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Solving Economic Dispatch By Using Swarm Based Mean-Variance Mapping Optimization (MVMOS) | OMICS International | Abstract
ISSN: 2229-8711

Global Journal of Technology and Optimization
Open Access

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Research Article

Solving Economic Dispatch By Using Swarm Based Mean-Variance Mapping Optimization (MVMOS)

Truong Khoa H1*, Vasant P1, Balbir Singh1 and Vo Dieu N2

1Department of Fundamental and Applied Sciences, Universiti Teknologi Petronas, Malaysia

2Department of Power Systems, HCMC University of Technology, Vietnam

Corresponding Author:
Dr. Truong H Khoa
Department of Fundamental and
Applied Sciences, Universiti Teknologi
Petronas, Malaysia
Tel:
+60 5-368 8000
E-mail: [email protected]

Received Date: April 11, 2015 Accepted Date: June 29, 2015 Published Date: July 06, 2015

Citation: Khoa TH, Vasant P, Singh B, Dieu VN (2015) Solving Economic Dispatch By Using Swarm Based Mean-Variance Mapping Optimization (MVMOS). Global J Technol Optim 6:184. doi:10.4172/2229-8711.1000184

Copyright: © 2015 Khoa TH, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

This paper proposes a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS) for solving the economic dispatch. The proposed optimization algorithm is the extension of the original single particle mean-variance mapping optimization (MVMO). The novel feature is the special mapping function applied for the mutation base on the mean and variance of n-best population.The MVMOS outperforms the classical MVMO in global search ability due to the improvement of the mapping. The proposed MVMOS is investigated on four test power systems, including 3-, 13- , 20- thermal generating units and large-scale system 140 units with quadratic cost function and the obtained results are compared with many other known methods in the literature. Test results show that the proposed method can efficiently implement for solving economic dispatch.

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