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Performance Comparison of Recent Nature-Inspired Optimization Algorithms in Optimal Placement and Sizing of Distributed Energy Resources

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Abstract

Through the integration of distributed generation into the distribution network, several benefits can be achieved, including minimization of system losses, enhancement of voltage profiles, and improvement of network reliability and security. One of the best ways to maximize the benefits of distributed generation units is to optimize the location and size of these units in the network. The main objective of this paper is the application and comparison of five recently developed optimization algorithms for optimizing the allocation of multiple distributed generators in the distribution network. The algorithms include the hybrid grey wolf optimizer and cuckoo search, bald eagle search, marine predator algorithm, artificial ecosystem optimizer, and slime mould algorithm. Three objectives are set in the problem of determining the optimal allocation of distributed generators, including the reduction of energy losses, enhancement of voltage profile, and improvement of voltage stability. The proposed optimization algorithms are evaluated and compared using IEEE 33-bus and IEEE 69-bus radial distribution networks. Numerical results show that the proposed algorithms are very competitive in their ability to allocate distributed generators optimally. However, artificial ecosystem optimizer and bald eagle search outperform other algorithms.

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Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

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Authors and Affiliations

  1. Department of Electrical Engineering, University of Ferhat Abbas, Setif 1, 19000, Setif, Algeria

    Mohammed Amroune, Arif Bourzami & Linda Slimani

  2. Department of Electrical Engineering, University of Kasdi Merbah, 30000, Ouargla, Algeria

    Abdelkader Boukaroura

  3. Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450, Shah Alam, Malaysia

    Ismail Musirin

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  1. Mohammed Amroune
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  2. Abdelkader Boukaroura
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  3. Arif Bourzami
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  4. Linda Slimani
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  5. Ismail Musirin
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Correspondence to Mohammed Amroune.

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Amroune, M., Boukaroura, A., Bourzami, A. et al. Performance Comparison of Recent Nature-Inspired Optimization Algorithms in Optimal Placement and Sizing of Distributed Energy Resources. Process Integr Optim Sustain 7, 641–654 (2023). https://doi.org/10.1007/s41660-022-00306-7

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  • DOI: https://doi.org/10.1007/s41660-022-00306-7

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