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Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem

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Recent Advances on Soft Computing and Data Mining (SCDM 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 978))

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Abstract

Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. Once trapped in any sub-optimal region, the algorithm is unable to escape because of deficiency in population diversity. To address this, an enhanced Bat Algorithm (EBA) is introduced in this paper. The EBA algorithm comes with adaptive exploration and exploitation capability, as well as, additional population diversity. This enables EBA improve its convergence ability to find even better solutions towards the end of search process, where standard BA is often trapped. To illustrate effectiveness of the proposed method, EBA is applied on non-linear, non-convex economic dispatch problem with a power generation system comprising of twenty thermal units. The experimental results suggest that EBA not only saved power generation cost but also reduced transmission losses, more efficiently as compared to original BA and other methods reported in literature. The EBA algorithm also showed enhanced convergence ability than BA towards the end of iterations.

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Acknowledgments

The authors would like to thank University of Electronic Science and Technology of China (UESTC) and National Natural Science Foundation of China (NSFC) for supporting this research under Grant No. 61772120.

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Authors and Affiliations

  1. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

    Kashif Hussain & William Zhu

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mohd Najib Mohd Salleh & Haseeb Ali

  3. Faculty of Science and Information Technology, Universiti Teknologi PETRONAS, Perak, Malaysia

    Noreen Talpur

  4. Department of Computer Science, City University of Science and Information Technology, Peshawar, Pakistan

    Rashid Naseem

  5. Department of Computer Science, University of Swabi, Swabi, Pakistan

    Arshad Ahmad & Ayaz Ullah

Authors
  1. Kashif Hussain
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  2. William Zhu
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  3. Mohd Najib Mohd Salleh
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  4. Haseeb Ali
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  5. Noreen Talpur
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  6. Rashid Naseem
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  7. Arshad Ahmad
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  8. Ayaz Ullah
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Corresponding author

Correspondence to Kashif Hussain .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Rozaida Ghazali

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Nazri Mohd Nawi

  3. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Mustafa Mat Deris

  4. School of Information Technology, Deakin University, Geelong Waurn Ponds Campus, VIC, Australia

    Jemal H. Abawajy

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Hussain, K. et al. (2020). Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem. In: Ghazali, R., Nawi, N., Deris, M., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2020. Advances in Intelligent Systems and Computing, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-030-36056-6_39

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