Optimizing capacitor size and placement in radial distribution networks for maximum efficiency
As distribution systems continue to expand, they face challenges such as increased system losses and inadequate voltage regulation. To address these issues, shunt capacitors are being deployed in distribution networks. These capacitors offer reactive power compensation, enhance power factor, improve...
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Elsevier
2024-12-01
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| Series: | Systems and Soft Computing |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772941924000401 |
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| author | R. Arunjothi K.P. Meena |
| author_facet | R. Arunjothi K.P. Meena |
| author_sort | R. Arunjothi |
| collection | DOAJ |
| description | As distribution systems continue to expand, they face challenges such as increased system losses and inadequate voltage regulation. To address these issues, shunt capacitors are being deployed in distribution networks. These capacitors offer reactive power compensation, enhance power factor, improve voltage profiles, promote system stability, and significantly reduce losses. However, determining the appropriate capacitor sizes and their optimal placements requires careful consideration of both technical and economic factors. The nonlinear nature of optimal capacitor placement and sizing, leveraging optimization techniques becomes crucial in identifying the best locations and values for capacitors. This paper demonstrates the effective utilization of Particle Swarm Optimization (PSO) and Real Coded Genetic Algorithm (RCGA) optimization techniques for capacitor placement and selection. The optimization techniques are applied to a 33-bus IEEE standard radial distribution system, to reduce the real power loss and to improve the voltage profile considering both constant and variable loads. Both PSO and RCGA algorithms identify suitable locations for the placement of capacitors for reactive power compensation within the distribution system. By optimizing the objective function associated with capacitor placement costs and maximizing annual cost savings, the PSO and RCGA techniques yield promising results. After implementing the optimal capacitor placements at the identified candidate nodes, a significant reduction in losses within the radial distribution system is observed. Moreover, the cost savings achieved through optimal placement and sizing are substantial. |
| format | Article |
| id | doaj-art-fa67a0c22bbf460abe35fbf12f8ea524 |
| institution | OA Journals |
| issn | 2772-9419 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
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| series | Systems and Soft Computing |
| spelling | doaj-art-fa67a0c22bbf460abe35fbf12f8ea5242025-08-20T02:34:40ZengElsevierSystems and Soft Computing2772-94192024-12-01620011110.1016/j.sasc.2024.200111Optimizing capacitor size and placement in radial distribution networks for maximum efficiencyR. Arunjothi0K.P. Meena1Corresponding author.; Central Power Research Institute, Bangalore, Karnataka, IndiaCentral Power Research Institute, Bangalore, Karnataka, IndiaAs distribution systems continue to expand, they face challenges such as increased system losses and inadequate voltage regulation. To address these issues, shunt capacitors are being deployed in distribution networks. These capacitors offer reactive power compensation, enhance power factor, improve voltage profiles, promote system stability, and significantly reduce losses. However, determining the appropriate capacitor sizes and their optimal placements requires careful consideration of both technical and economic factors. The nonlinear nature of optimal capacitor placement and sizing, leveraging optimization techniques becomes crucial in identifying the best locations and values for capacitors. This paper demonstrates the effective utilization of Particle Swarm Optimization (PSO) and Real Coded Genetic Algorithm (RCGA) optimization techniques for capacitor placement and selection. The optimization techniques are applied to a 33-bus IEEE standard radial distribution system, to reduce the real power loss and to improve the voltage profile considering both constant and variable loads. Both PSO and RCGA algorithms identify suitable locations for the placement of capacitors for reactive power compensation within the distribution system. By optimizing the objective function associated with capacitor placement costs and maximizing annual cost savings, the PSO and RCGA techniques yield promising results. After implementing the optimal capacitor placements at the identified candidate nodes, a significant reduction in losses within the radial distribution system is observed. Moreover, the cost savings achieved through optimal placement and sizing are substantial.http://www.sciencedirect.com/science/article/pii/S2772941924000401Optimal capacitor placementRadial distribution systemParticle Swarm Optimization (PSO)Real Coded Genetic Algorithm (RCGA) |
| spellingShingle | R. Arunjothi K.P. Meena Optimizing capacitor size and placement in radial distribution networks for maximum efficiency Systems and Soft Computing Optimal capacitor placement Radial distribution system Particle Swarm Optimization (PSO) Real Coded Genetic Algorithm (RCGA) |
| title | Optimizing capacitor size and placement in radial distribution networks for maximum efficiency |
| title_full | Optimizing capacitor size and placement in radial distribution networks for maximum efficiency |
| title_fullStr | Optimizing capacitor size and placement in radial distribution networks for maximum efficiency |
| title_full_unstemmed | Optimizing capacitor size and placement in radial distribution networks for maximum efficiency |
| title_short | Optimizing capacitor size and placement in radial distribution networks for maximum efficiency |
| title_sort | optimizing capacitor size and placement in radial distribution networks for maximum efficiency |
| topic | Optimal capacitor placement Radial distribution system Particle Swarm Optimization (PSO) Real Coded Genetic Algorithm (RCGA) |
| url | http://www.sciencedirect.com/science/article/pii/S2772941924000401 |
| work_keys_str_mv | AT rarunjothi optimizingcapacitorsizeandplacementinradialdistributionnetworksformaximumefficiency AT kpmeena optimizingcapacitorsizeandplacementinradialdistributionnetworksformaximumefficiency |