The dynamic economic dispatch (DED) is a complicated nonlinear dynamic constrained problem which occupies an important role in the economic operation of power system. An adaptive hybrid differential evolution algorithm (AHDE) is proposed in this paper to solve DED problem. In the proposed algorithm, an adaptive dynamic parameter control mechanism is adopted to obtain parameter settings in differential evolution algorithm (DE). Moreover, a local random search (LRS) operator is integrated with DE to avoid premature convergence. In view of the difficulties of handling the complicated constraints of DED problem, a new heuristic constraints handling method which does not require penalty factor settings is presented. The feasibility and effectiveness of the proposed method is demonstrated for an application example. Compared with other algorithms, AHDE can find the global optimum dispatch result with a shorter computational time along with higher effectiveness and robustness. (C) 2009 Elsevier Ltd. All rights reserved.
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Jiangsu Normal Univ, Sch Elect Engn & Automat, Xuzhou 221116, Jiangsu, Peoples R ChinaJiangsu Normal Univ, Sch Elect Engn & Automat, Xuzhou 221116, Jiangsu, Peoples R China
Zou, Dexuan
Li, Steven
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RMIT Univ, Grad Sch Business & Law, 379-405 Russell St, Melbourne, Vic 3000, AustraliaJiangsu Normal Univ, Sch Elect Engn & Automat, Xuzhou 221116, Jiangsu, Peoples R China
Li, Steven
Wang, Gai-Ge
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Jiangsu Normal Univ, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R ChinaJiangsu Normal Univ, Sch Elect Engn & Automat, Xuzhou 221116, Jiangsu, Peoples R China
Wang, Gai-Ge
Li, Zongyan
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China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221116, Peoples R ChinaJiangsu Normal Univ, Sch Elect Engn & Automat, Xuzhou 221116, Jiangsu, Peoples R China
Li, Zongyan
Ouyang, Haibin
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Guangzhou Univ, Sch Mech & Elect Engn, Guangzhou 510006, Guangdong, Peoples R ChinaJiangsu Normal Univ, Sch Elect Engn & Automat, Xuzhou 221116, Jiangsu, Peoples R China