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考虑电动汽车用户满意度的微网分层优化调度策略 被引量:13

Optimization Strategy of Microgrid Hierarchical Scheduling Considering Electric Vehicles User Satisfaction Degree
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摘要 针对住宅区微网中的电动汽车集群,提出一种考虑电动汽车用户满意度的微网分层优化调度策略。将微网调度优化的过程分为负荷层和源储层,负荷层在保证用户满意度的前提下,利用电动汽车的储能特性平抑微网的负荷峰值,源储层先用可再生能源出力支持微网用电负荷,多余出力部分则通过电动汽车进行消纳,使得微网综合运行成本达到最低。然后,用改进蚁狮算法求解源储层模型,最后,通过算例进行验证。结果表明,相对于电动汽车无序充电,该策略大幅提升了微网运行的经济性、可靠性以及电动汽车用户的满意度。 In this paper, a hierarchical scheduling optimization strategy considering electric vehicle user satisfaction degree is proposed for electric vehicle cluster in residential microgrid. Microgrid scheduling optimization process can be divided into load layer and source storage layer. The load layer utilizes the energy storage characteristics of electric vehicles to smooth the peak of the original load in the microgrid under the premise of ensuring user satisfaction of electric vehicles. Renewable energy is used to support the load of the microgrid in the source storage layer, and the excess part is absorbed by the dispatchable electric vehicle,which makes the comprehensive cost of the microgrid minimized. The improved ant lion algorithm is used to solve the model of the source storage layer. Lastly, verify through an example. The result shows that the strategy greatly improves the economics and reliability of microgrid compared with the disordered charge of electric vehicles. Meanwhile, the satisfaction degree of electric vehicle user is improved.
作者 于会群 尹申 张浩 时珊珊 彭道刚 蔡国顺 YU Huiqun;YIN Shen;ZHANG Hao;SHI Shanshan;PENG Daogang;CAI Guoshun(School of Automation Engineering,Shanghai University of Electric Power,Shanghai 200090,China;School of Electronic and Information Engineering,Tongji University,Shanghai 201804,China;State Grid Shanghai Electric Power Company Electric Power Research Institute,Shanghai 200437,China)
出处 《中国电力》 CSCD 北大核心 2020年第12期83-91,共9页 Electric Power
基金 国家自然科学基金项目资助(71871160) 国网上海市电力公司科技项目(52094019007G)。
关键词 电动汽车 用户满意度 微网 分层优化调度策略 改进蚁狮算法 electric vehicle user satisfaction degree microgrid hierarchical optimization scheduling strategy improved ant lion algorithm
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