基于用户意愿的电动汽车备用容量多目标优化  

Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes

作　　者：邵萍 杨之乐 李慷 朱晓东[1] SHAO Ping;YANG Zhile;LI Kang;ZHU Xiaodong(School of Electrical and Information Engineering,Zhengzhou University,Zhengzhou 450001,China;Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences,Shenzhen 518000,Guangdong,China;School of Electronics and Electrical Engineering,University of Leeds,Leeds LS29JT,U.K.)

机构地区：[1]郑州大学电气与信息工程学院,郑州450001 [2]中国科学院深圳先进技术研究院,广东深圳518000 [3]利兹大学电子与电气工程学院,英国利兹LS29JT

出　　处：《上海交通大学学报》2023年第11期1501-1511,共11页Journal of Shanghai Jiaotong University

基　　金：国家自然基金委面上项目(52077213);国家自然科学基金青年科学基金项目(62003332)。

摘　　要：电动汽车(EV)保有量可观且具有储能的特性,使其参与电力系统运行调控提供备用服务成为可能.针对此建立基于EV用户意愿,以集电商经济收益、微电网功率波动和用户满意度为目标的多目标优化调度模型.考虑到负荷预测误差的影响,对模型进行日前阶段和日内实时修正阶段的多时间尺度优化调度分析.求解方法采用主流的多目标智能优化算法NSGA-Ⅲ算法,同时将NSGA-Ⅱ和MOEA/D算法作为对比算法,通过对比实验选出最优调度方案并分析EV提供备用容量的场景.仿真结果证明所提模型的有效性.Due to the considerable number and the characteristics of energy storage,it is possible for electric vehicles(EVs)to participate in the operation and regulation of power system to provide reserve service.In view of this,a multi-objective optimal scheduling model is established based on the wishes of electric vehicle users,with the objectives of the economic benefits of electricity collectors,microgrid power fluctuations and user satisfaction.Considering the uncertainty of load demand,the optimal scheduling analysis of multi-time scale scenes with the day-ahead time scale and the intra-day real-time correction time scale is conducted.The mainstream multi-objective intelligent optimization algorithm NSGA-Ⅲ algorithm is adopted in the solution method,and the NSGA-II and MOEA/D algorithms are used for comparison.The optimal dispatching scheme is selected through comparative experiments and scenarios where EVs provide spare capacity are analyzed.The simulation results verify the feasibility and effectiveness of the proposed model.

关 键 词：备用容量 用户意愿 多目标 多时间尺度 负荷需求不确定性 

分 类 号：TP731[自动化与计算机技术—检测技术与自动化装置]