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Artificial immune system based approach for size and location optimization of distributed generation in distribution system

Author

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  • Vikas Singh Bhadoria

    (ABES, Engineering College)

  • Nidhi Singh Pal

    (Gautam Buddha University)

  • Vivek Shrivastava

    (National Institute of Technology)

Abstract

An increase in the share of distributed generation (DG) in the global generation system is a direct indication of the development of available technologies. The extraction of natural energy resources and their use as DG has several advantages, such as the reduction in line losses, improved voltage profile and reliability, etc., but the incorrect installation of these power plants can also have some negative effects. The innovation in technology has motivated to extract the maximum benefit of natural energy resources. Due to this, the capacity and location of these energy resources should be carefully identified. The optimal placement of a distributed generation power plant, in the existing network, is analyzed in this article. The proposed methodology is inspired by the human immune system. In this methodology clonal selection principle of immune system is combined with particle swarm optimization. For checking the validity of the proposed method two test systems, IEEE 33-node radial distribution system and IEEE 14-node loop distribution system, are considered. Results show the validity of the proposed algorithm in radial as well as in loop distribution system.

Suggested Citation

  • Vikas Singh Bhadoria & Nidhi Singh Pal & Vivek Shrivastava, 2019. "Artificial immune system based approach for size and location optimization of distributed generation in distribution system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 339-349, June.
    • Handle: RePEc:spr:ijsaem:v:10:y:2019:i:3:d:10.1007_s13198-019-00779-9
    DOI: 10.1007/s13198-019-00779-9
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    References listed on IDEAS

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    1. Muttaqi, K.M. & Le, An D.T. & Aghaei, J. & Mahboubi-Moghaddam, E. & Negnevitsky, M. & Ledwich, G., 2016. "Optimizing distributed generation parameters through economic feasibility assessment," Applied Energy, Elsevier, vol. 165(C), pages 893-903.
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    7. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
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    Cited by:

    1. Al-Attar Ali Mohamed & Shimaa Ali & Salem Alkhalaf & Tomonobu Senjyu & Ashraf M. Hemeida, 2019. "Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm," Sustainability, MDPI, vol. 11(23), pages 1-20, November.
    2. Mandhir Kumar Verma & Vivekananda Mukherjee & Vinod Kumar Yadav & Santosh Ghosh, 2020. "Constraints for effective distribution network expansion planning: an ample review," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 531-546, June.
    3. Lenin Kanagasabai, 2022. "Real power loss reduction by quantum based Ptilonorhynchus violaceus optimization and Haliastur Indus algorithms," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(4), pages 1913-1931, August.

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