摘要
为解决大规模电动汽车无序接入配电网,并与常规负荷相叠加导致“峰上峰”现象这一问题,提出了一种基于分时电价机制的电动汽车有序充放电优化策略。综合考虑用户成本与配电网的安全稳定性,以用户用电费用和电网负荷峰谷差作为优化目标;为提高搜索速度和避免陷入局部最优的情况,采用一种改进后的粒子群算法进行求解。模拟仿真的结果表明,所提优化策略能够同时降低用户用电费用和电网负荷的峰谷差,从而促进电力系统安全经济运行,验证了该优化策略的可行性和有效性。
In order to solve the problem of“peak to peak”phenomenon caused by the disorderly integration of large-scale electric vehicles into the distribution network and the superposition of conventional loads,a time-of-use electricity price mechanism-based optimization strategy for orderly charging and discharging of electric vehicles was proposed.Taking into account user costs and the safety and stability of the distribution network,the optimization objective was to optimize user electricity costs and peak valley load differences of the power grid;to improve search speed and avoid falling into local optima,an improved particle swarm optimization algorithm was adopted for solving.The simulation results show that the proposed optimization strategy can simultaneously reduce user electricity costs and the peak valley difference of grid load,thereby promoting the safe and economic operation of the power system,verifying the feasibility and effectiveness of the optimization strategy.
作者
马鹏博
黄曌
郭智薇
杨驰泽
Ma Pengbo;Huang Zhao;Guo Zhiwei;Yang Chize(School of Rail Transit,Hunan University of Technology,Zhuzhou Hunan 412007,China;School of Electrical and Information Engineering,Hunan University of Technology,Zhuzhou Hunan 412007,China)
出处
《电气自动化》
2024年第5期1-3,共3页
Electrical Automation
基金
国家自然科学基金(51404103、51574117、61376073)
湖南省自然科学基金(2017JJ5044)。
关键词
电动汽车
分时电价
改进粒子群算法
多目标优化
削峰填谷
electric vehicle
time-of-use electricity price
improved particle swarm optimization algorithm
multi-objective optimization
peak shaving and valley filling