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 gene...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Bilijipub publisher
2024-09-01
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| Series: | Journal of Artificial Intelligence and System Modelling |
| Subjects: | |
| Online Access: | https://jaism.bilijipub.com/article_206717_45fec3666a479ab135e245c43cc1a51a.pdf |
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| Summary: | 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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| ISSN: | 3041-850X |