Group search optimizer based optimal location and capacity of distributed generations

被引:51
|
作者
Kang, Qi [1 ,2 ]
Lan, Tian [1 ]
Yan, Yong [1 ]
Wang, Lei [1 ,2 ]
Wu, Qidi [1 ,2 ]
机构
[1] Tongji Univ, Dept Control Sci & Engn, Shanghai 201804, Peoples R China
[2] Tongji Univ, MOE, Key Lab Embedded Syst & Comp Serv, Shanghai 201804, Peoples R China
基金
美国国家科学基金会;
关键词
Distributed generations; Optimal location and capacity; Swarm intelligence; Improved group search optimizer;
D O I
10.1016/j.neucom.2011.05.030
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a novel efficient population-based heuristic approach for optimal location and capacity of distributed generations (DGs) in distribution networks, with the objectives of minimization of fuel cost, power loss reduction, and voltage profile improvement. The approach employs an improved group search optimizer (iGSO) proposed in this paper by incorporating particle swarm optimization (PSO) into group search optimizer (GSO) for optimal setting of DGs. The proposed approach is executed on a networked distribution system the IEEE 14-bus test system for different objectives. The results are also compared to those that executed by basic GSO algorithm and PSO algorithm on the same test system. The results show the effectiveness and promising applications of the proposed approach in optimal location and capacity of DGs. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:55 / 63
页数:9
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