基于出行链的电动汽车充电负荷预测模型

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摘要提出了一种基于电动汽车行驶出行链的考虑充电频率的电动汽车充电负荷预测方法。由居民出行调研统计数据将家用车辆出行目的分为五大类,构建简单和复杂出行链,分别采用三参数威布尔函数和对数正态概率分布函数拟合每段行程的结束时间和行驶距离,建立车辆一天行驶的时空分布模型;考虑温度、交通路况等因素对电动汽车耗电量的影响,采用模糊算法计算得到每公里实时耗电量结果。用蒙特卡洛仿真方法对不同渗透率、夏冬季、工作日和周末等不同情景电动汽车充电负荷进行计算,结果表明,电动汽车充电负荷具有季节性、假日性,电动汽车无序充电将使电网最大负荷发生一定增长,并随其渗透率逐步加大。

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	陈丽丹
	聂涌泉
	钟庆

关键词 ：电动汽车, 充电负荷, 全美家庭出行调查数据, 出行链, 蒙特卡洛

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

收稿日期: 2014-07-08 出版日期: 2015-04-13

PACS:

TM714

基金资助:国家自然科学基金（51307061）和华南理工大学广州学院优秀青年骨干教师项目（B09B113005）资助

作者简介: 陈丽丹女,1981年生,博士研究生,讲师,主要研究方向为电动汽车、新能源技术、电力系统优化规划与运行等。聂涌泉男,1990年生,博士研究生,主要研究方向为电力系统负荷预测、稳定运行分析与控制。

引用本文:

陈丽丹,聂涌泉,钟庆. 基于出行链的电动汽车充电负荷预测模型[J]. 电工技术学报, 2015, 30(4): 216-225. Chen Lidan,Nie Yongquan,Zhong Qing. A Model for Electric Vehicle Charging Load Forecasting Based on Trip Chains. Transactions of China Electrotechnical Society, 2015, 30(4): 216-225.

链接本文:

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

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