  The increasing market penetration of electric vehicles (EVs) may change the
travel behavior of drivers and pose a significant electricity demand on the
power system. Since the electricity demand depends on the travel behavior of
EVs, which are inherently uncertain, the forecasting of daily charging demand
(CD) will be a challenging task. In this paper, we use the recorded GPS data of
EVs and conventional gasoline-powered vehicles from the same city to
investigate the potential shift in the travel behavior of drivers from
conventional vehicles to EVs and forecast the spatiotemporal patterns of daily
CD. Our analysis reveals that the travel behavior of EVs and conventional
vehicles are similar. Also, the forecasting results indicate that the developed
models can generate accurate spatiotemporal patterns of the daily CD.
