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Papers by Felix Steck
Effects of EV fleet charging representation on power system flexibility provision How do user-ori... more Effects of EV fleet charging representation on power system flexibility provision How do user-oriented EV fleet charging decisions affect the flexibility of future EV fleets and what implications does this have on cost-optimal power system results? Results Profiles for user-oriented (blue and pink) and power system oriented (green) EV charging modeling
Energy Challenges for the Next Decade,16th IAEE European Conference,August 25-28, 2019, Aug 25, 2019
Abbildung 1: Das wasserstoffbetriebene Brennstoffzellenauto des DLR-Instituts für Vernetzte Energ... more Abbildung 1: Das wasserstoffbetriebene Brennstoffzellenauto des DLR-Instituts für Vernetzte Energiesysteme galt im Februar 2017 als das erste in Niedersachsen verkaufte wasserstoffbetriebene Fahrzeug. Im Jahr 2030 könnten Prognosen der AG2 der Nationalen Plattform Mobilität zufolge bis zu 350.000 Brennstoffzellen-Pkw in Deutschland zugelassen sein. [14]
The expected increase in battery electric vehicles poses both, opportunities and risks for the de... more The expected increase in battery electric vehicles poses both, opportunities and risks for the decarbonisation of future power systems. While electric mobility may technically serve as a source of flexibility, it increases the overall power demand and may as well increase the demand for power in peak load hours. While electric mobility in national and continental scale energy system optimization is often treated in an aggregated fleet, user behaviour and charging decisions play a crucial role in the availability of vehicles' batteries for balancing electric load and renewable energy feed-in. Michaelis, Gnann & Klingler (2018) find that reduction of peak load and RE surplus electricity stemming from plug-in vehicles in Germany may be as high as 2.2 GW and 1.8 TWh respectively for 2030. However, they assume constant charging stations' power of 3.7 kW that seem conservative. Also, the authors don't explicitly describe to what effect user behaviour limits vehicle charging. B...
The transportation sector is responsible for 23% of total global energy-related CO2 emissions. Ac... more The transportation sector is responsible for 23% of total global energy-related CO2 emissions. Achieving environmental goals thus requires significant reductions in transportation emissions. These emissions are almost entirely from road transportation. Consequently, electric vehicles have been identified as a solution to mitigate transportation-related emissions. Significant research on electric vehicles has been conducted to date. A particular area lacking detailed study is the time-specific charging demand from electric vehicles and how this charging demand relates to time-specific renewable energy sources. This paper provides a detailed analysis of electric vehicle charging demand coupled with technology specific electricity supply. Using Germany as a case study, we determine total charging demand using a microscopic travel model. The model assumes that the use of electric vehicles is very similar to the use of conventional vehicles and that electric vehicles preferably charge wh...
Despite ambitious climate goals, the German transportation sector has failed to reduce emissions.... more Despite ambitious climate goals, the German transportation sector has failed to reduce emissions. As these emissions are dominated by personal vehicles, electric vehicles are central for achieving environmental objectives. To determine potential emission reductions from electric vehicles, a detailed analysis of the transportation and energy sectors is necessary. Thus we present a methodology to calculate charging demand of electric vehicles using a time and location specific microsimulation and probability estimation based on a utility function for charging behavior. The transportation model is coupled with a detailed energy model for Germany, which provides electricity generation per energy source on an hourly basis over a year. We apply the methodology and models to the case study of Germany in 2030 for five scenarios. The scenarios represent difference pricing schemes reflecting policy options for electric vehicles. The results show that charging demand can be shifted using marke...
Battery electric vehicles provide an opportunity to balance supply and demand in future power sys... more Battery electric vehicles provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users’ charging ...
Effects of EV fleet charging representation on power system flexibility provision How do user-ori... more Effects of EV fleet charging representation on power system flexibility provision How do user-oriented EV fleet charging decisions affect the flexibility of future EV fleets and what implications does this have on cost-optimal power system results? Results Profiles for user-oriented (blue and pink) and power system oriented (green) EV charging modeling
Energy Challenges for the Next Decade,16th IAEE European Conference,August 25-28, 2019, Aug 25, 2019
Abbildung 1: Das wasserstoffbetriebene Brennstoffzellenauto des DLR-Instituts für Vernetzte Energ... more Abbildung 1: Das wasserstoffbetriebene Brennstoffzellenauto des DLR-Instituts für Vernetzte Energiesysteme galt im Februar 2017 als das erste in Niedersachsen verkaufte wasserstoffbetriebene Fahrzeug. Im Jahr 2030 könnten Prognosen der AG2 der Nationalen Plattform Mobilität zufolge bis zu 350.000 Brennstoffzellen-Pkw in Deutschland zugelassen sein. [14]
The expected increase in battery electric vehicles poses both, opportunities and risks for the de... more The expected increase in battery electric vehicles poses both, opportunities and risks for the decarbonisation of future power systems. While electric mobility may technically serve as a source of flexibility, it increases the overall power demand and may as well increase the demand for power in peak load hours. While electric mobility in national and continental scale energy system optimization is often treated in an aggregated fleet, user behaviour and charging decisions play a crucial role in the availability of vehicles' batteries for balancing electric load and renewable energy feed-in. Michaelis, Gnann & Klingler (2018) find that reduction of peak load and RE surplus electricity stemming from plug-in vehicles in Germany may be as high as 2.2 GW and 1.8 TWh respectively for 2030. However, they assume constant charging stations' power of 3.7 kW that seem conservative. Also, the authors don't explicitly describe to what effect user behaviour limits vehicle charging. B...
The transportation sector is responsible for 23% of total global energy-related CO2 emissions. Ac... more The transportation sector is responsible for 23% of total global energy-related CO2 emissions. Achieving environmental goals thus requires significant reductions in transportation emissions. These emissions are almost entirely from road transportation. Consequently, electric vehicles have been identified as a solution to mitigate transportation-related emissions. Significant research on electric vehicles has been conducted to date. A particular area lacking detailed study is the time-specific charging demand from electric vehicles and how this charging demand relates to time-specific renewable energy sources. This paper provides a detailed analysis of electric vehicle charging demand coupled with technology specific electricity supply. Using Germany as a case study, we determine total charging demand using a microscopic travel model. The model assumes that the use of electric vehicles is very similar to the use of conventional vehicles and that electric vehicles preferably charge wh...
Despite ambitious climate goals, the German transportation sector has failed to reduce emissions.... more Despite ambitious climate goals, the German transportation sector has failed to reduce emissions. As these emissions are dominated by personal vehicles, electric vehicles are central for achieving environmental objectives. To determine potential emission reductions from electric vehicles, a detailed analysis of the transportation and energy sectors is necessary. Thus we present a methodology to calculate charging demand of electric vehicles using a time and location specific microsimulation and probability estimation based on a utility function for charging behavior. The transportation model is coupled with a detailed energy model for Germany, which provides electricity generation per energy source on an hourly basis over a year. We apply the methodology and models to the case study of Germany in 2030 for five scenarios. The scenarios represent difference pricing schemes reflecting policy options for electric vehicles. The results show that charging demand can be shifted using marke...
Battery electric vehicles provide an opportunity to balance supply and demand in future power sys... more Battery electric vehicles provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users’ charging ...