Hybrid bare-bones PSO for dynamic economic dispatch with valve-point effects
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作者:
Zhang, Yong
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China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R ChinaChina Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R China
Zhang, Yong
[1
]
Gong, Dun-wei
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China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R ChinaChina Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R China
Gong, Dun-wei
[1
]
Geng, Na
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China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R ChinaChina Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R China
Geng, Na
[1
]
Sun, Xiao-yan
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China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R ChinaChina Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R China
Sun, Xiao-yan
[1
]
机构:
[1] China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Peoples R China
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.