This paper presents a novel and efficient optimisation approach based on the ant colony optimisation (ACO) for solving the economic dispatch (ED) problem with non-smooth cost functions. In order to improve the performance of ACO algorithm, three additional techniques, i.e. priority list, variable reduction, and zoom feature are presented. To show its efficiency and effectiveness, the proposed ACO is applied to two types of ED problems with non-smooth cost functions. Firstly, the ED problem with valve-point loading effects consists of 13 and 40 generating units. Secondly, the ED problem considering the multiple fuels consists of 10 units. Additionally, the results of the proposed ACO are compared with those of the conventional heuristic approaches. The experimental results show that the proposed ACO approach is comparatively capable of obtaining higher quality solution and faster computational time. (C) 2009 Elsevier Ltd. All rights reserved.
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Univ Technol, Fac Engn & Informat Technol, Sydney, NSW 2007, AustraliaUniv Technol, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia
Lu, Haiyan
Sriyanyong, Pichet
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King Mongkuts Univ Technol, Fac Tech Educ, Dept Teacher Training Elect Engn, N Bangkok, ThailandUniv Technol, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia
Sriyanyong, Pichet
Song, Yong Hua
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Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R ChinaUniv Technol, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia
Song, Yong Hua
Dillon, Tharam
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Curtin Univ Technol, Digital Ecosyst & Business Intelligence Inst, Perth, WA 6845, AustraliaUniv Technol, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia