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基于负荷数据聚类的充电站储能容量规划方法
作者姓名:李笑彤  宋宝同  吕风波  齐步洋  贡晓旭  王坤芳
作者单位:国网北京市电力公司经济技术研究院;清华四川能源互联网研究院;清华大学
基金项目:国网北京市电力公司科技项目资助(52023419000A)。
摘    要:针对已建充电站配置储能需求的问题,以充电站储能折算到日净收益最大为目标函数,构建充电站储能容量优化配置模型,基于充电站全年实际运行数据,通过应用K-均值聚类方法进行分类,并采用粒子群算法对储能容量优化模型进行求解,最后通过典型算例对模型和方法进行验证。结果表明,该模型和方法能够综合考虑充电站全年实际运行特性,更加精细和全面地反映储能全年收益情况,能够有效指导已建充电站储能容量配置和规划建设。

关 键 词:储能  充电站  容量配置  聚类  粒子群算法

An Energy Storage Capacity Planning Method of Charging Station Based on Load Data Clustering
Authors:LI Xiaotong  SONG Baotong  Lü Fengbo  QI Buyang  GONG Xiaoxu  WANG Kunfang
Affiliation:(State Grid Beijing Electric Power Company Economic and Technical Research Institute,Beijing 102209,China;Tsinghua Sichuan Energy Internet Research Institute,Chengdu 610213,Sichuan,China;Tsinghua University,Beijing 100084,China)
Abstract:Aiming at the issue of energy storage demand of existing charging stations,and taking the conversion of energy storage capacity of charging stations to the maximum daily net income as the objective function,the optimal allocation model of energy storage capacity of charging stations is constructed in this paper. Based on the annual actual operation data of charging stations, the k-means clustering method is applied for classification,and the particle swarm optimization algorithm is used to solve the optimization model of energy storage capacity.Finally,a typical example is given to verify the model and method. The results show that the model and method proposed in this paper can comprehensively consider the actual operation characteristics of the charging station throughout the year,reflect the annual income of energy storage more accurately and comprehensively,and can effectively guide the energy storage capacity configuration and planning and construction of existing charging stations.
Keywords:energy storage  charging station  capacity configuration  clustering  particle swarm algorithm
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