050 GWh Storage Content Battery Redox Flow Battery Lead Acid Battery Lithium Ion CAES Adiabatic CAES Diabatic Pump Storage ⢠Reliance on import goes hand in hand with no investments in storage capacities ⢠Exception being results in the MorePV scenario ⢠Lithium-ion storage content in the year 2050 of 0.28 GWh
- 28. Optimized amount and types of storage sites in Netherlands ⢠Hydrogen storage is chosen in the Dutch context ⢠For 2050 H2 storage of approximately 13 GWh in the Base and BattCost scenario ⢠18 GWh in the MorePV scenario ⢠Potential sites for hydrogen storage are based on the ESTMAP database. 0 2 4 6 8 10 12 14 16 18 20 Statistics Base Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost Base MorePV BatteryCost 2010 2015 2020 2025 2030 2035 2040 2045 2050 GWh H2 Storage Content H2 Storage
- 29. Germany, Belgium & Netherlands Model - PowerFys dispatch model (Ecofys) Frank Meinke-Hubeny
- 30. Schematic representation of the inputs and outputs of the PowerFys model
- 31. PowerFys â Adaptation of the load variation curve Snapshot of the first week of January 2050, Germany
- 32. date 05-Jun 06-Jun 07-Jun 08-Jun MW 10 4 -2 0 2 4 6 8 10 12 20160720_Baseline_update_v2 - DE+NL+BE elektra Storage release RE Oil OilCC Coal Lignite Gas GasCC curt. RE Storage filling Curtailment Load PowerFys Example of power dispatch for a three-day period in June
- 33. PowerFys Destination of surplus renewables % of total renewable generation 0 2 4 6 8 10 12 14 16 18 20 TOTAL BE NL DE 20160720_Baseline_update_v2 - Surplus Renewables avoided curtailment - to export avoided curtailment - to storage curtailment
- 34. TIMES analysis in the context of large scale energy storage Challenges / Critical self-reflection ⢠Underestimation of LSES demand due to low time slice resolution and âlast moment investments (e.g. >2040) ⢠Avoidance of âmarginally expensiveâ technologies, like storage, due to âperfect foresightâ ⢠Secondary business cases or âirrational behaviourâ only implemented as exogenous input ⢠Interaction with electricity market price difficult to model ⢠Transmission capacity investments are used in multi- region models and compete (or replace?) storage in small countries (like Belgium)
- 35. TIMES analysis in the context of large scale energy storage Lessons learned ⢠Various storage technologies play a role in the outcomes â the mix is important and country-specific ⢠Not a âone solution fits allâ result ⢠âCompetitionâ among technologies play a key role - see GER example ⢠Need for a better understanding of the energy systems: Power - Heat â Storage - Flexibility/DSM ⢠Transmission capacity and willingness for an Energy Union have a significant impact on small countries (BE) ⢠Knowledge of current and future technologies is key (solar, wind, storage, âŚ): Technical, Economic, Potential aspects