  Plug-in electric vehicles (PEVs) can contribute to energy and environmental
challenges. Among different types of PEVs, plug-in hybrid electric taxis
(PHETs) go in advance. In this study, we provide a spatial and temporal PHET
charging demand forecasting method based on one-month global positioning system
(GPS)-based taxi travel data in Beijing. Then, using the charging demand
forecasting results, a mixed integer linear programming (MILP) model is
formulated to plan PHET charging stations in the central area of Beijing. The
model minimizes both investment and operation costs of all the PHET charging
stations and takes into account the service radius of charging stations,
charging demand satisfaction and rational occupation rates of chargers. At
last, the test of the planning method is carried out numerically through
simulations and the analysis is complemented according to the results.
