Forecasting Plug-In Electric Vehicle Sales and the Diurnal Recharging Load Curve

Abstract

The expected market penetration of plug-in electric vehicles has drawn much attention to the potential impact on power systems, which to a large extent depends on the number of electric vehicles on the road and the fleet's diurnal recharging load curve. We present two interactive models to jointly forecast plug-in electric vehicle sales and the diurnal recharging load curve in the U.S. between 2012 and 2020. The sales forecasting model is based on information about consumer preferences between hybrid electric vehicles and internal combustion engine vehicles, which can be extracted from historical data. The recharging load forecasting model is based on the assumption that electric vehicle users' recharging behavior will demonstrate a gradual transition from a convenience driven mode in 2012 to a cost driven mode in 2020. A case study is conducted for the Midwest ISO region. Compared to the sales forecasts from the literature, our results turn out to be less optimistic. Our recharging load forecast results also suggest that, if appropriately managed, the impact of plug-in electric vehicles on electricity load would not be overwhelming in the next decade.