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

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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.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, ABES, Engineering College, Ghaziabad, U.P., 201009, India

    Vikas Singh Bhadoria

  2. Department of Electrical Engineering, Gautam Buddha University, Greater Noida, U.P., 201312, India

    Nidhi Singh Pal

  3. Department of Electrical Engineering, National Institute of Technology, Delhi, 110040, India

    Vivek Shrivastava

Authors
  1. Vikas Singh Bhadoria
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  2. Nidhi Singh Pal
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  3. Vivek Shrivastava
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Correspondence to Vikas Singh Bhadoria.

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Bhadoria, V.S., Pal, N.S. & Shrivastava, V. Artificial immune system based approach for size and location optimization of distributed generation in distribution system. Int J Syst Assur Eng Manag 10, 339–349 (2019). https://doi.org/10.1007/s13198-019-00779-9

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  • DOI: https://doi.org/10.1007/s13198-019-00779-9

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