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Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art
The hybrid renewable energy system (HRES) has been presented as the most studied solution for improving the sustainability of energy production infrastructures in isolated areas. With the rapid growth of HRES markets, various issues and aspects must be taken into consideration when the major working...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8926421/ https://www.ncbi.nlm.nih.gov/pubmed/35313649 http://dx.doi.org/10.1007/s11831-022-09730-x |
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author | Bouaouda, Anas Sayouti, Yassine |
author_facet | Bouaouda, Anas Sayouti, Yassine |
author_sort | Bouaouda, Anas |
collection | PubMed |
description | The hybrid renewable energy system (HRES) has been presented as the most studied solution for improving the sustainability of energy production infrastructures in isolated areas. With the rapid growth of HRES markets, various issues and aspects must be taken into consideration when the major working about the hybridization of renewable energy sources, consequently optimization problem solving for this system is a requirement. Therefore, this paper presents a state-of-the-art review of hybrid meta-heuristic algorithms applied for the optimal size of HRES. The relevant literature source and their distribution are presented firstly. We then review the literature from two viewpoints, including existing applied hybrid meta-heuristic algorithms for single-objective and for multi-objective design. Finally, some promising paths ranging from improving algorithms to technical applications are outlined to encourage researchers to conduct research in related fields. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11831-022-09730-x. |
format | Online Article Text |
id | pubmed-8926421 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-89264212022-03-17 Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art Bouaouda, Anas Sayouti, Yassine Arch Comput Methods Eng Review Article The hybrid renewable energy system (HRES) has been presented as the most studied solution for improving the sustainability of energy production infrastructures in isolated areas. With the rapid growth of HRES markets, various issues and aspects must be taken into consideration when the major working about the hybridization of renewable energy sources, consequently optimization problem solving for this system is a requirement. Therefore, this paper presents a state-of-the-art review of hybrid meta-heuristic algorithms applied for the optimal size of HRES. The relevant literature source and their distribution are presented firstly. We then review the literature from two viewpoints, including existing applied hybrid meta-heuristic algorithms for single-objective and for multi-objective design. Finally, some promising paths ranging from improving algorithms to technical applications are outlined to encourage researchers to conduct research in related fields. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11831-022-09730-x. Springer Netherlands 2022-03-16 2022 /pmc/articles/PMC8926421/ /pubmed/35313649 http://dx.doi.org/10.1007/s11831-022-09730-x Text en © The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE) 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Article Bouaouda, Anas Sayouti, Yassine Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art |
title | Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art |
title_full | Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art |
title_fullStr | Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art |
title_full_unstemmed | Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art |
title_short | Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art |
title_sort | hybrid meta-heuristic algorithms for optimal sizing of hybrid renewable energy system: a review of the state-of-the-art |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8926421/ https://www.ncbi.nlm.nih.gov/pubmed/35313649 http://dx.doi.org/10.1007/s11831-022-09730-x |
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