Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Bouaouda, Anas, Sayouti, Yassine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
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
_version_ 1784670233451036672
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
work_keys_str_mv AT bouaoudaanas hybridmetaheuristicalgorithmsforoptimalsizingofhybridrenewableenergysystemareviewofthestateoftheart
AT sayoutiyassine hybridmetaheuristicalgorithmsforoptimalsizingofhybridrenewableenergysystemareviewofthestateoftheart