Maximum loadability limit of power system using hybrid differential evolution with particle swarm optimization

被引:32
作者
Gnanambal, K. [1 ]
Babulal, C. K. [2 ]
机构
[1] KLN Coll Engn, Dept Elect & Elect Engn, Pottapalayam 630611, Tamil Nadu, India
[2] Thiagarajar Coll Engn, Dept Elect & Elect Engn, Madurai 625015, Tamil Nadu, India
关键词
Maximum loadability limit; Particle swarm optimization; Differential evolution;
D O I
10.1016/j.ijepes.2012.04.033
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
Differential evolution (DE), a simple evolutionary algorithm which shows superior performance in global optimization. Since it utilizes the differential information to get the new candidate solution, sometimes it results in instability of performance. Particle swarm optimization (PSO) is widely used to solve the optimization problems as it can converge quickly. But PSO easily gets stuck in local optima. Hybridization of DE and PSO (DEPSO) eliminates the disadvantages of both. This paper presents the application of DEPSO algorithm to determine the maximum loadability limit of power system. It is tested on Matpower 30 bus and IEEE 118 bus systems. To compare the performance of this DEPSO algorithm with other evolutionary algorithms like DE and Multi Agent Hybrid PSO, statistical measures like best, mean, standard deviation of results and average computation time over 20 independent trials are considered here. The results show the better performance of DEPSO algorithm to solve the maximum loadability problem. DEPSO algorithm provides high maximum loading point in reduced time. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:150 / 155
页数:6
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