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A Spatio-temporal Optimization Model for the Analysis of Future Energy Systems with Power to Hydrogen Pathways

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A Spatio-temporal Optimization Model for the Analysis of Future Energy Systems with Power to Hydrogen Pathways

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A Spatio-temporal Optimization Model for the Analysis of Future Energy Systems with Power to Hydrogen Pathways

  1. 1. MitgliedderHelmholtz-Gemeinschaft Spatio-temporal Models for the Analysis of Future Energy Systems with Power to Hydrogen Pathways Martin Robinius, Lara Welder, Leander Kotzur Jochen Linßen, Peter Markewitz, Detlef Stolten m.robinius@fz-juelich.de 71th SEMI-ANNUAL ETSAP MEETING 10th July 2017, Washington DC Institute of Electrochemical Process Engineering (IEK-3)
  2. 2. Institute of Electrochemical Process Engineering 2 - The IEA HIA Task 38 - The Department of Process- and System Analysis (VSA) - Status of the “Energiewende” in Germany - Selected Highlights of the VSA - Simulation - Time Series Aggregation - Optimization Table of contents
  3. 3. Institute of Electrochemical Process Engineering 3 Over 50 experts from 34 organizations in 15 countries Major objectives: - To provide a comprehensive understanding of the various technical and economic pathways for power-to-hydrogen applications in diverse situations - To provide a comprehensive assessment of existing legal frameworks - To provide business developers and policy makers with general guidelines and recommendations that enhance hydrogen system deployment in energy markets The Task 38 of the IEA HIA Power-to-Hydrogen and Hydrogen-to-X: System Analysis of the techno-economic, legal and regulatory conditions M. Robinius, L. Welder, S. Ryberg, C. Mansilla, M. Balan, F. Dolci, R. Dickinson, R. Gammon, P. Lucchese, N.D. Meeks, A. Pereira, S. Samsatli, J. Simon, O. Tlili, S. Valentin, E. Weidner (2017): Power-to-Hydrogen and Hydrogen-to-X: Which markets? Which economic potential? Answers from the literature. 14th International Conference on the European Energy Market, Dresden Germany
  4. 4. Institute of Electrochemical Process Engineering 4 The Task 38 of the IEA HIA Power-to-Hydrogen and Hydrogen-to-X: System Analysis of the techno-economic, legal and regulatory conditions Subtask Subtask Name Subtask Leader Subtask Activities 1 Management, strategy and communication Paul Lucchese and Christine Mansilla, CEA, France - Involving new experts - Coordination (meeting organization, private website update, ST/TF activity follow-up) - Interfacing (IEA, HyLaw, Task 36, CEN/CENELEC) 2 Mapping and review of existing demonstration projects Joris Proost, Université Catholique de Louvain, Belgium - Review of existing databases - Proposal of a roadmap 3A Review and analysis of the existing techno- economic studies on PtH HtX Martin Robinius, Forschungszentrum Jülich, Germany - Literature review and analysis - Database establishment 3B Review of the existing legal context and policy measures Francesco Dolci, JRC, European Commission - Review of existing legal frameworks and policy measures - Database establishment for mapping relevant national legislation 4 Systemic approach Sheila Samsatli, University of Bath, United Kingdom - Analysis of energy system models - Outlook for hydrogen from a system perspective 5 Case studies Gema Alcalde and Carlos Funez, Centro Nacional del Hidrógeno, Spain - Identification and analysis of relevant case studies
  5. 5. Institute of Electrochemical Process Engineering 5 Who we are  Process and Systems Analysis (VSA) Head of Depatment: Dr.-Ing. Martin Robinius Renewable Energies, and Storage Infrastructures TransportResidental Sector Industry Areas of Expertise VSA: Jochen Linßen Dr.-Ing. Peter Markewitz Dr.-Ing. Thomas Grube
  6. 6. Institute of Electrochemical Process Engineering 6 - The IEA HIA Task 38 - The Department of Process- and System Analysis (VSA) - Status of the “Energiewende” in Germany - Selected Highlights of the VSA - Simulation - Time Series Aggregation - Optimization
  7. 7. Institute of Electrochemical Process Engineering 7 0 200 400 600 800 1.000 1.200 1990 1995 2000 2005 2010 GHGemissions CO2.-equivalent[Mt] The overall GHG emission goals of Germany require a holistic transformation of all sectors GHG Emissions in Germany since 1990 [1] Goals of the BRD in reference to 1990 [2] 60% 45% 30% 5-20% 2020 2030 2040 2050 [1] BMWi, Zahlen und Fakten Energiedaten - Nationale und Internationale Entwicklung. 2016, Bundesministerium für Wirtschaft und Energie: Berlin. [2] BRD, Energiekonzept für eine umweltschonende, zuverlässige und bezahlbare Energieversorgung, Bundeskabinett. 2010: Berlin. [3] UN, Paris Agreement - COP21, United Nations Framework Convention on Climate Change 2015: Paris. COP21 Paris [3] Mobility Industry and commerce Residential Others Power Sector 43% 34% 21% 15% 3% MobilityIndustry/ commerce Resi- dential Others Power Sector GHG emission reduction per sector 1990 to 2013 [1] The mobility sector lags behind in comparison to the achieved emission reductions of the other sectors. >2050 0%
  8. 8. Institute of Electrochemical Process Engineering 8 The National Climate Action Plan 2016 Source: Klimaschutzplan 2050 – Klimaschutzpolitische Grundsätze und Ziele der Bundesregierung vom 14.11.2016 1990 tCO2eq 2014 tCO2eq 2014 vs. 1990 Goals 2030 tCO2eq Goals 2030 vs. 1990 Conversion 466 358 - 23,2 % 175 - 183 62 – 61 % Buildings 209 119 - 43,1 % 70 - 72 67 – 66 % Transport 162 160 - 1,2 % 95 - 98 42 – 40 % Industry 283 181 - 36 % 140 - 143 51 – 49 % Agriculture 88 72 - 18,2 % 58 - 61 34 – 31 % Others 39 12 - 69 % 5 87 % Summe 1248 902 - 27,7 % 543 - 562 56 – 55%
  9. 9. Institute of Electrochemical Process Engineering 9 - The IEA HIA Task 38 - The Department of Process- and System Analysis (VSA) - Status of the “Energiewende” in Germany - Selected Highlights of the VSA - Simulation - Time Series Aggregation - Optimization
  10. 10. Institute of Electrochemical Process Engineering 10 VSA Highlights 10 [1] Otto, A., Robinius, M., Grube, T., Schiebahn, S., Praktiknjo, A., & Stolten, D. (2017). Power-to-Steel: Reducing CO2 through the Integration of Renewable Energy and Hydrogen into the German Steel Industry. Energies, 10(4), 451. [2] Welder, L., Ryberg, S., Kotzur, L., Grube, T., Robinius, M., & Stolten, D. (2017). Spatio-Temporal Optimization of a Future Energy System for Power-to-Hydrogen Applications in Germany (submitted) [3] Kotzur, L., Markewitz, P., Robinius, M., & Stolten, D. (2017). Impact of different time series aggregation methods on optimal energy system design (submitted) [4] Reuß, M., Grube, T., Robinius, M., Preuster, P., Wasserscheid, P., & Stolten, D. (2017). Seasonal storage and alternative carriers: A flexible hydrogen supply chain model. Applied Energy, 200, 290-302. Flexible hydrogen supply model [4] Aggregated time series [3] First Product: Open Software for time series aggregation Aggregated optimization model for industry and mobility sectors [2] Power-to-Steel [1]1 2 3 4
  11. 11. Institute of Electrochemical Process Engineering 11 - The IEA HIA Task 38 - The Department of Process- and System Analysis (VSA) - Status of the “Energiewende” in Germany - Selected Highlights of the VSA - Simulation - Time Series Aggregation - Optimization
  12. 12. Institute of Electrochemical Process Engineering 12 Assessment based on municipal level and an hourly resolution of grid load and RES feed-in RES power [GW | TWh]: onshore: 170 | 350; offshore: 59 | 231; PV: 55 | 47; hydro: 6 | 21; bio: 7 | 44 Further assumptions: grid electricity: 528 TWh; imports: 28 TWh; exports: 45 TWh; pos. residual: natural gas „Copper plate“ & 40 GWh pumped hydro: 191 TWh (→ 4.0 million tH2) Grid capacity constraints considered: 293 TWh (→ 6.2 million tH2) RES: Renewable Energy Sources All values after Robinius, M. (2016): Strom- und Gasmarktdesign zur Versorgung des deutschen Straßenverkehrs mit Wasserstoff. Dissertation RWTH Aachen University, ISBN: 978-3-95806-110-1 Electrical Grid 380 and 220 kV Conventional Power Plants Residual load Load ∑ RES (Example PV only) = - Neg. RL (Surplus) Positive residual load The Year 2050 – Energy Concept 2.0Power-Sector
  13. 13. Institute of Electrochemical Process Engineering 13 Linking the Power and Transport Sector Residual energy [MWh/km²] Negative residual energy (Surplus) Positive residual energy
  14. 14. Institute of Electrochemical Process Engineering 14 Energy Concept 2.0 Assessment based on county level FCV [kg/100 km]: 0.92 (2010) → 0.58 (2050) [1], linear decrease FCV fleet: curve fit; until 2033 according to [2]; maximum share in 2050: 75 % of German fleet Further assumptions: 14,000 km annual mileage 12 years lifetime; total vehicle stock: 44 million cars Peak annual H2 demand: 2.93 million tH2 (2052) (Surplus 2050 Copper plate scenario  4.0 million tH2) H2Demand/a All values after Robinius, M. (2016): Strom- und Gasmarktdesign zur Versorgung des deutschen Straßenverkehrs mit Wasserstoff and Tietze, V.: Techno-ökonomische Bewertung von pipelinebasierten Wasserstoffversorgungssystemen für den deutschen Straßenverkehr, to be published except: [1] GermanHy (2009), Scenario “Moderat” [2] H2-Mobility, time scale shifted 2 years into the future [3] Krieg, D. (2012), Konzept und Kosten eines Pipelinesystems zur Versorgung des deutschen Straßenverkehrs mit Wasserstoff. 0 0,5 1 1,5 2 2,5 3 0 5 10 15 20 25 30 35 40 0 - 3 3 - 4 4 - 5 5 - 6 6 - 8 8 - 11 11 - 19 19 - 30 30 - 45 45 - 148 Hydrogen Demand [103 t/a] FCV[Million] HydrogenDemand[Milliont] Peak-Year 2052 Number of cars Population density Useable income of private households … High Hydrogen Demand - Target is 75 % of total passenger cars are FCV  32.9 million FCV in 2050 - Reference points are based on H2Mobility # based on: S-Curve based on:
  15. 15. Institute of Electrochemical Process Engineering 15 Energy Concept 2.0 Assessment based on county level H2 sources: 28 GW electrolysis power in 15 districts in Northern Germany, 15 billion € H2 sinks: 9,968 refueling stations with averaged sales of 803 kg/d, 20 billion € H2 storage: 48 TWh (incl. 60 day reserve), 8 billion € Pipeline invest [3]: 6.7 billion € (12,104 km transmission grid); 12 billion € (29,671 km distribution grid) Electricity cost: LCOE Onshore: 5.8 ct/kWh; Total H2 cost (pre-tax): 17.5 ct/kWh WACC: 8 % Results All values after Robinius, M. (2016): Strom- und Gasmarktdesign zur Versorgung des deutschen Straßenverkehrs mit Wasserstoff. Dissertation RWTH Aachen University, ISBN: 978-3-95806-110-1; except: [3] Krieg, D. (2012), Konzept und Kosten eines Pipelinesystems zur Versorgung des deutschen Straßenverkehrs mit Wasserstoff. Forschungszentrum Jülich IEK-3 Transmission Hubs Distribution Neg. RL (Surplus) High Hydrogen Demand Electrolyzer Node Electrical line Countie with surplus
  16. 16. Institute of Electrochemical Process Engineering 16 8,9 8,4 3,4 1,3 3,3 1,9 0 4 8 12 16 20 24 Wind power (5,9 ct/kWh) Elektrolysis H2 at pump (appreciable cost) Gasoline (70 ct/l) Natural gas (2,5 ct/kWh) Wind powe (5,9 ct/kWh Electrolysi Grid feed- Costofhydrogen,ct€/kWh OPEX Interest cost Depreciation cost Energy cost H2 appreciable cost Gasoline/NG, pre tax 22 (0,7 kg/100km) 17,5 16* (1,0 kg/100km) 8.0 2.5 10,8 CAPEX via depreciation of investment plus interest  10 a for electrolysers and other production devices  40 a for transmission grid  20 a for distribution grid and refueling stations  Interest rate 8.0 % p.a. Other Assumptions:  2.9 million tH2/a from renewable power via electrolysis  Electrolysis: η = 70 %LHV, 28 GW; investment cost 500 €/kW  Methanation: η = 80 %LHV • Appreciable cost @ half the specific fuel consumption [1] Energy Concept 2.0 Hydrogen for Transportation Cost Comparison of Power to Gas Options – Pre-tax Hydrogen for Transportation with a Dedicated Hydrogen Infrastructure is Economically Reasonable
  17. 17. Institute of Electrochemical Process Engineering 17 - The IEA HIA Task 38 - The Department of Process- and System Analysis (VSA) - Status of the “Energiewende” in Germany - Selected Highlights of the VSA - Simulation - Time Series Aggregation - Optimization
  18. 18. Institute of Electrochemical Process Engineering 18 Impact of time series aggregation on optimal energy system design[1] Considered residential supply systems Prediction error of the system cost for different number of typical days [1] Kotzur, L., P. Markewitz, M. Robinius and D. Stolten (2017). Impact of different time series aggregation methods on optimal energy system design, Forschungszentrum Jülich, IEK-3 – UNPUBLISHED. Go to: https://github.com/FZJ-IEK3-VSA/tsam
  19. 19. Institute of Electrochemical Process Engineering 19 - The IEA HIA Task 38 - The Department of Process- and System Analysis (VSA) - Status of the “Energiewende” in Germany - Selected Highlights of the VSA - Simulation - Time Series Aggregation - Optimization
  20. 20. Institute of Electrochemical Process Engineering 20 Optimization Techno-economic data Cost parameters depending on the technology design Weather data Wind speeds and solar radiation Demand data For electricity and hydrogen, resolved on the district level Eligible land For wind turbines, pipelines, and salt caverns Case studies Thermodynamic modelling • Pressure drop along pipeline • Technology design and de- termination of operating limits Complexity reduction • Time series aggregation • Decomposition algorithms • Network reduction Spatio-Temporal Optimization Optimization output Energy system’s cost Capital and operational cost contribution from each technology Structure and design Placement and size of each technology for each considered region Operation Operation modes/ inventories of the technologies Recommendations Recommend feasible and cost- effective scenarios Point out value of key technologies min Total annual costs s.t. demand & technical con- straints are considered MethodologyInvestigated system Output • “The value of X” analyses (X not included in superstructure) • Sensitivity analyses , Figures from: Lara Welder, D. Severin Ryberg, Leander Kotzur, Thomas Grube, Martin Robinius, Detlef Stolten (2017): Spatio-Temporal Optimization of a Future Energy System for Power-to- Hydrogen Applications in Germany. (submitted) Robinius (2015) Strom- und Gasmarktdesign zur Versorgung des deutschen Straßenverkehrs mit Wasserstoff.
  21. 21. Institute of Electrochemical Process Engineering 21 Investigation of a green field scenario for a Power-to-Mobility (2.9 Mio. tH2/year) and Power- to-Industry (1.1 Mio. tH2/year) applications in Germany*. SELECTED RESULTS[1] Even when adding distribution costs (3.4 €/kgH2), costs are below current hydrogen price (9.5 €/kgH2) at German fueling stations. Value of salt caverns in the energy system: The costs increase by 1.5 €/kgH2 if the construction of salt caverns is prohibited during optimization. Optimization of a Future Energy System for “Power-to-Mobility” and “Power-to-Industry” Applications in Germany Illustrative optimization results[1] * Technology options: Onshore wind turbines, electrolyzers, salt caverns, vessels, pipelines. Demands: PtM 2.9 Mio. tH2/year, PtI (1.1 Mio. tH2/year), no electricity demand. [1] Lara Welder, D. Severin Ryberg, Leander Kotzur, Thomas Grube, Martin Robinius, Detlef Stolten (2017): Spatio-Temporal Optimization of a Future Energy System for Power-to- Hydrogen Applications in Germany. (submitted) Installed capacities: wind turbines 79.1 GW, electrolyzers 47.6 GW, salt caverns 10.3 TWh.
  22. 22. Institute of Electrochemical Process Engineering 22 Thank you for your attention Process and Systems Analysis (VSA) Dr. Martin Robinius Head of VSA m.robinius@fz-juelich.de Prof. Dr. Detlef Stolten Head of IEK-3 d.stolten@fz-juelich.de Dr. Bernd Emonts Deputy Head of IEK-3 b.emonts@fz-juelich.de Dr. Thomas Grube Transport th.grube@fz-juelich.de Jochen Linßen Infrastructure and Sector Coupling Dr. Peter Markewitz Stationary Energy Systems p.markewitz@fz-juelich.de

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