基于时序谷时段充电的小区电动汽车负荷预测  

Residential Electric Vehicle Load Forecast Based on Valley Time Series Charging

作　　者：李恒杰[1,2,3] 吕俊青 陈伟 裴喜平[1,2,3] LI Hengjie;LV Junqing;CHEN Wei;PEI Xiping(College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050 China;Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou 730050 China;National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050 China)

机构地区：[1]兰州理工大学电气工程与信息工程学院,兰州730050 [2]甘肃省工业过程先进控制重点实验室,兰州730050 [3]兰州理工大学电气与控制工程国家级实验教学示范中心,兰州730050

出　　处：《电气工程学报》2019年第1期95-100,共6页Journal of Electrical Engineering

基　　金：国家自然科学基金项目(51767017);甘肃省基础研究创新群体项目(18JR3RA133)资助

摘　　要：针对传统负荷预测模型的不足,提出一种基于时序谷时段充电的小区私家电动汽车负荷预测模型,在满足居民小区内大规模私家电动汽车有序充电的同时进行负荷预测,并为小区充电站的规划及配电网的优化调度提供理论基础。首先分析了小区私家电动汽车历史出行规律、居民小区生活用电规律及历史用电数据;其次,基于峰谷分时电价引导并充分利用谷时段进行电动汽车有序充电,从而得出该小区的电动汽车总充电负荷;最后对兰州市某个具有代表性的居民小区电动汽车充电负荷进行仿真验证。结果表明,该方法不仅能有效降低电网负荷峰谷差率及小区配网过载率,同时能够更加方便准确地预测出整个小区电动汽车的总充电负荷,具有较强的实用性。Aiming at the shortcomings of traditional load forecasting model, a residential private electric vehicle load forecasting model is proposed based on time series valley charging in the paper, which can predict the electric vehicle load, make the orderly charging of large-scale private electric vehicles in the residential community, provide a theoretical basis for the planning of the charging station and the optimal scheduling of the distribution network. Firstly, the historical travel rules of residential private electric vehicles, the rules of residential electricity consumption and historical electricity consumption data are amalyzed. Secondly, based on the peak-to-valley time-of^use electricity price guide and making full use of the valley period for the orderly charging of electric vehicles, the charging load of the electric vehicle in the community is obtained. Finally, the electric vehicle charging load of a residential area in Lanzhou is simulated and verified. The results show that the method can more effectively and accurately predict the charging load of electric vehicles while effectively reducing the peak-to-valley difference of the grid load and the network distribution network overload rate, which has strong practicability.

关 键 词：电动汽车 负荷预测 时序充电 峰谷分时电价 

分 类 号：TM715[电气工程—电力系统及自动化]