A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations
Abstract The supply-demand-based optimization (SDO) is among the recent stochastic approaches that have proven its capability in solving challenging engineering tasks. Owing to the non-linearity and complexity of the real-world IEEE optimal power flow (OPF) in modern power system issues and like the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-41608-1 |
| _version_ | 1797452681388752896 |
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| author | Fatima Daqaq Mohamed H. Hassan Salah Kamel Abdelazim G. Hussien |
| author_facet | Fatima Daqaq Mohamed H. Hassan Salah Kamel Abdelazim G. Hussien |
| author_sort | Fatima Daqaq |
| collection | DOAJ |
| description | Abstract The supply-demand-based optimization (SDO) is among the recent stochastic approaches that have proven its capability in solving challenging engineering tasks. Owing to the non-linearity and complexity of the real-world IEEE optimal power flow (OPF) in modern power system issues and like the existing algorithms, the SDO optimizer necessitates some enhancement to satisfy the required OPF characteristics integrating hybrid wind and solar powers. Thus, a SDO variant namely leader supply-demand-based optimization (LSDO) is proposed in this research. The LSDO is suggested to improve the exploration based on the simultaneous crossover and mutation mechanisms and thereby reduce the probability of trapping in local optima. The LSDO effectiveness has been first tested on 23 benchmark functions and has been assessed through a comparison with well-regarded state-of-the-art competitors. Afterward, Three well-known constrained IEEE 30, 57, and 118-bus test systems incorporating both wind and solar power sources were investigated in order to authenticate the performance of the LSDO considering a constraint handling technique called superiority of feasible solutions (SF). The statistical outcomes reveal that the LSDO offers promising competitive results not only for its first version but also for the other competitors. |
| first_indexed | 2024-03-09T15:12:10Z |
| format | Article |
| id | doaj.art-d581a225e00644869af771ea50571a27 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:12:10Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-d581a225e00644869af771ea50571a272023-11-26T13:19:51ZengNature PortfolioScientific Reports2045-23222023-09-0113113510.1038/s41598-023-41608-1A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generationsFatima Daqaq0Mohamed H. Hassan1Salah Kamel2Abdelazim G. Hussien3Laboratory of Study and Research for Applied Mathematics, Mohammadia School of Engineers, Mohammed V University in RabatMinistry of Electricity and Renewable EnergyDepartment of Electrical Engineering, Faculty of Engineering, Aswan UniversityDepartment of Computer and Information Science, Linköping UniversityAbstract The supply-demand-based optimization (SDO) is among the recent stochastic approaches that have proven its capability in solving challenging engineering tasks. Owing to the non-linearity and complexity of the real-world IEEE optimal power flow (OPF) in modern power system issues and like the existing algorithms, the SDO optimizer necessitates some enhancement to satisfy the required OPF characteristics integrating hybrid wind and solar powers. Thus, a SDO variant namely leader supply-demand-based optimization (LSDO) is proposed in this research. The LSDO is suggested to improve the exploration based on the simultaneous crossover and mutation mechanisms and thereby reduce the probability of trapping in local optima. The LSDO effectiveness has been first tested on 23 benchmark functions and has been assessed through a comparison with well-regarded state-of-the-art competitors. Afterward, Three well-known constrained IEEE 30, 57, and 118-bus test systems incorporating both wind and solar power sources were investigated in order to authenticate the performance of the LSDO considering a constraint handling technique called superiority of feasible solutions (SF). The statistical outcomes reveal that the LSDO offers promising competitive results not only for its first version but also for the other competitors.https://doi.org/10.1038/s41598-023-41608-1 |
| spellingShingle | Fatima Daqaq Mohamed H. Hassan Salah Kamel Abdelazim G. Hussien A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations Scientific Reports |
| title | A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations |
| title_full | A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations |
| title_fullStr | A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations |
| title_full_unstemmed | A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations |
| title_short | A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations |
| title_sort | leader supply demand based optimization for large scale optimal power flow problem considering renewable energy generations |
| url | https://doi.org/10.1038/s41598-023-41608-1 |
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