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Hybrid Differential Evolution and Gravitational Search Algorithm for Nonconvex Economic Dispatch

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Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 2))

Abstract

The hybrid differential evolution and gravitational search algorithm (DEGSA) to solve economic dispatch (ED) problems with non-convex cost functions is presented in this paper with various generator constraints in power systems. The proposed DEGSA method is an improved differential evolution method based on the gravitational search algorithm scheme. The DEGSA method has the flexible adjustment of the parameters to get a better optimal solution. Moreover, an effective constraint handling framework in the method is employed for properly handling equality and inequality constraints of the problems. The proposed DEGSA has been tested on three systems with 13, 15, 40 units and the obtained results from the DEGSA algorithm have been compared to those from other methods in the literature. The result comparison has indicated that the proposed DEGSA method is more effective than many other methods for obtaining better optimal solution for the test systems. Therefore, the proposed DEGSA is a very favorable method for solving the non-convex ED problems.

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Author information

Authors and Affiliations

  1. Ho Chi Minh City University of Technology (Hutech), Ho Chi Minh City, Vietnam

    Luong D. Le & Loc D. Ho

  2. Department of Power Systems, HCMC University of Technology, Ho Chi Minh City, Vietnam

    Dieu N. Vo

  3. Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Teronoh, Malaysia

    Pandian Vasant

Authors
  1. Luong D. Le
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  2. Loc D. Ho
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  3. Dieu N. Vo
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  4. Pandian Vasant
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Corresponding author

Correspondence to Luong D. Le .

Editor information

Editors and Affiliations

  1. Faculty of Science and Technology Department of Infomatics, Kindai University, Higashi-Osaka, Japan

    Hisashi Handa

  2. Department of Computer Science and Intelligent Systems, Osaka Prefecture University, Osaka, Japan

    Hisao Ishibuchi

  3. School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

    Yew-Soon Ong

  4. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Kay-Chen Tan

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© 2015 Springer International Publishing Switzerland

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Le, L.D., Ho, L.D., Vo, D.N., Vasant, P. (2015). Hybrid Differential Evolution and Gravitational Search Algorithm for Nonconvex Economic Dispatch. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, KC. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-13356-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-13356-0_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13355-3

  • Online ISBN: 978-3-319-13356-0

  • eBook Packages: EngineeringEngineering (R0)

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