Meta Heuristic Algorithm Based Multi Objective Optimal Planning of Rapid Charging Stations and Distribution Generators in a Distribution System Coupled with Transportation Network

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Vutla Vijay, C. Venkaiah, Vinod Kumar Dulla Mallesham
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引用次数: 0

Abstract

. The application of Electric Vehicles (EVs) is increasing in many countries, causing many researchers to focus on EV Rapid Charging Station (RCS) related issues. The optimal planning of RCS considering only distribution networks is not a reli-able approach. Moreover, the RCS location should be convenient to the EV user in a given EV driving range and the performance of the distribution system. In this paper, a multi-objective approach for optimal planning of RCS and Distributed Generators (DG) in a distributed system coupled with a transportation network is analyzed. The proposed optimal planning method aims to achieve reduced active power loss, EV user costs, and voltage deviation for effective RCS and DG planning. The approach includes the analysis of the test system with the base case, solo planning of RCS, planning of DGs with fixed RCS, and simultaneous optimal planning of RCS and DGs. Daily load variation at buses and hourly charging probability of EVs have been used in the analysis. IEEE 33 bus distribution system superimposed with a 25-node transportation network is considered the test system. Rao 3 algorithm is applied for optimization, and the results have been compared with PSO and JAYA algorithms.
基于元启发式算法的快速充电站和配电网多目标优化规划
电动汽车(EV)在许多国家的应用正在增加,这导致许多研究人员关注电动汽车快速充电站(RCS)的相关问题。仅考虑配电网的RCS优化规划是不可行的。此外,在给定的电动汽车行驶里程和配电系统的性能下,RCS的位置应该方便电动汽车用户。本文分析了与运输网络耦合的分布式系统中RCS和分布式发电机(DG)的多目标优化规划方法。所提出的优化规划方法旨在实现有效RCS和DG规划的有功功率损耗、电动汽车用户成本和电压偏差的降低。该方法包括带基本情况的测试系统分析、RCS的单独规划、固定RCS的DG规划以及RCS和DG的同时优化规划。分析中使用了公交车的日负荷变化和电动汽车的小时充电概率。IEEE 33总线配电系统与25节点的交通网络叠加被认为是测试系统。将Rao-3算法应用于优化,并与PSO算法和JAYA算法进行了比较。
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来源期刊
Advances in Electrical and Electronic Engineering
Advances in Electrical and Electronic Engineering ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
1.30
自引率
33.30%
发文量
30
审稿时长
25 weeks
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