A review of hybrid renewable energies optimisation: design, methodologies, and criteria
Over the years, several achievements have been made in power generation and optimising hybrid renewable energy systems (HRES) to achieve nature conservation, achieve energy security, and reduce carbon emissions. However, there are many complexities in Renewable energy (RE) conversion, sizing, design...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | International Journal of Sustainable Energy |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/14786451.2023.2227294 |
| _version_ | 1797680264433893376 |
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| author | Olalekan Kunle Ajiboye Chimere Victor Ochiegbu Eric Antwi Ofosu Samuel Gyamfi |
| author_facet | Olalekan Kunle Ajiboye Chimere Victor Ochiegbu Eric Antwi Ofosu Samuel Gyamfi |
| author_sort | Olalekan Kunle Ajiboye |
| collection | DOAJ |
| description | Over the years, several achievements have been made in power generation and optimising hybrid renewable energy systems (HRES) to achieve nature conservation, achieve energy security, and reduce carbon emissions. However, there are many complexities in Renewable energy (RE) conversion, sizing, design, and implementation, that require optimisation techniques to achieve optimal results in terms of reliability, cost, and environmental protection over time. This paper presents an overview of research trends in Optimization methods in HRES which are classified into modern and conventional methods. These two classifications are further divided into control methods, Artificial intelligence, Iterative and mathematical operations. However, all mentioned techniques have inherent advantages and disadvantages which will be discussed in this survey. In addition, the review paper explored different types of research in computing intelligence (CI), an aspect of Artificial Intelligence (AI) that involves the development of nature-inspired algorithms for optimisation. Finally, general optimisation criteria, system sizing methods used in RES, Mathematical modelling of RES, and gaps for future work to achieve sustainability were also presented. |
| first_indexed | 2024-03-11T23:27:12Z |
| format | Article |
| id | doaj.art-ff831e772ba84c63ad5a35c3c21d2e72 |
| institution | Directory Open Access Journal |
| issn | 1478-6451 1478-646X |
| language | English |
| last_indexed | 2024-03-11T23:27:12Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Sustainable Energy |
| spelling | doaj.art-ff831e772ba84c63ad5a35c3c21d2e722023-09-20T10:45:15ZengTaylor & Francis GroupInternational Journal of Sustainable Energy1478-64511478-646X2023-12-0142164868410.1080/14786451.2023.22272942227294A review of hybrid renewable energies optimisation: design, methodologies, and criteriaOlalekan Kunle Ajiboye0Chimere Victor Ochiegbu1Eric Antwi Ofosu2Samuel Gyamfi3The University of Energy and Natural resourcesThe University of Energy and Natural resourcesThe University of Energy and Natural resourcesThe University of Energy and Natural resourcesOver the years, several achievements have been made in power generation and optimising hybrid renewable energy systems (HRES) to achieve nature conservation, achieve energy security, and reduce carbon emissions. However, there are many complexities in Renewable energy (RE) conversion, sizing, design, and implementation, that require optimisation techniques to achieve optimal results in terms of reliability, cost, and environmental protection over time. This paper presents an overview of research trends in Optimization methods in HRES which are classified into modern and conventional methods. These two classifications are further divided into control methods, Artificial intelligence, Iterative and mathematical operations. However, all mentioned techniques have inherent advantages and disadvantages which will be discussed in this survey. In addition, the review paper explored different types of research in computing intelligence (CI), an aspect of Artificial Intelligence (AI) that involves the development of nature-inspired algorithms for optimisation. Finally, general optimisation criteria, system sizing methods used in RES, Mathematical modelling of RES, and gaps for future work to achieve sustainability were also presented.http://dx.doi.org/10.1080/14786451.2023.2227294optimization techniqueshybrid renewable energy system (hres)optimization criteria |
| spellingShingle | Olalekan Kunle Ajiboye Chimere Victor Ochiegbu Eric Antwi Ofosu Samuel Gyamfi A review of hybrid renewable energies optimisation: design, methodologies, and criteria International Journal of Sustainable Energy optimization techniques hybrid renewable energy system (hres) optimization criteria |
| title | A review of hybrid renewable energies optimisation: design, methodologies, and criteria |
| title_full | A review of hybrid renewable energies optimisation: design, methodologies, and criteria |
| title_fullStr | A review of hybrid renewable energies optimisation: design, methodologies, and criteria |
| title_full_unstemmed | A review of hybrid renewable energies optimisation: design, methodologies, and criteria |
| title_short | A review of hybrid renewable energies optimisation: design, methodologies, and criteria |
| title_sort | review of hybrid renewable energies optimisation design methodologies and criteria |
| topic | optimization techniques hybrid renewable energy system (hres) optimization criteria |
| url | http://dx.doi.org/10.1080/14786451.2023.2227294 |
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