Chaotic self-adaptive particle swarm optimization algorithm for dynamic economic dispatch problem with valve-point effects |
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| Authors: | Ying Wang Jianzhong Zhou Youlin Lu Hui Qin Yongqiang Wang |
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| Affiliation: | 1. Computer Technology Department, University of Alicante, Carretera San Vicente del Raspeig s/n, 03690 Alicante, Spain;2. Communications Engineering Department, University of Málaga, Málaga, Spain;1. Department of Computer Applications, BMS College of Engineering, Bangalore 560019, India;2. School of Computer and Information Sciences, University of Hyderabad, Hyderabad 500046, India;1. Civil Engineering Program COPPE/Federal University of Rio de Janeiro, Brazil;2. Graduate Program of Computational Modeling Federal University of Juiz de Fora, Brazil;3. Department of Mathematics Federal Center for Technological Education of Minas Gerais, Brazil;4. Department of Applied and Computational Mechanics School of Engineering, Federal University of Juiz de Fora, Brazil |
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| Abstract: | This paper presents a chaotic self-adaptive particle swarm optimization algorithm (CSAPSO) to solve dynamic economic dispatch problem (DED) with value-point effects. The proposed algorithm takes PSO as the main evolution method. The velocity, a sensitive parameter of PSO, is adjusted dynamically to increase the precision of PSO. To overcome the drawback of premature in PSO, chaotic local search is imported into proposed algorithm. Moreover, a new strategy is proposed to handle the various constraints of DED problem in this paper, the results solved by proposed strategy can satisfy the constraints of DED problem well. Finally, the high feasibility and effectiveness of proposed CSAPSO algorithm is validated by three test systems consisting of 10 and extended 30 generators while compared with the experimental results calculated by the other methods reported in this literature. |
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