: Virtual Power Plants of Electric Vehicles in Sustainable Smart Electricity Markets Defended on Friday, 15 September 2017
The batteries of electric vehicles can be used as Virtual Power Plants to balance out frequency deviations in the electricity grid. Carsharing fleet owners have the options to charge an electric vehicle's battery, discharge an electric vehicle's battery, or keep an electric vehicle idle for potential rentals. Charging and discharging can be used to provide reliable operating reserves.
We develop an analytical model that manages carsharing fleets. On the one hand, the energy in the batteries of an electric vehicle can be made available to the grid as operating reserves. On the other hand, the electric vehicle can be made available for rental, where the location within the city matters: drivers want a car to be close to their place of departure or arrival. The model can also be used by Transportation Network Companies such as Uber to preposition their vehicles conveniently in a city or optimize zonal pricing.
To validate our model we develop a Discrete Event Simulation platform. We calibrate this simulation with locational information (GPS), rental, and charging transactions of 1,500 electric vehicles from the carsharing services Car2Go (Daimler) and DriveNow (BMW) over several years. We investigate the influence of the charging infrastructure density, battery technology, and rental demand for vehicles on the payoff for the carsharing operator and make an international comparison between the USA, Germany, the Netherlands, and Denmark. We show that Virtual Power Plants of electric vehicles create sustainable revenue streams for electric vehicle carsharing companies without compromising their rental business.
Auctions, Data Analytics, Decision Support Systems, Design Science, Electric Vehicles, Energy Informatics, Smart Markets, Sustainability, Virtual Power Plants
Kahlen, M.T. (2017, September 15). Virtual Power Plants of Electric Vehicles in Sustainable Smart Electricity Markets (No. EPS-2017-431-LIS). ERIM Ph.D. Series Research in Management. Erasmus University Rotterdam. Retrieved from hdl.handle.net/1765/100844