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Optimal placement of different types of DG units considering various load models using novel multiobjective quasi-oppositional grey wolf optimizer

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Abstract

The optimal placement of Distributed Generation (DG) units in radial distribution system is one of the important ways for techno-economic improvements. The maximum technical benefits can be extracted by minimizing the distribution power loss as well as bus voltage deviation, whereas the maximum economical benefits can be procured by minimizing the total yearly economic loss which includes installation, operation and maintenance cost. So for the maximum techno-economic benefits, all three objectives should be simultaneously minimized by considering a multiobjective optimization technique. For optimal results, a Pareto optimal concept-based novel multiobjective quasi-oppositional grey wolf optimizer (MQOGWO) algorithm has been proposed. The performance of the proposed algorithm has been tested on IEEE-33 bus radial distribution system. In this analysis, various voltage-dependent load models such as constant power, constant current, constant impedance, residential, industrial and commercial load models have been considered at different loading conditions like light load, full load and heavy load. The effects of DG type on the system performance have also been analyzed to find the best optimal solution.

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Acknowledgments

The authors acknowledge the support rendered by UGC UPE II Program and DRS scheme of Power Engg. Dept., Jadavpur University, India.

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Authors and Affiliations

  1. Electrical Engineering Department, Gargi Memorial Institute of Technology, Baruipur, Kolkata, India

    Sajjan Kumar

  2. Power Engineering Department, Jadavpur University, Kolkata, India

    Kamal Krishna Mandal & Niladri Chakraborty

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  1. Sajjan Kumar
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  2. Kamal Krishna Mandal
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  3. Niladri Chakraborty
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Correspondence to Sajjan Kumar.

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Kumar, S., Mandal, K.K. & Chakraborty, N. Optimal placement of different types of DG units considering various load models using novel multiobjective quasi-oppositional grey wolf optimizer. Soft Comput 25, 4845–4864 (2021). https://doi.org/10.1007/s00500-020-05494-3

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