作者: Hongcai Zhang , Wenzuo Tang , Zechun Hu , Yonghua Song , Zhiwei Xu
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摘要: Forecasting the spatial and temporal distribution of plug-in electric vehicle (PEV) charging load is of great significance to study impacts of PEVs on power systems and plan charging facilities. A method for forecasting the spatial and temporal distribution of PEV charging load is proposed based on PEVs' parking behaviors and the Parking Generation Rate Method (PGRM). Firstly, parking demands are quantified by PGRM and the PEVs' spatial and temporal distributions are formulated considering various parking behaviors in blocks of different land usages. Then, PEV charging demands for different types of charging facilities are analyzed. An integrated procedure using Monte-Carlo Simulation method is designed to simulate PEVs' parking, driving and charging behaviors. A case study of a typical urban area in China proves the proposed method is effective to forecast the spatial and temporal distribution of PEV …