Optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizer
To boost the use of renewable energy sources while maintaining reliability and affordability, Multi-source renewable and sustainable energy systems must be optimally sized. This research introduces a stand-alone metaheuristic algorithm for designing a hybrid sustainable and renewable energy system c...
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Elsevier
2025-09-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025028762 |
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| author | Djamel Eddine Sifou Aissa Kheldoun Ahmed Chaib Hamza Belmadani Hisham Alharbi Saleh S. Alharbi Takele Ferede Agajie Sherif S.M. Ghoneim |
| author_facet | Djamel Eddine Sifou Aissa Kheldoun Ahmed Chaib Hamza Belmadani Hisham Alharbi Saleh S. Alharbi Takele Ferede Agajie Sherif S.M. Ghoneim |
| author_sort | Djamel Eddine Sifou |
| collection | DOAJ |
| description | To boost the use of renewable energy sources while maintaining reliability and affordability, Multi-source renewable and sustainable energy systems must be optimally sized. This research introduces a stand-alone metaheuristic algorithm for designing a hybrid sustainable and renewable energy system combining Wind turbine, PV and battery system. The main goal is to lower the overall present-day system’s cost at the same time considering the indicator of reliability, which is the loss of power supply probability (LPSP), as a constraint. The developed algorithm resulted from enhancing the recent Harris Hawks Optimizer (HHO). The modified version incorporates a vector that saves the best three solutions and opposition learning to enhance the population diversity and assist the algorithm in jumping out of local optima regions. Three scenarios are presented, the first is modeled by PV/Bat the second one is modeled by WT/Bat while the third one consists of PV/WT/Bat. The studied project is located in Sidi Khattab, Relizane province, Algeria. The results demonstrate that the MHHO outperforms a range of well-known algorithms, among which one can cite the original HHO, Krill Optimization Algorithm (KOA), Red Squirrel Algorithm (RSA), Modified Coati Optimization Algorithm (MCOA), and Generalized Oppositional-based Social Spider Algorithm (GOOSE). Compared to the other algorithms, MHHO demonstrated superior performance in all proposed configuration settings. |
| format | Article |
| id | doaj-art-dcfc0a023a2c46208dc2d8013f830fdb |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-dcfc0a023a2c46208dc2d8013f830fdb2025-08-23T04:49:02ZengElsevierResults in Engineering2590-12302025-09-012710681210.1016/j.rineng.2025.106812Optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizerDjamel Eddine Sifou0Aissa Kheldoun1Ahmed Chaib2Hamza Belmadani3Hisham Alharbi4Saleh S. Alharbi5Takele Ferede Agajie6Sherif S.M. Ghoneim7Research Laboratory of Signals & Systems, Institute of Electrical and Electronic Engineering, University M’hamed Bougara, Boumerdes 35000, AlgeriaResearch Laboratory of Signals & Systems, Institute of Electrical and Electronic Engineering, University M’hamed Bougara, Boumerdes 35000, Algeria; Corresponding authors.Laboratory of Applied Automatic (LAA), University M’hamed Bougara, Boumerdes, 35000, AlgeriaSET Laboratory, Blida 1 University, Faculty of Technology, Electrical and control Department, 09000 Blida, AlgeriaDepartment of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi ArabiaDepartment of Electrical Engineering, Al-Baha University, Alaqiq 65779, Saudi ArabiaDepartment of Electrical and Computer Engineering, Faculty of technology, DebreMarkos University, Debre Markos 269, Ethiopia; Corresponding authors.Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi ArabiaTo boost the use of renewable energy sources while maintaining reliability and affordability, Multi-source renewable and sustainable energy systems must be optimally sized. This research introduces a stand-alone metaheuristic algorithm for designing a hybrid sustainable and renewable energy system combining Wind turbine, PV and battery system. The main goal is to lower the overall present-day system’s cost at the same time considering the indicator of reliability, which is the loss of power supply probability (LPSP), as a constraint. The developed algorithm resulted from enhancing the recent Harris Hawks Optimizer (HHO). The modified version incorporates a vector that saves the best three solutions and opposition learning to enhance the population diversity and assist the algorithm in jumping out of local optima regions. Three scenarios are presented, the first is modeled by PV/Bat the second one is modeled by WT/Bat while the third one consists of PV/WT/Bat. The studied project is located in Sidi Khattab, Relizane province, Algeria. The results demonstrate that the MHHO outperforms a range of well-known algorithms, among which one can cite the original HHO, Krill Optimization Algorithm (KOA), Red Squirrel Algorithm (RSA), Modified Coati Optimization Algorithm (MCOA), and Generalized Oppositional-based Social Spider Algorithm (GOOSE). Compared to the other algorithms, MHHO demonstrated superior performance in all proposed configuration settings.http://www.sciencedirect.com/science/article/pii/S2590123025028762Hybrid systemRenewable energyOptimizationModified hhoOpposition learningLPSP |
| spellingShingle | Djamel Eddine Sifou Aissa Kheldoun Ahmed Chaib Hamza Belmadani Hisham Alharbi Saleh S. Alharbi Takele Ferede Agajie Sherif S.M. Ghoneim Optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizer Results in Engineering Hybrid system Renewable energy Optimization Modified hho Opposition learning LPSP |
| title | Optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizer |
| title_full | Optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizer |
| title_fullStr | Optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizer |
| title_full_unstemmed | Optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizer |
| title_short | Optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizer |
| title_sort | optimum sizing of hybrid sustainable and renewable energy systems using a modified harris hawks optimizer |
| topic | Hybrid system Renewable energy Optimization Modified hho Opposition learning LPSP |
| url | http://www.sciencedirect.com/science/article/pii/S2590123025028762 |
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