Balancing with Electric Vehicles: A Profitable Business Model

Micha Kahlen, Wolf Ketter, Jan van Dalen

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

23 Citations (Scopus)

Abstract

Virtual Power Plants (VPP), centrally-controlled systems of interconnected energy sources, are relevant for balancing the electrical grid. VPPs facilitate flexible energy supply through distributed generation, storage capacity and demand response mechanisms. In our research, we study the role of VPPs consisting of electric vehicles (EV) fleets in addressing the challenges associated with inflexible renewable energy sources. Idle EV’s objectives are charging for the next ride and providing VPP capacity, which we show is sufficiently available. These VPPs participate in an energy exchange. They are controlled by intelligent trading agents which buy energy on the spot market, store it, and sell it later at higher prices. We study trading behavior of EV fleet owners agents, and its effects in Power TAC, a large scale, multi-agent smart grid simulation. We show that these VPPs offer crucial resource flexibility to the grid. They reduce the average electricity price by 3.2% and CO2 emissions by 2.4%. In addition, we show how increasing competition among VPPs affects profitability for fleet owners. The key contribution of this research is the validation of a VPP business model in terms of its profitability through arbitrage, ecological worthwhileness through emission reductions, and benefits for consumers by reducing energy expenses.
Original languageEnglish
Title of host publicationProceedings of the 22nd European Conference on Information Systems
Place of PublicationTel Aviv, Israel
Pages1-15
Number of pages15
Publication statusPublished - 5 Jun 2014
Event22nd European Conference on Information Systems, ECIS 2014 - Tel Aviv, Israel
Duration: 9 Jun 201411 Jun 2014

Conference

Conference22nd European Conference on Information Systems, ECIS 2014
Country/TerritoryIsrael
CityTel Aviv
Period9/06/1411/06/14

Research programs

  • RSM LIS

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