Energy System Modelling A Comprehensive Approach to Analyse Scenarios of a Future European Electricity Supply System Stefan Weitemeyer November 12 th, 2012 IRES 2012 Berlin PhD project in co-operation with
I. Outline 1. NEXT ENERGY 2. Background & Motivation 3. Current State of Research 4. Modelling: MOSES 5. First Results 6. Summary & Outlook Windpark Nysted (DK) Source: Siemens 2
1. NEXT ENERGY: Energy Research for the Future Founded in March 2007 as an independent Research Institute at the Uni OL About 90 employees in R&D and administration Research in the fields of Renewable Energy, Energy Infrastructure and Energy Efficiency 3
1. NEXT ENERGY: Energy Research for the Future Founded in March 2007 as an independent Research Institute at the Uni OL About 90 employees in R&D and administration Research in the fields of Renewable Energy, Energy Infrastructure and Energy Efficiency Photovoltaics Energy Storage Fuel Cells Energy system modelling combines these research areas 4
2. Background & Motivation Reducing greenhouse gas emissions to counteract climate change Improving energy efficiency Transformation to a reliable European power supply system based on Renewable Energies EU - Roadmap 2050 (2011):» Efficiency target for 2020: Reduce primary energy consumption by 20% compared to projections (Europe 2020 strategy)» Share of RES in electricity consumption will rise to 60-80% by 2050» Renewables will play important role for future energy supply 5
2. Background & Motivation Demand for backup power grows with higher share of RE EU-27 today: 16% EE [1] 582 197 +64% IEA: Power demand rises by 40% 2050: 40% RES [2] 2050: 80% RES [2] Backup/Storage: 45% of today s fossil/nuclear 420 generation capacity 140 270 190 670 1610 Total: 70% of today s fossil/nuclear generation capacity: costly 0 500 1000 1500 2000 2500 Capacity [GW] Capacity fossil/nuclear Capacity backup Capacity RES Data sources: [1] EU energy and transport in figures 2010, EU 2010 [2] Roadmap 2050, ECF 2010 6
3. Current State of Research Alternatives Storage Optimised mix Grid expansion Overcapacities DSM (Smart Grids) Source: T. Feck, Presentation in Bosch-Forschungs-Kolloquium, 17.03.11, ISEA, http://www.isea.rwth-aachen.de/de/energy_storage_systems_technology_redox_flow_batteries/, 21.11.11 7
3. Current State of Research Optimised mix Mix: 60% Wind, 40% Solar Left: Normalised power production from wind (blue), solar (orange) and demand (red) over a period of 8 years in Europe. Right: Combination of power production from wind and solar with a ratio of 60%/40% (green). Source: Heide et al. / Renewable Energy (2010) 8
3. Current State of Research Alternatives Storage Optimised mix Grid expansion Overcapacities DSM (Smart Grids) Interactions between different system components & security analysis Modelling / Simulations Source: T. Feck, Presentation in Bosch-Forschungs-Kolloquium, 17.03.11, ISEA, http://www.isea.rwth-aachen.de/de/energy_storage_systems_technology_redox_flow_batteries/, 21.11.11 9
4. Modelling: MOSES RE portfolio Scenarios EU-2050 Electricity demand Long-term meteorological data Grid model DSM Storage Grids Source: T. Feck, Presentation in Bosch-Forschungs-Kolloquium, 17.03.11 10
4. Modelling: MOSES Some details» Wind power / solar radiation data: 10x10 km², 10 years (Univ. Oldenburg)» DC grid model» No economic optimization Simulation runs for chosen set of parameters» Sensitivity analysis» Study national strategies in European context» Provide recommendations to policy makers 11
5. First Results Optimised mix 100% wind-and-solar-only scenario for Eastern Germany (TSO: 50hertz) Usage of real production (wind and PV) and load data for 2011 Mismatch energy Δ: a: wind fraction, W: wind, S: solar, L: load, < > yearly average Variation of parameter a: 0 100% Standard deviation σ Δ as an indicator for minimum storage / optimum mix Calculation also for daily and weekly averages 12
5. First Results Time resolution has influence on results σ Δ a / % Different share (a) depending on time resolution No conclusions regarding needed energy 13
6. Summary & Outlook Recent studies indicate that 100%-RE-scenario is realistic High cost: need to reduce storage or backup capacities Simulations allow to study interactions and synergies between system components 14
6. Summary & Outlook Open questions:» What is the optimum mix of RES to reduce backup capacities?» Can the expansion of the European transmission grid significantly reduce the demand for storage capacities?» Over-capacities vs backup capacities: where is the optimum?» To what extent can intelligent methods like demand-side management contribute to a reduction of storage capacities?» How does the large-scale import of solar energy from the MENA region or wind energy from offshore regions change the demand for storage? 15
Thank you for your attention Questions? Comments? Suggestions? 16
Appendix 17
A1. Storage Costs Case Description Cost - today - Cost - future - 1 Long-term storage / weekly (e.g. Hydrogen, CAES) 2 Load-Leveling / hourly Transmission grid (e.g. NaS, Li-Ionen, Redox-Flow) 3 Peak-Shaving Medium voltage (e.g. NaS, NaNiCl, Lead, Li-Ionen) 4 Peak-Shaving Distribution grid (e.g.. NaS, NaNiCl, Lead, Li-Ionen) 24-38 ct/kwh 9-22 ct/kwh (> 10 yrs) Appendix 19-50 ct/kwh 8-20 ct/kwh (5-10 yrs) 13-30 ct/kwh 5-14 ct/kwh (5-10 yrs) 16-38 ct/kwh 6-16 ct/kwh (5-10 yrs) Data source: VDE -Studie, Energiespeicher im Stromversorgungssystem mit hohem Anteil erneuerbarer Energieträger (2009) 18
A2. Current State of Research Optimised mix requires transmission capacities between countries 19
A3. Current State of Research Grid expansion Backup demand / Annual energy turnover 0,45 0,4 0,35 0,3 0,25 0,2 0,15 0,1 0,05 0 100%RE-Scenario / copper plate 25km 100%RE-Scenario / copper plate 3000km 0h 1h 4h 12h 1d 7d 30d Storage capacity / time average demand Data source: Presentation Dr. Clemens Hoffmann, Siemens AG, IRES 2010 20