A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems
One of the most important issues that can significantly affect the electric power network’s ability to operate sustainably is the optimal power flow (OPF) problem. It involves reaching the most efficient operating conditions for the electrical networks while maintaining reliability and systems const...
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MDPI AG
2024-12-01
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| Series: | Applied System Innovation |
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| Online Access: | https://www.mdpi.com/2571-5577/7/6/122 |
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| author | Mohamed H. ElMessmary Hatem Y. Diab Mahmoud Abdelsalam Mona F. Moussa |
| author_facet | Mohamed H. ElMessmary Hatem Y. Diab Mahmoud Abdelsalam Mona F. Moussa |
| author_sort | Mohamed H. ElMessmary |
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| description | One of the most important issues that can significantly affect the electric power network’s ability to operate sustainably is the optimal power flow (OPF) problem. It involves reaching the most efficient operating conditions for the electrical networks while maintaining reliability and systems constraints. Solving the OPF problem in transmission networks lowers three critical expenses: operation costs, transmission losses, and voltage drops. The OPF is characterized by the nonlinearity and nonconvexity behavior due to the power flow equations, which define the relationship between power generation, load demand, and network component physical constraints. The solution space for OPF is massive and multimodal, making optimization a challenging concern that calls for advanced mathematics and computational methods. This paper introduces an innovative metaheuristic algorithm, the Egyptian Stray Dog Optimization (ESDO), inspired by the behavior of Egyptian stray dogs and used for solving both single and multi-objective optimal power flow problems concerning the transmission networks. The proposed technique is compared with the particle swarm optimization (PSO), multi-verse optimization (MVO), grasshopper optimization (GOA), and Harris hawk optimization (HHO) and hippopotamus optimization (HO) algorithms through MATLAB simulations by applying them to the IEEE 30-bus system under various operational circumstances. The results obtained indicate that, in comparison to other used algorithms, the suggested technique gives a significantly enhanced performance in solving the OPF problem. |
| format | Article |
| id | doaj-art-9300ebe919c44569b4696d1c70938f8f |
| institution | Kabale University |
| issn | 2571-5577 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Applied System Innovation |
| spelling | doaj-art-9300ebe919c44569b4696d1c70938f8f2024-12-27T14:09:35ZengMDPI AGApplied System Innovation2571-55772024-12-017612210.3390/asi7060122A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow ProblemsMohamed H. ElMessmary0Hatem Y. Diab1Mahmoud Abdelsalam2Mona F. Moussa3Department of Electrical Energy Engineering, Collage of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Smart Village Campus, Giza 12577, EgyptDepartment of Electrical Energy Engineering, Collage of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Smart Village Campus, Giza 12577, EgyptDepartment of Electrical Energy Engineering, Collage of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Smart Village Campus, Giza 12577, EgyptDepartment of Electrical Energy Engineering, Collage of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Smart Village Campus, Giza 12577, EgyptOne of the most important issues that can significantly affect the electric power network’s ability to operate sustainably is the optimal power flow (OPF) problem. It involves reaching the most efficient operating conditions for the electrical networks while maintaining reliability and systems constraints. Solving the OPF problem in transmission networks lowers three critical expenses: operation costs, transmission losses, and voltage drops. The OPF is characterized by the nonlinearity and nonconvexity behavior due to the power flow equations, which define the relationship between power generation, load demand, and network component physical constraints. The solution space for OPF is massive and multimodal, making optimization a challenging concern that calls for advanced mathematics and computational methods. This paper introduces an innovative metaheuristic algorithm, the Egyptian Stray Dog Optimization (ESDO), inspired by the behavior of Egyptian stray dogs and used for solving both single and multi-objective optimal power flow problems concerning the transmission networks. The proposed technique is compared with the particle swarm optimization (PSO), multi-verse optimization (MVO), grasshopper optimization (GOA), and Harris hawk optimization (HHO) and hippopotamus optimization (HO) algorithms through MATLAB simulations by applying them to the IEEE 30-bus system under various operational circumstances. The results obtained indicate that, in comparison to other used algorithms, the suggested technique gives a significantly enhanced performance in solving the OPF problem.https://www.mdpi.com/2571-5577/7/6/122optimal power flowtransmission networksmetaheuristic algorithmIEEE 30-bus systemMATLAB simulationssingle and multi-objective function |
| spellingShingle | Mohamed H. ElMessmary Hatem Y. Diab Mahmoud Abdelsalam Mona F. Moussa A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems Applied System Innovation optimal power flow transmission networks metaheuristic algorithm IEEE 30-bus system MATLAB simulations single and multi-objective function |
| title | A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems |
| title_full | A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems |
| title_fullStr | A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems |
| title_full_unstemmed | A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems |
| title_short | A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems |
| title_sort | novel optimization algorithm inspired by egyptian stray dogs for solving multi objective optimal power flow problems |
| topic | optimal power flow transmission networks metaheuristic algorithm IEEE 30-bus system MATLAB simulations single and multi-objective function |
| url | https://www.mdpi.com/2571-5577/7/6/122 |
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