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
DOI: 10.12677/MOS.2014.34012, PDF,  被引量    科研立项经费支持
作者: 潘 欢, 乔文娟, 李 楠：宁夏大学，物理电气信息学院及宁夏沙漠信息智能感知重点实验室，银川
关键词: 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
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。
Abstract: 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.
文章引用：潘欢, 乔文娟, 李楠. 基于蒙特卡洛模拟的电动汽车充电负荷预测[J]. 建模与仿真, 2014, 3(4): 83-91. http://dx.doi.org/10.12677/MOS.2014.34012

参考文献

[1] Bauer, T., Lips, H.P., Thiele, G., et al. (1997) Operational tests on HVDC thyristor modules in a synthetic test circuit for the Sylmar East Restoration Project. IEEE Transactions on Power Delivery, 12, 1151-1158.
[2] 杨孝纶 (2007) 电动汽车技术发展趋势及前景(上). 汽车科技, 6, 10-13.
[3] 张文亮, 武斌, 李武峰, 等 (2009) 电动汽车我国纯电动汽车的发展方向及能源供给模式的探讨. 电网技术, 33, 1-5.
[4] 李建祥 (2013) 电动汽车充电需求负荷建模方法研究. 建筑电气, 32, 45-48.
[5] 杨冰, 王丽芳, 廖承林 (2013) 大规模电动汽车充电需求及影响因素. 电工技术学报, 28, 22-27.
[6] Clement, K., Haesen, E. and Driesen, J. (2010) The impact of charging plug-in hybrid electric vehicles on a residential distribution grid. IEEE Transactions on Power Systems, 25, 371-380.
[7] Soares, F.J., Lopes, J.A.P. and Almeida, P.M.R. (2010) A Monte Carlo method to evaluate electric vehicles impacts in distribution networks. In: Proceedings of IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply, IEEE, Waltham, 365-372.
[8] Kristien, C.N., Edwin, H. and Johan, D. (2010) The impact of charging plug-in hybrid electric vehicles on a residential distribution grid. IEEE Transactions on Power Systems, 25, 371-380.
[9] 荆朝霞, 钟童科, 林志龙, 等 (2013) 电动汽车充电行为对电网负荷曲线的影响. 南方电网技术, 7, 80-84.
[10] 杨少兵, 吴命利, 姜久春 (2013) 电动汽车充电站负荷建模方法. 电网技术, 37, 1190-1195.
[11] 罗卓伟, 胡泽春, 宋永华, 等 (2012) 换电模式下电动汽车电池充电负荷建模与有序充电研究. 中国电机工程学报, 32, 1-7.
[12] 樊扬, 左郑敏, 朱浩骏, 等 (2011) 电动汽车充电模式对广东电网负荷特性的影响. 广东电力, 24, 58-61.
[13] 罗卓伟, 胡泽春, 宋永华 (2011) 电动汽车充电负荷计算方法. 电力系统自动化, 35, 36-42.
[14] 贾洪旭 (2008) 奥运电动汽车电池管理系统的研究与设计. 硕士学位论文, 北京交通大学, 北京.
[15] Sandels, C., Franke, U., Ingvar, N., et al. (2010) Vehicle to grid—Monte Carlo simulations for optimal aggregator strategies. Proceedings of International Conference on Power System Technology, Hangzhou, 24-28 October 2010, 1-8.
[16] 陈帝伊, 柳烨, 马孝义 (2012) 基于径向基函数神经网络的混沌时间序列相空间重构双参数联合估计. 物理学报, 61, 100501.1-100501.9.
[17] Chen, D.Y. and Han, W.T. (2013) Prediction of multivariate chaotic time series via radial basis function neural network. Complexity, 18, 55-66.

为你推荐