Swarm-based mean-variance mapping optimization (MVMOS) for solving non-convex economic dispatch problems

Khoa, T.H. and Vasant, P.M. and Singh, B.S.M. and Dieu, V.N. (2015) Swarm-based mean-variance mapping optimization (MVMOS) for solving non-convex economic dispatch problems. IGI Global, pp. 211-251. ISBN 9781466682924; 1466682914; 9781466682917

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Abstract

The practical Economic Dispatch (ED) problems have non-convex objective functions with complex constraints due to the effects of valve point loadings, multiple fuels, and prohibited zones. This leads to difficulty in finding the global optimal solution of the ED problems. This chapter proposes a new swarm-based Mean-Variance Mapping Optimization (MVMOS) for solving the non-convex ED. The proposed algorithm is a new population-based meta-heuristic optimization technique. Its special feature is a mapping function applied for the mutation. The proposed MVMOS is tested on several test systems and the comparisons of numerical obtained results between MVMOS and other optimization techniques are carried out. The comparisons show that the proposed method is more robust and provides better solution quality than most of the other methods. Therefore, the MVMOS is very favorable for solving non-convex ED problems. © 2015, IGI Global. All rights reserved.

Item Type: Book
Additional Information: cited By 5
Uncontrolled Keywords: Mapping; Optimization; Scheduling, Complex constraints; Economic dispatch problems; Global optimal solutions; Mapping optimization; Meta-heuristic optimization techniques; Non-convex economic dispatches; Non-convex objective functions; Optimization techniques, Electric load dispatching
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:17
Last Modified: 09 Nov 2023 16:17
URI: https://khub.utp.edu.my/scholars/id/eprint/5959

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