A Quasioppositional-Chaotic Symbiotic Organisms Search Algorithm for Distribution Network Reconfiguration with Distributed Generations

This study suggests an enhanced metaheuristic method based on the Symbiotic Organisms Search (SOS) algorithm, namely, Quasioppositional Chaotic Symbiotic Organisms Search (QOCSOS). It aims to optimize the network configuration simultaneously and allocate distributed generation (DG) subject to the mi...

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Published in:Mathematical problems in engineering Vol. 2021; pp. 1 - 13
Main Authors: Nguyen Hoang, Minh-Tuan, Truong, Bao-Huy, Hoang, Khoa Truong, Dang Tuan, Khanh, Vo Ngoc, Dieu
Format: Journal Article
Language:English
Published: New York Hindawi 24.12.2021
John Wiley & Sons, Inc
Subjects:
Algorithms
Distributed generation
Electric power distribution
Heuristic
Heuristic methods
Methods
Optimization
Organisms
Power
Radial distribution
Reconfiguration
Search algorithms
ISSN:1024-123X, 1563-5147
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Abstract This study suggests an enhanced metaheuristic method based on the Symbiotic Organisms Search (SOS) algorithm, namely, Quasioppositional Chaotic Symbiotic Organisms Search (QOCSOS). It aims to optimize the network configuration simultaneously and allocate distributed generation (DG) subject to the minimum real power loss in radial distribution networks (RDNs). The suggested method is developed by integrating the Quasiopposition-Based Learning (QOBL) as well as Chaotic Local Search (CLS) approaches into the original SOS algorithm to obtain better global search capacity. The proposed QOCSOS algorithm is tested on 33-, 69-, and 119-bus RDNs to verify its effectiveness. The findings demonstrate that the suggested QOCSOS technique outperformed the original SOS and provided higher-quality alternatives than many other methods studied. Accordingly, the proposed QOCSOS algorithm is favourable in adapting to the DG placement problems and optimal distribution network reconfiguration.
AbstractList This study suggests an enhanced metaheuristic method based on the Symbiotic Organisms Search (SOS) algorithm, namely, Quasioppositional Chaotic Symbiotic Organisms Search (QOCSOS). It aims to optimize the network configuration simultaneously and allocate distributed generation (DG) subject to the minimum real power loss in radial distribution networks (RDNs). The suggested method is developed by integrating the Quasiopposition-Based Learning (QOBL) as well as Chaotic Local Search (CLS) approaches into the original SOS algorithm to obtain better global search capacity. The proposed QOCSOS algorithm is tested on 33-, 69-, and 119-bus RDNs to verify its effectiveness. The findings demonstrate that the suggested QOCSOS technique outperformed the original SOS and provided higher-quality alternatives than many other methods studied. Accordingly, the proposed QOCSOS algorithm is favourable in adapting to the DG placement problems and optimal distribution network reconfiguration.
Author Truong, Bao-Huy
Hoang, Khoa Truong
Vo Ngoc, Dieu
Nguyen Hoang, Minh-Tuan
Dang Tuan, Khanh
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ContentType Journal Article
Copyright Copyright © 2021 Minh-Tuan Nguyen Hoang et al.
Copyright © 2021 Minh-Tuan Nguyen Hoang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms Algorithms
Distributed generation
Electric power distribution
Heuristic
Heuristic methods
Methods
Optimization
Organisms
Power
Radial distribution
Reconfiguration
Search algorithms
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Title A Quasioppositional-Chaotic Symbiotic Organisms Search Algorithm for Distribution Network Reconfiguration with Distributed Generations
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