Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization Algorithm

被引:23
|
作者
Muthukannan, S. [1 ]
Karthikaikannan, D. [2 ]
机构
[1] SASTRA Deemed Univ, Thanjavur 613401, Tamil Nadu, India
[2] SASTRA Deemed Univ, Sch Elect & Elect Engn, Thanjavur 613401, Tamil Nadu, India
关键词
Electric vehicle charging; Mathematical models; Charging stations; Capacitors; Optimization; Costs; Voltage; Charging station; electric vehicle (EV); facility location problem; particle swarm optimization (PSO); direct search (DS); IDENTIFICATION; GENERATION; SYSTEMS;
D O I
10.1109/ACCESS.2022.3168830
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Electric Vehicle (EV) charging station placement problem is a facility location problem. The EV charging station placement problem concerns about the total coverage in traffic network, the system losses and node voltage deviations in electric distribution system. To address the loss reduction and voltage profile improvement, the distribution systems are normally equipped with shunt capacitors for reactive power compensation. In this paper mathematical model comprising three objective functions, maximization of coverage and minimization of loss and node voltage deviations subjected to constraints is proposed for the simultaneous placement of EV charging stations and shunt capacitors. The control variables for optimization are the rating and location of charging stations and shunt capacitors. A hybrid optimization algorithm (PSO-DS) combining particle swarm optimization algorithm and direct search method is proposed for the solution of the mathematical model. The performance of PSO-DS is justified by comparing it with other state-of-the-art algorithms in solving the standard benchmark functions. Simulations are carried out on a 33-bus distribution system and a 25-node traffic network system to determine the different planning strategy for the placement of charging stations.
引用
收藏
页码:48088 / 48101
页数:14
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