Hybrid genetic algorithm and particle swarm for optimal power flow with non-smooth fuel cost functions

被引:11
|
作者
Gacem A. [1 ]
Benattous D. [2 ]
机构
[1] Department of Electrical Engineering, University Med Khaider, Biskra
[2] Department of Electrical Engineering, University Echahid Hamma Lakhdar, El-Oued
关键词
HGAPSO; Non-smooth cost function; Optimal power flow; Valve point effects;
D O I
10.1007/s13198-014-0312-8
中图分类号
学科分类号
摘要
This paper presents a hybrid genetic algorithm and particle swarm optimization (HGAPSO) for solving optimal power flow problem with non-smooth cost function and subjected to limits on generator real, reactive power outputs, bus voltages, transformer taps and power flow of transmission lines. In (HGAPSO), individuals in a new generation are created, not only by crossover and mutation operation as in (GA), but also by (PSO). The effectiveness of this algorithm is examined and tested for standard IEEE 30 bus system with six generating units. The results of the proposed technique are compared with that of PSO and other methods reported in the literature. © 2014, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.
引用
收藏
页码:146 / 153
页数:7
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