IMPACT OF DIFFERENT CHARGING STRATEGIES OF ELECTRIC VEHICLES ON THE GERMAN GRID

Transcription

1 IMPACT OF DIFFERENT CHARGING STRATEGIES OF ELECTRIC VEHICLES ON THE GERMAN GRID Niklas Hartmann E. Doruk Özdemir Institute of Energy Economics and the Rational Use of Energy, University of Stuttgart N. Hartmann

2 University of Stuttgart Hamburg Faculty of Energy Technologies, Process Engineering and Biological Engineering Berlin Cologne GERMANY Leipzig Institute of Energy Economics and the Rational Use of Energy IER Frankfurt Mannheim Stuttgart BADEN - WÜRTTEMBERG Munich Dept. TFU Prof. Dr. Rainer Friedrich Technology Assessment and Environment Dept. SEE Dr. Ludger Eltrop System Analysis and Renewable Energies Dept. ESA Dr. Ulrich Fahl Energy Economics and Systems Analysis Dept. EGA Ingo Ellersdorfer Energy Markets and Economic Assessments N. Hartmann

3 System Analysis and Renewable Energies (SEE) Technological, economical and ecological analysis of renewable energies (biomass, biofuels, wind, geothermal energy, solar, etc.) including potential assessment Focus Bioenergy: assessment of competing bioenergy options, worldwide biomass production and use, biogas and biofuels Analysis of renewable energies in energy systems particularly villages and cities; methods for energy planning with use of renewable energies Renewable energies and sustainable development in developing countries Monitoring of renewable energy plants and applications, information and technology transfer N. Hartmann

4 IER Energy-Environment-Economy Models Energy System Electricity System TIMES-EU Technology E-Cost (LLCEC) E2M2S Energy-Economy TIMES Bavaria, Saxonia, Hessen, Baden-Württ. Balance (LCA) JMM Germany LEMI EU Environmental System NEWAGE World (TIAM) Resources Balance (LCA) LOPEX EcoSense (External Costs) N. Hartmann

5 Introduction Approach Simulation results Summary and conclusion N. Hartmann

6 Aim in Germany to produce 20-30% of the electrical generation capacity with renewable energies in the year A massive offshore development of wind farms is unavoidable to reach the goal. In the year 2030 the installed wind power (onshore and offshore) will rise to about 65 GW in Germany Power [MW] 35,000 30,000 25,000 20,000 15,000 10,000 5,000 Power Onshore Power Offshore Power generation total Power generation [TWh] WindEnergy Study N. Hartmann

7 The main challenge is to integrate the fluctuating wind power into the grid. Fluctuations of 65 GW Wind energy compared to the system load in Germany in ,000 70,000 60,000 System load Germany Power wind farm Power [MW] 50,000 40,000 30, ,000-4,000 20,000 10, Mo 361 Tue 385 We 409 Thu 433 Fr 457 Sa 481 Su505 Mo529 Hour N. Hartmann

8 The main challenge is to integrate the fluctuating wind power into the grid. Storage facilities can balance the fluctuating character of renewable electricity generation. Stationary storage is available basically throughout the day e.g. pumped hydro, compressed air, stationary battery Mobile storage systems are only available when they are connected to the grid When is the mobile storage available to the grid? How do Electric vehicles influence the demand in Germany (unmanaged charging vs. managed charging)? How high is the storage potential from EVs to integrate renewable Energy in Germany? N. Hartmann

9 Introduction Approach Simulation results Summary and conclusion N. Hartmann

10 Plug-in availability of passenger vehicles in Germany A vehicle which is standing is plug-in available Calculations are preformed in hourly time steps Data from the survey Mobilität in Deutschland Division into different modes of transport Division into seven motives for travelling In Germany: About 80 Mio people and about 46 Mio passenger vehicles N. Hartmann

11 Introduction Approach Simulation results Summary and conclusion N. Hartmann

12 Share of passenger cars en route of an average week Maximal about 10% of passenger cars en route at the same time. Peak in the afternoon at around 4 pm. Saturdays the peak shifts to the morning (10 am), Sundays at noon plug-in availability in Germany is high at any time over the day (> 90 %) N. Hartmann

13 Driven vkm of 1,000,000 passenger cars for an average week Travel time < 30 min High amount of vkm with the motive Work and Shopping N. Hartmann

14 Driven vkm of 1,000,000 passenger cars for an average week Travel time >: < 1h 30 min 30 min High amount of vkm with the motive Work and Leisure N. Hartmann

15 Driven vkm of 1,000,000 passenger cars for an average week Travel time > 1 h 30 min High amount of vkm with the motive Business trip and Leisure N. Hartmann

16 Energy demand for different number of Evs in Germany (unmanaged charging) Hour of week (Monday through Sunday) [h] Times of charging of Evs correlate with high demand times Charging of low number of Evs hardly impact the demand N. Hartmann

17 Energy demand for different number of Evs in Germany (managed charging) Monday through Sunday Improvement of the energy demand between charging with an optimized charging strategy and the energy demand without the impact of EVs is only 0.64 % for 1 million Evs (Least suare method) Potential to support the grid is high with large number of vehicles introduced in Germany N. Hartmann

18 Impact of EVs on the integration of wind power in Germany Power [GW] / capacity [GWh] With about 6 mil. Evs, the charging/discharging power is equal to the maximum positiv power difference of windpower minus demand. Even with 42 mil. EVs, the maximum charging/discharging capacity difference of windpower minus demand of one day can not be met. However the average capacity difference is reached for about 8 mil. EVs N. Hartmann

19 Introduction Approach Simulation results Summary and conclusion N. Hartmann

20 Low daily variation of passenger cars en route (about 10%) but difference between weekdays Saturdays and Sundays. On weekdays a maximum of 11 % of passenger cars are en route (at 4 pm) On Saturdays the peak shifts to the morning (at 10 am) On Sundays about only about 6 % of passenger cars are en route Influence of charging EVs on the grid With low number of EVs introduced, they hardly alter the demand However times of charging and high demand correlate Managed charging of EVs is needed only for a large number of EVs High potential for the integration windpower EVs can contribute to the integration of flucutation renewable energy, but only on a short time basis (daily power and energy shifting rather than long term shifting) N. Hartmann

21 Thanks to the Reiner Lemoine Foundation in Germany for supporting the work Thanks for your attention! N. Hartmann