Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer

The arrangement of distributed generation networks through optimal capacitor placement and sizing is critical for modern power systems, particularly in the context of renewable energy sources with inherent uncertainties. As renewable sources such as wind and solar introduce variability in power generation, the stability and efficiency of the distribution network can be significantly affected. This study addresses the challenge of optimizing distribution network configurations by integrating capacitor placement and distributed generation sizing under these renewable energy uncertainties. Using a self-adaptive Kho-Kho optimizer, the research aims to minimize operational costs while improving technical parameters, such as voltage stability and loss reduction. The proposed method was applied to the IEEE 33-bus standard network, yielding significant improvements. Specifically, a capacitor was placed at bus 9 with a capacity of 2260 kVar, and a 110 kW distributed generation unit was installed at bus 14. Post-optimization results indicated a reduction in power loss costs from 4.11 × 10^5 to 1.05 × 10^5 units, representing a 25.54% decrease. Additionally, energy purchased from the upstream network dropped by 19.81%, and the total operational cost decreased by 9.35%, from 8.77 × 10^6 to 7.95 × 10^6 units. These results underscore the effectiveness of the proposed optimization strategy in enhancing network performance while minimizing costs, offering a valuable approach for future distribution network management. Further research will explore multi objective algorithms and the incorporation of additional types of distributed generation to continue improving reliability and stability.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-09-01
DOI
https://doi.org/10.22034/jaism.2024.472210.1050
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
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article

Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer

SHILAP Revista de lepidopterología
Optimal Power Flow Distribution
article

Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer

article en

Abstract

The arrangement of distributed generation networks through optimal capacitor placement and sizing is critical for modern power systems, particularly in the context of renewable energy sources with inherent uncertainties. As renewable sources such as wind and solar introduce variability in power generation, the stability and efficiency of the distribution network can be significantly affected. This study addresses the challenge of optimizing distribution network configurations by integrating capacitor placement and distributed generation sizing under these renewable energy uncertainties. Using a self-adaptive Kho-Kho optimizer, the research aims to minimize operational costs while improving technical parameters, such as voltage stability and loss reduction. The proposed method was applied to the IEEE 33-bus standard network, yielding significant improvements. Specifically, a capacitor was placed at bus 9 with a capacity of 2260 kVar, and a 110 kW distributed generation unit was installed at bus 14. Post-optimization results indicated a reduction in power loss costs from 4.11 × 10^5 to 1.05 × 10^5 units, representing a 25.54% decrease. Additionally, energy purchased from the upstream network dropped by 19.81%, and the total operational cost decreased by 9.35%, from 8.77 × 10^6 to 7.95 × 10^6 units. These results underscore the effectiveness of the proposed optimization strategy in enhancing network performance while minimizing costs, offering a valuable approach for future distribution network management. Further research will explore multi objective algorithms and the incorporation of additional types of distributed generation to continue improving reliability and stability.

SHILAP Revista de lepidopterología
Yangzhou Vocational University (CN)
Affordable and clean energy
Openalex Percentile: Top 66%
Optimal Power Flow Distribution
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