Hybrid bare-bones PSO for dynamic economic dispatch with valve-point effects

被引:78
作者
Zhang, Yong [1 ]
Gong, Dun-wei [1 ]
Geng, Na [1 ]
Sun, Xiao-yan [1 ]
机构
[1] China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R China
基金
中国国家自然科学基金;
关键词
Dynamic economic dispatch; Particle swarm optimization; Disturbance factor; Directionally chaotic search; Constraint handling; PARTICLE SWARM OPTIMIZATION; ALGORITHM; LOAD;
D O I
10.1016/j.asoc.2014.01.035
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 an efficient hybrid particle swarm optimization algorithm to solve dynamic economic dispatch problems with valve-point effects, by integrating an improved bare-bones particle swarm optimization (BBPSO) with a local searcher called directionally chaotic search (DCS). The improved BBPSO is designed as a basic level search, which can give a good direction to optimal regions, while DCS is used as a fine-tuning operator to locate optimal solution. And an adaptive disturbance factor and a new genetic operator are also incorporated into the improved BBPSO to enhance its search capability. Moreover, a heuristic handing mechanism for constraints is introduced to modify infeasible particles. Finally, the proposed algorithm is applied to the 5-, 10-, 30-unit-test power systems and several numerical functions, and a comparative study is carried out with other existing methods. Results clarify the significance of the proposed algorithm and verify its performance. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:248 / 260
页数:13
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