基于高斯混合模型的电动私家车出行时间特征量分析  

Analysis of Travel Time Characteristics of Private Electric Vehicles Based on Gaussian Mixture Model

作　　者：韩跃峻 沈志祺 张洋 杜漾腾 辛洁晴[2] Han Yuejun;Shen Zhiqi;Zhang Yang;Du Yangteng;Xin Jieqing(Shibei Electricity Supply Branch,State Grid SMEPC,Shanghai 200072,China;Department of Electric Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)

机构地区：[1]国网上海市电力公司市北供电公司,上海200072 [2]上海交通大学电气工程系,上海200240

出　　处：《电气自动化》2024年第6期40-42,共3页Electrical Automation

摘　　要：目前尚未有我国电动私家车出行时间特征量概率分析结果,为此开展上海地区居民用户电动汽车使用行为习惯调研。基于出行链结构,采用高斯混合模型构建电动汽车出行时间特征量概率分析方法,并将该方法用于调研数据,获得上海地区私家电动车第一次出行时间、单日出行次数和单次停车时长的概率分布。研究结果为后续开展电动汽车负荷预测和社区充电桩优化布点提供信息基础。A survey on the usage habits of electric vehicles among residents in Shanghai was conducted to address the issue of the lack of probabilistic analysis results on the travel time characteristics(TTCs)of private electric cars(EVs)in China.Based on the travel chain structure,a Gaussian mixture model was used to construct a probability analysis method for the characteristic quantities of electric vehicle travel time,and the method was applied to research data to obtain the probability distribution of the first travel time,daily travel times,and single parking time of private electric vehicles in Shanghai.The research findings provide an information foundation for subsequent electric vehicle load forecasting and optimization of community charging station layout.

关 键 词：电动汽车 出行链 高斯混合模型 时间特征 用户调研 

分 类 号：TM715[电气工程—电力系统及自动化]