text: Simulating the value of electric-vehicle–grid integration using a behaviourally realistic model | Nature Energy
  Simulating the value of electric-vehicle–grid integration using a behaviourally realistic model
  Michael Wolinetz1,2,
  Jotham Peters1,2 &
  Curran Crawford3
  Nature Energyvolume 3, pages132–139 (2018) | Download Citation
  Vehicle–grid integration (VGI) uses the interaction between electric vehicles and the electrical grid to provide benefits that may include reducing the cost of using intermittent renwable electricity or providing a financial incentive for electric vehicle ownerhip. However, studies that estimate the value of VGI benefits have largely ignored how consumer behaviour will affect the magnitude of the impact. Here, we simulate the long-term impact of VGI using behaviourally realistic and empirically derived models of vehicle adoption and charging combined with an electricity system model. We focus on the case where a central entity manages the charging rate and timing for participating electric vehicles. VGI is found not to increase the adoption of electric vehicles, but does have a a small beneficial impact on electricity prices. By 2050, VGI reduces wholesale electricity prices by 0.6–0.7% (0.7 $ MWh–1, 2010 CAD) relative to an equivalent scenario without VGI. Excluding consumer behaviour from the analysis inflates the value of VGI.
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  This study was funded by Natural Resources Canada, the Pacific Institute for Climate Solutions (PICS), the Government of British Columbia, BC Hydro and the Social Sciences & Humanities Research Council of Canada (SSHRC). Thank you to S. Behboodi from the University of Victoria for his valuable support, and to M. Castro for her assistance regarding choice of modelling approaches.
  Navius Research, Vancouver, Canada
  Michael Wolinetz
  & Jotham Peters
  Sustainable Transportation Action Research Team, Simon Fraser University, Burnaby, Canada
  , Jonn Axsen
  Institute for Integrated Energy Systems, University of Victoria, Victoria, Canada
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  M.W. and J.A. developed the REPAC model, designed and conducted the analysis and co-wrote the paper. J.P. developed the IESD model and its link to the other models. C.C. participated in the study design and edited the manuscript.