Multi-objective Charging Station Planning Method Considering Investment Construction Cost and Safe Operation of the Power Grid

被引:1
|
作者
Zhang, Jing [1 ]
Jiang, Linru [1 ]
Wang, Wen [2 ]
Yang, Ye [2 ]
Wang, Ruohan [3 ]
Li, Jing [3 ]
Zhuang, Changhai [4 ]
机构
[1] China Elect Power Res Inst, Beijing Elect Vehicle Charging Battery Swap Engn, Beijing, Peoples R China
[2] State Grid Smart Internet Vehicles Co Ltd, Beijing, Peoples R China
[3] State Grid Shandong Elect Power Co, Mkt Serv Ctr Metrol Ctr, Jinan, Peoples R China
[4] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu, Peoples R China
来源
2023 5TH ASIA ENERGY AND ELECTRICAL ENGINEERING SYMPOSIUM, AEEES | 2023年
关键词
electric vehicle; charging load prediction; planning of charging stations; multi-objective optimization;
D O I
10.1109/AEEES56888.2023.10114276
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The unreasonable layout of charging stations will increase the investment construction cost of charging stations and affect the safe operation of the power grid. To solve the existing unreasonable charging stations layout problem, this paper proposes a multi-objective layout planning method. Firstly, the Monte Carlo method is used to predict the charging load of electric vehicles (EV) in time and space, and the prediction results are used as the conditions of primary location selection of charging stations. A multi-objective optimization model is established to minimize the comprehensive social cost and network loss. By setting the constraints of the maximum line power and the maximum voltage offset, the safe operation requirements of the power grid are achieved. Secondly, the model is solved by a multi-objective optimization algorithm and the Pareto optimal solution set is obtained. Besides, after eliminating the solutions that do not meet the safety requirements by N-1 running evaluation, the solution with the highest satisfaction is derived by fuzzy theory, which is 3572.38kCNY on comprehensive social cost and 214.35kW center dot h on network loss respectively. Finally, the feasibility of the model and algorithm is verified by analyzing the results.
引用
收藏
页码:1291 / 1297
页数:7
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