Advanced particle swarm optimization for efficient coordination of distributed generators in power distribution networks
Abstract Integrating distributed generators (DGs) into electrical power networks remains a significant area of research which has several technical and economic benefits for optimum performance, especially at the distribution level. This study presents a model of power distribution networks with ren...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-07-01
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| Series: | Journal of Electrical Systems and Information Technology |
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| Online Access: | https://doi.org/10.1186/s43067-025-00231-y |
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| author | Funso Kehinde Ariyo Ayooluwa Peter Adeagbo Oludamilare Bode Adewuyi Samson Oladayo Ayanlade Tayo Uthman Badrudeen |
| author_facet | Funso Kehinde Ariyo Ayooluwa Peter Adeagbo Oludamilare Bode Adewuyi Samson Oladayo Ayanlade Tayo Uthman Badrudeen |
| author_sort | Funso Kehinde Ariyo |
| collection | DOAJ |
| description | Abstract Integrating distributed generators (DGs) into electrical power networks remains a significant area of research which has several technical and economic benefits for optimum performance, especially at the distribution level. This study presents a model of power distribution networks with renewable distributed generation (DG) units. It adapted Loss Sensitivity Factor (LSF) and Constriction Coefficient Particle Swarm Optimization (CCPSO) technique to ascertain the optimal placement and sizing of the DG units. The numerical analysis is executed on the Imalefalafia 32-bus network which is a real distribution network in Nigeria and the commonly known standard IEEE 33-bus network. The result shows that the scenario where cost minimization with loss reduction and voltage stability improvement concurrently performs better than other scenarios for different numbers of allocated DGs. With 3 DGs incorporation, the real and reactive power loss reduction of 62.46% and 62.32%, respectively, were achieved in scenario three compared to 14.06% and 14.46% in scenario two and 61.48% and 61.46% in scenario one for IEEE 33-bus RDN while for Imalefalafia 32-bus, the real and reactive power loss were reduced by 71.07% and 71.13% were achieved in scenario three compared to 43.95% and 43.99% in scenario two and 55.87% and 55.92% in scenario one. It was also observed that the voltage at the worst performing bus improves significantly better for scenario 3 for all numbers of DGs compared to the other scenarios. |
| format | Article |
| id | doaj-art-019831f675fb45b6afa9374cdefdb3f2 |
| institution | Kabale University |
| issn | 2314-7172 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Electrical Systems and Information Technology |
| spelling | doaj-art-019831f675fb45b6afa9374cdefdb3f22025-08-20T04:01:53ZengSpringerOpenJournal of Electrical Systems and Information Technology2314-71722025-07-0112112310.1186/s43067-025-00231-yAdvanced particle swarm optimization for efficient coordination of distributed generators in power distribution networksFunso Kehinde Ariyo0Ayooluwa Peter Adeagbo1Oludamilare Bode Adewuyi2Samson Oladayo Ayanlade3Tayo Uthman Badrudeen4Department of Electronic and Electrical Engineering, Obafemi Awolowo UniversityDepartment of Electronic and Electrical Engineering, Obafemi Awolowo UniversityFaculty of Engineering, Information and Systems, University of TsukubaDepartment of Electrical and Electronic Engineering, Lead City UniversityDepartment of Electrical and Electronic Engineering, Oduduwa UniversityAbstract Integrating distributed generators (DGs) into electrical power networks remains a significant area of research which has several technical and economic benefits for optimum performance, especially at the distribution level. This study presents a model of power distribution networks with renewable distributed generation (DG) units. It adapted Loss Sensitivity Factor (LSF) and Constriction Coefficient Particle Swarm Optimization (CCPSO) technique to ascertain the optimal placement and sizing of the DG units. The numerical analysis is executed on the Imalefalafia 32-bus network which is a real distribution network in Nigeria and the commonly known standard IEEE 33-bus network. The result shows that the scenario where cost minimization with loss reduction and voltage stability improvement concurrently performs better than other scenarios for different numbers of allocated DGs. With 3 DGs incorporation, the real and reactive power loss reduction of 62.46% and 62.32%, respectively, were achieved in scenario three compared to 14.06% and 14.46% in scenario two and 61.48% and 61.46% in scenario one for IEEE 33-bus RDN while for Imalefalafia 32-bus, the real and reactive power loss were reduced by 71.07% and 71.13% were achieved in scenario three compared to 43.95% and 43.99% in scenario two and 55.87% and 55.92% in scenario one. It was also observed that the voltage at the worst performing bus improves significantly better for scenario 3 for all numbers of DGs compared to the other scenarios.https://doi.org/10.1186/s43067-025-00231-yDistribution networkDistributed generationEnergy storagePower lossOptimizationTechno-economic analysis |
| spellingShingle | Funso Kehinde Ariyo Ayooluwa Peter Adeagbo Oludamilare Bode Adewuyi Samson Oladayo Ayanlade Tayo Uthman Badrudeen Advanced particle swarm optimization for efficient coordination of distributed generators in power distribution networks Journal of Electrical Systems and Information Technology Distribution network Distributed generation Energy storage Power loss Optimization Techno-economic analysis |
| title | Advanced particle swarm optimization for efficient coordination of distributed generators in power distribution networks |
| title_full | Advanced particle swarm optimization for efficient coordination of distributed generators in power distribution networks |
| title_fullStr | Advanced particle swarm optimization for efficient coordination of distributed generators in power distribution networks |
| title_full_unstemmed | Advanced particle swarm optimization for efficient coordination of distributed generators in power distribution networks |
| title_short | Advanced particle swarm optimization for efficient coordination of distributed generators in power distribution networks |
| title_sort | advanced particle swarm optimization for efficient coordination of distributed generators in power distribution networks |
| topic | Distribution network Distributed generation Energy storage Power loss Optimization Techno-economic analysis |
| url | https://doi.org/10.1186/s43067-025-00231-y |
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