基于投资收益与用户效用耦合决策的电动汽车充电站优化配置  

Optimal Allocation of Charging Station for Electric Vehicle Based on Coupled Decision of Investment Benefit and User Utility

作　　者：谭洋洋[1] 杨洪耕[1] 徐方维[1] 余雪莹[1] 张曦[1] 胥威汀 TAN Yangyang YANG Honggeng XU Fangwei YU Xueying ZHANG Xi XU Weiting(School of Electrical Engineering and Information, Sichuan University, Chengdu 610065, Sichuan Province, China Sichuan Electric Power Corporation Power Economic Research Institute, Chengdu 610041, Sichuan Province, China)

机构地区：[1]四川大学电气信息学院,四川省成都市610065 [2]国网四川省电力公司经济技术研究院,四川省成都市610041

出　　处：《中国电机工程学报》2017年第20期5951-5960,共10页Proceedings of the CSEE

基　　金：国家自然科学基金项目(51377111)~~

摘　　要：传统方法多聚焦于充电站的投资成本和收益,忽略了充电用户选择决策对投资主体规划决策的影响,该文提出一种考虑充电站投资收益和充电用户效用耦合决策的电动汽车充电站双层优化模型。根据城市电动汽车种类及其出行特性,计算规划区域内电动汽车充电功率需求,并以充电站投资收益为上层目标函数,以充电用户满意度为下层目标函数。引入用户选择决策变量耦合关联上下层模型,使用KKT条件实现双单层规划模型解耦。综合粒子群算法的快速搜索能力和变邻域搜索算法的全局搜索优势,采用混合变邻域粒子群算法对解耦模型进行求解。最后,算例仿真结果验证了模型和算法的有效性和可行性。Traditional methods mainly focuses on the cost and benefit of electric vehicles （EVs） charging station, and ignores the decisions of users had great impact on the planning decisions of investors. This paper proposed a bi-level optimal model of EVs charging station considering coupled decision of invest benefit and user utility. According to the types and trip characteristics of urban EVs, and the charging power demand of EVs in planning area was calculated. The upper-level objective function identifies the investment benefit of charging station, whereas the lower-level objective function identifies the degree of satisfaction of users, and introduces a selection decision variable to couple the upper and lower model. Using the KKT to deeouple the bi-level into single-level, and then integrating the fast search capability of particle swarm optimization with the global search ability of variable neighborhood search and using the hybrid intelligent algorithm to solve the single-level programming problem. Finally, the simulation results verify the proposed model and algorithm is effective and feasible.

关 键 词：双层优化模型 投资收益 用户效用 粒子群算法 变邻域搜索 

分 类 号：TM71[电气工程—电力系统及自动化]