基于出行链的电动汽车充电负荷预测模型

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Abstract Electric vehicles(EVs) will be large-scale applications in the future, which may have an important impact on the power grid. Electric vehicle charging load forecasting is the based analysis of V2G. However there is no mature forecasting method. In this paper, a novel EV load forecasting model is formulated to investigate the effects of stochastic charging behavior on local power grid. Firstly, several geographically distinct areas are assumed according to travel purposes. Based on Markov Chain, the interrelationship of the multiple trips in one day is investigated to give detailed roadmap of daily routes. Secondly, the influence of external conditions on energy consumption is taken into account and charging criterion is determined. Then, the overall daily charging load forecast at different places is then obtained by Monte Carlo simulation. Calculation results show that electric vehicles charging load have the seasonal and holiday characteristic, the charging load make maximum load of power grid increased in a certain extent.

Key words： Electric vehicle charging load national household travel survey(NHTS) trip chains Monte Carol

Received: 08 July 2014 Published: 13 April 2015

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TM714

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	Chen Lidan
	Nie Yongquan
	Zhong Qing

Cite this article:

Chen Lidan,Nie Yongquan,Zhong Qing. A Model for Electric Vehicle Charging Load Forecasting Based on Trip Chains[J]. Transactions of China Electrotechnical Society, 2015, 30(4): 216-225.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2015/V30/I4/216

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