ISSN 1000-1026
CN 32-1180/TP
  • ISSN 1000-1026
  • CN 32-1180/TP

Citation: ZHANG Hongcai,HU Zechun,SONG Yonghua,XU Zhiwei,JIA Long.A Prediction Method for Electric Vehicle Charging Load Considering Spatial and Temporal Distribution[J].Automation of Electric Power Systems,2014,38(1):13-20. DOI: 10.7500/AEPS20130613009 copy

A Prediction Method for Electric Vehicle Charging Load Considering Spatial and Temporal Distribution

  • Received Date: June 13, 2013
    Accepted Date: August 20, 2013
    Available Online: January 01, 2014

  • Abstract:

        A new method of predicting the electric vehicle(EV)charging load considering the spatial and temporal distribution is proposed based on driving and parking characteristics of private cars.The parking demand is predicted with the parking generation rate model and the spatial and temporal distribution model of EV parking demand is developed by integrating various parking demands and characteristics in different types of areas.Then,EV charging demands are analyzed based on the daily driving mileages and the spatial and temporal distribution characteristics of daily parking demands.The Monte Carlo simulation method is adopted to simulate EV parking,driving and charging behavior sat different time and different places for the prediction of the spatial and temporal distribution characteristics of EV charging load.The predicted outcomes of Shenzhen in2020show that EV charging load changes with different charging behaviors and charging facilities available;charging demands can be mostly satisfied with charging facilities at residential quarters and workplaces;charging loads in different parts of a city with different pieces of land for construction are markedly different.


  • Keywords:

    electric vehicle(EV); parking generation rate model; Monte Carlo simulation; charging load; spatial and temporal distribution


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