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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Vydané v:Mathematical problems in engineering Ročník 2021; s. 1 - 13
Hlavní autori: Nguyen Hoang, Minh-Tuan, Truong, Bao-Huy, Hoang, Khoa Truong, Dang Tuan, Khanh, Vo Ngoc, Dieu
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Hindawi 24.12.2021
John Wiley & Sons, Inc
Predmet:
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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Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1024-123X
1563-5147
DOI:10.1155/2021/2065043