王琼,邹晴,李乐,李超然,闫雪鹰
WANG Qiong,ZOU Qing,LI Le,LI Chaoran,YAN Xueying

• 1:国网北京市电力公司
• 2:国网北京大兴供电公司
• 3:国网智慧车联网技术有限公司

摘要(Abstract)：

针对城市EV（电动汽车）充电站规划建设中投资高、效率低的问题，提出一种考虑用户动态充电需求不确定性的充电站选址定容优化模型。首先，基于出行链理论和OD（起讫点）矩阵研究EV出行特性，结合Dijkstra算法和蒙特卡洛法建立EV的充电负荷时空分布预测模型。其次，建立以充电站经营者年化成本、EV用户年化经济损失之和最小为目标的充电站选址定容模型，采用加权Voronoi图与自适应模拟退火粒子群优化算法求解，确定充电站的最优数量、位置及服务范围。最后，在定容模型中引入不确定情境集描述用户动态充电需求的不确定性，并采用鲁棒优化理论求解充电站容量。针对北方某市部分城区的EV充电站规划问题开展算例分析，验证了模型的有效性。
Due to high investment costs and low efficiency in the planning and construction of electric vehicle(EV) charging stations in cities, an optimal model for siting and sizing of charging stations that takes into consideration the uncertainty of dynamic charging demand of users is proposed. Initially, the characteristics of EV trip are studied based on trip chain theory and origin-destination(OD) matrix. In conjunction with the Dijkstra's algorithm and the Monte Carlo method, a spatiotemporal prediction model for EV charging load distribution is established. Subsequently, an optimal siting and sizing model for charging stations is constructed, with the aim of minimizing the sum of the annualized cost of charging station operators and the annualized economic loss of EV users. The optimal number, location, and service range of charging stations are determined using the weighted Voronoi diagram and an adaptive simulated annealing particle swarm optimization(ASAPSO). Finally, an uncertain scenario set that describes the uncertainty of dynamic charging demand of users is introduced into the sizing model, and the charging station capacity is solved using robust optimization. The effectiveness of the model is validated through a case study analyzing the planning of EV charging stations in parts of a city in north China.

关键词(KeyWords)： 电动汽车充电站;选址定容;鲁棒优化;加权Voronoi图;自适应模拟退火粒子群优化算法
EV charging station;siting and sizing;robust optimization;weighted Voronoi diagram;ASAPSO

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金（62203172）;; 国网北京大兴2022年V2G测试支撑项目（B20212220016）

作者(Author): 王琼,邹晴,李乐,李超然,闫雪鹰
WANG Qiong,ZOU Qing,LI Le,LI Chaoran,YAN Xueying

DOI: 10.19585/j.zjdl.202409002

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