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Chen, D.Y. and Han, W.T. (2013) Prediction of multivariate chaotic time series via radial basis function neural network. Complexity, 18, 55-66.

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  • 标题: 基于蒙特卡洛模拟的电动汽车充电负荷预测The Prediction of Electric Vehicles Charging Load Based on Monte Carlo Simulation

    作者: 潘欢, 乔文娟, 李楠

    关键字: 电动汽车, 蒙特卡洛模拟, 充电负荷, 充电方式Electric Vehicles, Monte Carlo Simulation, Charging Load, Charging Mode

    期刊名称: 《Modeling and Simulation》, Vol.3 No.4, 2014-11-12

    摘要: 本文主要对未来各类电动汽车大规模充电时所造成的电网负荷进行预测。基于现有中国电动汽车的发展趋势,根据用途不同,分为电动公交车、电动出租车、电动公务车、电动私家车;讨论不同类型电动汽车充电时对应的充电方式及充电时段,采用蒙特卡洛模拟法抽取起始荷电状态、起始充电时间;计算四种电动汽车的充电负荷,应用C++语言仿真模拟对应负荷特性曲线,并计算得到总体负荷曲线;通过分析曲线特征,总结未来电动汽车充电负荷主要影响因素,为电动汽车的充电设备建设提供指导型意见。 The charging load of a large number of electric vehicles is predicted in this paper. Based on the trends of electric vehicles in China, the electric vehicles are divided into electric buses, electric taxis, electric officer’s car and electric private car according to different use. The charging mode and time of different kinds of electric vehicles are discussed. The Monte Carlo simulation method is applied to determine the starting state of charge (SOC) and the initial charging point. The charging loads of four kinds of electric vehicles are calculated. The corresponding four charging curves and the total curves are obtained via simulation. Through analyzing the character of the curves, the influence factors of electric vehicles charging load in future are summarized and the suggestion for charging equipment building is provided.

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