Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan Island
Abstract Combined renewable energy sources (RESs) are emerging as a competitive alternative to conventional energy production facilities due to their sustainability and zero-emission characteristics. However, determining the optimal system size is complicated by two major challenges: the cost of ene...
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2025-01-01
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| Series: | International Journal of Computational Intelligence Systems |
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| Online Access: | https://doi.org/10.1007/s44196-025-00737-3 |
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| author | Hessameddin Talebi Javad Nikoukar Majid Gandomkar |
| author_facet | Hessameddin Talebi Javad Nikoukar Majid Gandomkar |
| author_sort | Hessameddin Talebi |
| collection | DOAJ |
| description | Abstract Combined renewable energy sources (RESs) are emerging as a competitive alternative to conventional energy production facilities due to their sustainability and zero-emission characteristics. However, determining the optimal system size is complicated by two major challenges: the cost of energy (COE) and the intermittent nature of RESs. This study introduces a novel mathematical approach to optimize the sizing of photovoltaic (PV), wind, hydrogen, battery, and fuel cell systems with electrolyzers, specifically tailored for the remote area of Lavan Island. The proposed method aims to deliver electricity without reliance on the traditional electricity distribution grid, while offering a scalable solution applicable to other geographical regions. The primary objective is to achieve cost-effective electricity generation while ensuring a reliable energy supply through the evaluation of system reliability indices. A fuzzy logic system is employed to minimize the costs of a hybrid system incorporating hydroelectric, wind, solar, and battery technologies, while simultaneously calculating two key reliability metrics: the Loss of Power Supply Probability (LPSP) and the Dump Energy Probability (DEP). To optimize the objective function, this study applies three advanced algorithms: the Shuffled Frog Leaping Algorithm (SFLA), the Grasshopper Optimization Algorithm (GOA), and the Honey Badger Algorithm (HBA). These algorithms are used to determine the global optimum, with comparative analyses conducted to highlight the performance of the proposed approach. The results are evaluated based on statistical metrics, including consistency, execution time, convergence speed, and the minimization of the objective function. The findings demonstrate the superiority and the reliability of the proposed method over alternative approaches, paving the way for cost-efficient and sustainable energy solutions in isolated regions. |
| format | Article |
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| institution | Kabale University |
| issn | 1875-6883 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
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| series | International Journal of Computational Intelligence Systems |
| spelling | doaj-art-d003f8ef3f8c4ebb824a41120bf7ce5a2025-02-02T12:41:59ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832025-01-0118112810.1007/s44196-025-00737-3Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan IslandHessameddin Talebi0Javad Nikoukar1Majid Gandomkar2Department of Electrical Engineering, College of Engineering Technology, Saveh Branch, Islamic Azad UniversityDepartment of Electrical Engineering, College of Engineering Technology, Saveh Branch, Islamic Azad UniversityDepartment of Electrical Engineering, College of Engineering Technology, Saveh Branch, Islamic Azad UniversityAbstract Combined renewable energy sources (RESs) are emerging as a competitive alternative to conventional energy production facilities due to their sustainability and zero-emission characteristics. However, determining the optimal system size is complicated by two major challenges: the cost of energy (COE) and the intermittent nature of RESs. This study introduces a novel mathematical approach to optimize the sizing of photovoltaic (PV), wind, hydrogen, battery, and fuel cell systems with electrolyzers, specifically tailored for the remote area of Lavan Island. The proposed method aims to deliver electricity without reliance on the traditional electricity distribution grid, while offering a scalable solution applicable to other geographical regions. The primary objective is to achieve cost-effective electricity generation while ensuring a reliable energy supply through the evaluation of system reliability indices. A fuzzy logic system is employed to minimize the costs of a hybrid system incorporating hydroelectric, wind, solar, and battery technologies, while simultaneously calculating two key reliability metrics: the Loss of Power Supply Probability (LPSP) and the Dump Energy Probability (DEP). To optimize the objective function, this study applies three advanced algorithms: the Shuffled Frog Leaping Algorithm (SFLA), the Grasshopper Optimization Algorithm (GOA), and the Honey Badger Algorithm (HBA). These algorithms are used to determine the global optimum, with comparative analyses conducted to highlight the performance of the proposed approach. The results are evaluated based on statistical metrics, including consistency, execution time, convergence speed, and the minimization of the objective function. The findings demonstrate the superiority and the reliability of the proposed method over alternative approaches, paving the way for cost-efficient and sustainable energy solutions in isolated regions.https://doi.org/10.1007/s44196-025-00737-3Optimal sizingRenewable energy sources (RESs)Fuzzy logic systemShuffled frog leaping algorithm (SFLA)Grasshopper optimization algorithm (GOA)Honey badger algorithm (HBA) |
| spellingShingle | Hessameddin Talebi Javad Nikoukar Majid Gandomkar Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan Island International Journal of Computational Intelligence Systems Optimal sizing Renewable energy sources (RESs) Fuzzy logic system Shuffled frog leaping algorithm (SFLA) Grasshopper optimization algorithm (GOA) Honey badger algorithm (HBA) |
| title | Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan Island |
| title_full | Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan Island |
| title_fullStr | Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan Island |
| title_full_unstemmed | Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan Island |
| title_short | Optimal Sizing and Techno-economic Analysis of Combined Solar Wind Power System, Fuel Cell and Tidal Turbines Using Meta-heuristic Algorithms: A Case Study of Lavan Island |
| title_sort | optimal sizing and techno economic analysis of combined solar wind power system fuel cell and tidal turbines using meta heuristic algorithms a case study of lavan island |
| topic | Optimal sizing Renewable energy sources (RESs) Fuzzy logic system Shuffled frog leaping algorithm (SFLA) Grasshopper optimization algorithm (GOA) Honey badger algorithm (HBA) |
| url | https://doi.org/10.1007/s44196-025-00737-3 |
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