摘要
随着新能源汽车不断普及,其配套充电设施的建设也同样需要不断完善。分析了充电站选址的不同场景以及对电网、交通网的互动关系,通过结合Bagging算法与粒子群算法(particle swarm optimization, PSO)算法,求解考虑充电站建设成本及有效性的充电站规划模型,具有较高的鲁棒性。并根据最终给出的规划方案,计算不同地区的充电站建设重要程度,为充电站的建设提供更宏观可靠的建议。
With continuous popularization of new energy vehicles,construction of their supporting charging facilities need to be improved continuously.Different scenarios for charging station siting and their interaction with power grid and traffic network were analyzed.By combining Bagging algorithm and particle swarm optimization(PSO),a charging station planning model considering both construction cost and effectiveness of the charging station was found-a model of high robustness.According to the final planning scheme,degrees of importance of station construction in different areas were calculated,thus providing more macroscopic and reliable suggestions for charging station construction.
作者
杨纲
屈婉莹
丁圣康
陆轶祺
解大
Yang Gang;Qu Wanyin;Ding Shengkang;Lu Yiqi;Xie Da(State Grid Shanghai Electric Power Co.Fengxian Power Supply Co.,Shanghai 201406,China;College of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《电气自动化》
2020年第3期10-12,16,共4页
Electrical Automation
基金
“上海市郊新能源公交车充电设施建设中供电方案和规划配套的研究”(SGTYHT/17-JS-199)资金支持。
关键词
电动汽车
充电站
选址定容
BAGGING
粒子群算法
electric vehicle
charging station
siting and sizing
Bagging algorithm
particle swarm optimization(PSO)
