Multiobjective optimal power flow solutions using nondominated sorting colliding bodies optimization
Abstract In the current work, an innovative nondominated sorting colliding bodies optimization (NSCBO) technique is introduced to tackle multiobjective optimal power flow (MOOPF) challenges within electrical power networks. This method offers a means to generate a diverse array of nondominated solut...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-11-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-77275-z |
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| author | Harish Pulluri Kambhampati Venkata Govardhan Rao Cholleti Sriram B. Srikanth Goud Praveen Kumar Balachandran Sangeetha K |
| author_facet | Harish Pulluri Kambhampati Venkata Govardhan Rao Cholleti Sriram B. Srikanth Goud Praveen Kumar Balachandran Sangeetha K |
| author_sort | Harish Pulluri |
| collection | DOAJ |
| description | Abstract In the current work, an innovative nondominated sorting colliding bodies optimization (NSCBO) technique is introduced to tackle multiobjective optimal power flow (MOOPF) challenges within electrical power networks. This method offers a means to generate a diverse array of nondominated solutions in a single iteration by including the nondominated (ND) sorting process and the concept of crowding distance. Additionally, it utilizes a spread indicator to archive the latest nondominated solutions. In the NSCBO method, the mass of each colliding body is determined by its nondominated rank rather than relying on objective function information. Moreover, a fuzzy decision-making strategy is employed to identify a suitable solution from the set of ND solutions. To showcase the scalability and viability of the NSCBO method, experiments are conducted on IEEE 30-bus, considering both bi- and tri-objective models. Comparative analysis with existing methods from recent literature demonstrates the efficacy of the NSCBO technique in handling constraints and deriving nondominated solutions for MOOPF problems. |
| format | Article |
| id | doaj-art-0a70c2c29a564fee9b3ddea2af463626 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-0a70c2c29a564fee9b3ddea2af4636262024-11-10T12:21:09ZengNature PortfolioScientific Reports2045-23222024-11-0114111310.1038/s41598-024-77275-zMultiobjective optimal power flow solutions using nondominated sorting colliding bodies optimizationHarish Pulluri0Kambhampati Venkata Govardhan Rao1Cholleti Sriram2B. Srikanth Goud3Praveen Kumar Balachandran4Sangeetha K5Department of Electrical and Electronics Engineering, Anurag UniversityDepartment of Electrical and Electronics Engineering, St. Martin’s Engineering College, DhulapallyDepartment of Electrical and Electronics Engineering, Guru Nanak Institute of Technology, IbrahimpatnamDepartment of Electrical and Electronics Engineering, Anurag UniversityDepartment of Electrical and Electronics Engineering, Vardhaman College of EngineeringDepartment of CSE, Kebri Dehar UniversityAbstract In the current work, an innovative nondominated sorting colliding bodies optimization (NSCBO) technique is introduced to tackle multiobjective optimal power flow (MOOPF) challenges within electrical power networks. This method offers a means to generate a diverse array of nondominated solutions in a single iteration by including the nondominated (ND) sorting process and the concept of crowding distance. Additionally, it utilizes a spread indicator to archive the latest nondominated solutions. In the NSCBO method, the mass of each colliding body is determined by its nondominated rank rather than relying on objective function information. Moreover, a fuzzy decision-making strategy is employed to identify a suitable solution from the set of ND solutions. To showcase the scalability and viability of the NSCBO method, experiments are conducted on IEEE 30-bus, considering both bi- and tri-objective models. Comparative analysis with existing methods from recent literature demonstrates the efficacy of the NSCBO technique in handling constraints and deriving nondominated solutions for MOOPF problems.https://doi.org/10.1038/s41598-024-77275-zColliding bodies optimizationHeuristic techniqueObjective optimizationEmission pollutionTotal production cost |
| spellingShingle | Harish Pulluri Kambhampati Venkata Govardhan Rao Cholleti Sriram B. Srikanth Goud Praveen Kumar Balachandran Sangeetha K Multiobjective optimal power flow solutions using nondominated sorting colliding bodies optimization Scientific Reports Colliding bodies optimization Heuristic technique Objective optimization Emission pollution Total production cost |
| title | Multiobjective optimal power flow solutions using nondominated sorting colliding bodies optimization |
| title_full | Multiobjective optimal power flow solutions using nondominated sorting colliding bodies optimization |
| title_fullStr | Multiobjective optimal power flow solutions using nondominated sorting colliding bodies optimization |
| title_full_unstemmed | Multiobjective optimal power flow solutions using nondominated sorting colliding bodies optimization |
| title_short | Multiobjective optimal power flow solutions using nondominated sorting colliding bodies optimization |
| title_sort | multiobjective optimal power flow solutions using nondominated sorting colliding bodies optimization |
| topic | Colliding bodies optimization Heuristic technique Objective optimization Emission pollution Total production cost |
| url | https://doi.org/10.1038/s41598-024-77275-z |
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