Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance
Abstract The strategic integration of distributed generation (DG) units into distribution power networks (DPNs) is pivotal for augmenting system efficiency and stability. This study introduces an advanced metaheuristic optimization framework leveraging the Jellyfish Search Algorithm (JSA) for the op...
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Nature Portfolio
2025-07-01
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| Online Access: | https://doi.org/10.1038/s41598-025-08227-4 |
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| author | P Rajakumar P. M. Balasubramaniam E. Parimalasundar K. Suresh P. Aravind |
| author_facet | P Rajakumar P. M. Balasubramaniam E. Parimalasundar K. Suresh P. Aravind |
| author_sort | P Rajakumar |
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| description | Abstract The strategic integration of distributed generation (DG) units into distribution power networks (DPNs) is pivotal for augmenting system efficiency and stability. This study introduces an advanced metaheuristic optimization framework leveraging the Jellyfish Search Algorithm (JSA) for the optimal placement and sizing of solar photovoltaic (PV) DG units. The formulated multi-objective function incorporates real power loss (RPL) minimization, voltage deviation index (VDI) reduction, and voltage stability index (VSI) enhancement, employing a weighted sum approach (WSA) to ensure computational rigor. The efficacy of the proposed methodology is rigorously validated on the IEEE 33-bus radial DPN under single and multiple PV system deployment scenarios. For single PV system optimized inclusion, RPL of the DPN is cut down from 210.98 kW to 102.89 kW, total VDI is reduced from 1.8047 p.u to 0.5331 p.u, and minimum VSI is increased from 0.6671 to 0.7559. For two PV DG units inclusion, RPL is reduced to 82.99 kW, total VDI is reduced to 0.6518 p.u with a least VSI improved to 0.8848. However, better result is obtained with three units of DG placement with RPL reduced to 69.59 kW, total VDI decreased to 0.3293 p.u with a least VSI of the test system increased to 0.8916. Comparative analyses against state-of-the-art metaheuristic algorithms underscore the superior convergence efficiency and optimality of JSA in addressing nonlinearity and high-dimensionality constraints. Empirical results substantiate substantial RPL reduction, bus voltage enhancement, and system stability reinforcement, establishing JSA as an avant-garde paradigm in DG optimization. |
| format | Article |
| id | doaj-art-b8cc02f560cc4e0aaf9541f972513f31 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-b8cc02f560cc4e0aaf9541f972513f312025-08-20T04:01:41ZengNature PortfolioScientific Reports2045-23222025-07-0115112710.1038/s41598-025-08227-4Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performanceP Rajakumar0P. M. Balasubramaniam1E. Parimalasundar2K. Suresh3P. Aravind4Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyDepartment of ECE, Hindusthan Institute of TechnologyMohan Babu UniversityChrist (Deemed to be University)Mattu UniversityAbstract The strategic integration of distributed generation (DG) units into distribution power networks (DPNs) is pivotal for augmenting system efficiency and stability. This study introduces an advanced metaheuristic optimization framework leveraging the Jellyfish Search Algorithm (JSA) for the optimal placement and sizing of solar photovoltaic (PV) DG units. The formulated multi-objective function incorporates real power loss (RPL) minimization, voltage deviation index (VDI) reduction, and voltage stability index (VSI) enhancement, employing a weighted sum approach (WSA) to ensure computational rigor. The efficacy of the proposed methodology is rigorously validated on the IEEE 33-bus radial DPN under single and multiple PV system deployment scenarios. For single PV system optimized inclusion, RPL of the DPN is cut down from 210.98 kW to 102.89 kW, total VDI is reduced from 1.8047 p.u to 0.5331 p.u, and minimum VSI is increased from 0.6671 to 0.7559. For two PV DG units inclusion, RPL is reduced to 82.99 kW, total VDI is reduced to 0.6518 p.u with a least VSI improved to 0.8848. However, better result is obtained with three units of DG placement with RPL reduced to 69.59 kW, total VDI decreased to 0.3293 p.u with a least VSI of the test system increased to 0.8916. Comparative analyses against state-of-the-art metaheuristic algorithms underscore the superior convergence efficiency and optimality of JSA in addressing nonlinearity and high-dimensionality constraints. Empirical results substantiate substantial RPL reduction, bus voltage enhancement, and system stability reinforcement, establishing JSA as an avant-garde paradigm in DG optimization.https://doi.org/10.1038/s41598-025-08227-4Metaheuristic optimizationJellyfish search algorithmDistributed generationVoltage deviationVoltage stabilityPhotovoltaic |
| spellingShingle | P Rajakumar P. M. Balasubramaniam E. Parimalasundar K. Suresh P. Aravind Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance Scientific Reports Metaheuristic optimization Jellyfish search algorithm Distributed generation Voltage deviation Voltage stability Photovoltaic |
| title | Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance |
| title_full | Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance |
| title_fullStr | Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance |
| title_full_unstemmed | Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance |
| title_short | Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance |
| title_sort | optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for enhanced power system performance |
| topic | Metaheuristic optimization Jellyfish search algorithm Distributed generation Voltage deviation Voltage stability Photovoltaic |
| url | https://doi.org/10.1038/s41598-025-08227-4 |
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