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Distribution Network Reconfiguration Using Hybrid Optimization Technique

S. Arun Kumar*, S. Padma, S. Madhubalan

Department of EEE, Sona College of Technology, Salem, Tamilnadu, 636005, India

* Corresponding Author: S. Arun Kumar. Email: email

Intelligent Automation & Soft Computing 2022, 33(2), 777-789. https://doi.org/10.32604/iasc.2022.023702

Abstract

Energy management carried in a power system by configuration process is a difficult activity. So, reconfiguration has been introduced to solve this problem. Numerous optimization topologies have been utilized to solve this problem so far. However, they exhibit some drawbacks such as convergence, etc. Hence to overcome this issue, this work formulated a new hybrid optimization topology Genetic Algorithm Enabled Particle Swarm Optimization (PSOGA) to solve the energy configuration problem with low power loss in the Distribution System (DS). The proposed topology’s effectiveness was evaluated on the IEEE 33 bus Distribution System, and the results were compared to methods reported in the literature. As a result, the suggested technique appears to be more successful than other approaches, and the power loss in buses is minimised and hence exhibits an enhanced voltage profile. Hence, it is concluded that the proposed PSOGA can be a promising topology for reconfiguration as well as energy management in DS.

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APA Style
Kumar, S.A., Padma, S., Madhubalan, S. (2022). Distribution network reconfiguration using hybrid optimization technique. Intelligent Automation & Soft Computing, 33(2), 777-789. https://doi.org/10.32604/iasc.2022.023702
Vancouver Style
Kumar SA, Padma S, Madhubalan S. Distribution network reconfiguration using hybrid optimization technique. Intell Automat Soft Comput . 2022;33(2):777-789 https://doi.org/10.32604/iasc.2022.023702
IEEE Style
S.A. Kumar, S. Padma, and S. Madhubalan "Distribution Network Reconfiguration Using Hybrid Optimization Technique," Intell. Automat. Soft Comput. , vol. 33, no. 2, pp. 777-789. 2022. https://doi.org/10.32604/iasc.2022.023702



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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