Biogeography based optimization for multi-constraint optimal power flow with emission and non-smooth cost function

被引：115
作者：
Roy, P. K. [1 ]
Ghoshal, S. P. [1 ]
Thakur, S. S. [1 ]
机构：
[1] Natl Inst Technol, Dept Elect Engn, Durgapur 713209, W Bengal, India
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 12期
关键词：
Biogeography; Optimal power flow; Particle swarm optimization; Genetic algorithm; Mutation; Migration; SWARM OPTIMIZATION;
D O I：
10.1016/j.eswa.2010.05.064
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 biogeography based optimization (BBO) technique for solving constrained optimal power flow problems in power systems, considering valve point nonlinearities of generators. In this paper, the proposed algorithm has been tested in 9-bus and IEEE 30-bus systems under various simulated conditions. A comparison of simulation results reveals optimization efficacy of the proposed scheme over evolutionary programming (EP), genetic algorithm (GA), particle swarm optimization (PSO), mixed-integer particle swarm optimization (MIPSO) and sequential quadratic programming (SQP) used in MAT-POWER for the global optimization of multi-constraint OPF problems. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：8221 / 8228
页数：8
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