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Swarm-Based Mean-Variance Mapping Optimization (MVMOS) for Solving Non-Convex Economic Dispatch Problems
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Author(s): Truong Hoang Khoa (Universiti Teknologi Petronas, Malaysia), Pandian Vasant (Universiti Teknologi PETRONAS, Malaysia), Balbir Singh Mahinder Singh (Universiti Teknologi Petronas, Malaysia)and Vo Ngoc Dieu (HCMC University of Technology, Vietnam)
Copyright: 2015
Pages: 41
Source title:
Handbook of Research on Swarm Intelligence in Engineering
Source Author(s)/Editor(s): Siddhartha Bhattacharyya (RCC Institute of Information Technology, India)and Paramartha Dutta (Visva-Bharati University, India)
DOI: 10.4018/978-1-4666-8291-7.ch007
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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.
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