Towards a Business Case for Vehicle-to-Grid—Maximizing Profits in Ancillary Service Markets

  • David Ciechanowicz
  • Alois Knoll
  • Patrick Osswald
  • Dominik Pelzer
Chapter
Part of the Power Systems book series (POWSYS)

Abstract

Employing plug-in electric vehicles (PEV) as energy buffers in a smart grid could contribute to improved power grid stability and facilitate the integration of renewable energies. While the technical feasibility of this concept termed vehicle-to-grid (V2G) has been extensively demonstrated, economic concerns remain a crucial barrier for its implementation into practice. A common drawback of previous economic viability assessments, however, is their static approach based on average values which neglects intrinsic system dynamics. Realistically assessing the economics of V2G requires modeling an intelligent agent as a homo economicus who exploits all available information with regard to maximizing its utility. Therefore, a smart control strategy built on real-time information, prediction and more sophisticated battery models is proposed in order to optimize an agent’s market participation strategy. By exploiting this information and by dynamically adapting the agent behavior at each time step, an optimal control strategy for energy dispatches of each single PEV is derived. The introduced cost-revenue model, the battery model, and the optimization model are applied in a case study building on data for Singapore. It is the aim of this work to provide a comprehensive view on the economic aspects of V2G which are essential for making it a viable business case.

Keywords

Vehicle-to-grid Plug-in electric vehicle Economic viability Ancillary services Battery modeling Optimization model 

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Copyright information

© Springer Science+Business Media Singapore 2015

Authors and Affiliations

  • David Ciechanowicz
    • 1
  • Alois Knoll
    • 2
  • Patrick Osswald
    • 1
  • Dominik Pelzer
    • 1
  1. 1.TUM CREATESingaporeSingapore
  2. 2.Institute for Informatics VI, Robotics and Embedded SystemsTechnische Universität München (TUM)MunichGermany

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