Design of Hybrid Renewable Energy Systems: Integrating Multi‐Objective Optimization Into a Multi‐Criteria Decision‐Making Framework
ABSTRACT Research into hybrid renewable energy systems (HRESs) fulfills the need for the development of sustainable and environmentally friendly energy systems to supply house‐holds. The design of HRESs is a challenging endeavor requiring the optimization of multiple objectives considered over multi...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Engineering Reports |
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| Online Access: | https://doi.org/10.1002/eng2.13074 |
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| author | Tebello Ntsiki Don Mathaba Khaled Abo‐Al‐Ez |
| author_facet | Tebello Ntsiki Don Mathaba Khaled Abo‐Al‐Ez |
| author_sort | Tebello Ntsiki Don Mathaba |
| collection | DOAJ |
| description | ABSTRACT Research into hybrid renewable energy systems (HRESs) fulfills the need for the development of sustainable and environmentally friendly energy systems to supply house‐holds. The design of HRESs is a challenging endeavor requiring the optimization of multiple objectives considered over multiple criteria. This paper presents a new multi‐criteria decision‐making framework (MCDM) to automate the design. The proposed framework initially uses a metaheuristic multi‐objective (MO) optimization algorithm to generate optimal candidate configurations and then objectively evaluates candidates to select the best configuration. A combination of the MO particle swarm optimization and a newly developed MO leaders‐and‐follower algorithms (MO‐LaF/PSO) is used to generate optimal configurations based on minimal levelized cost of energy (LCOE), renewable energy (RE) power abandonment, and CO2 emissions, while maintaining an acceptable level of reliability. The evaluation phase applies the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) ranking method that uses objective criteria weights calculated using MEREC (MEthod based on the Removal Effects of Criteria). This method is applied to a case‐study of an off‐grid Wind/PV/Diesel/Battery HRES. The results reveal that this newly proposed framework generates a unique top‐ranking configuration with an LCOE of 0.199 $/kWh, 0% wastage of RE, and 982 tons of CO2. |
| format | Article |
| id | doaj-art-71bef4e24a824903bff9ddc0a9be86e4 |
| institution | Kabale University |
| issn | 2577-8196 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Engineering Reports |
| spelling | doaj-art-71bef4e24a824903bff9ddc0a9be86e42025-01-31T00:22:49ZengWileyEngineering Reports2577-81962025-01-0171n/an/a10.1002/eng2.13074Design of Hybrid Renewable Energy Systems: Integrating Multi‐Objective Optimization Into a Multi‐Criteria Decision‐Making FrameworkTebello Ntsiki Don Mathaba0Khaled Abo‐Al‐Ez1Postgraduate School of Engineering Management University of Johannesburg Johannesburg South AfricaPostgraduate School of Engineering Management University of Johannesburg Johannesburg South AfricaABSTRACT Research into hybrid renewable energy systems (HRESs) fulfills the need for the development of sustainable and environmentally friendly energy systems to supply house‐holds. The design of HRESs is a challenging endeavor requiring the optimization of multiple objectives considered over multiple criteria. This paper presents a new multi‐criteria decision‐making framework (MCDM) to automate the design. The proposed framework initially uses a metaheuristic multi‐objective (MO) optimization algorithm to generate optimal candidate configurations and then objectively evaluates candidates to select the best configuration. A combination of the MO particle swarm optimization and a newly developed MO leaders‐and‐follower algorithms (MO‐LaF/PSO) is used to generate optimal configurations based on minimal levelized cost of energy (LCOE), renewable energy (RE) power abandonment, and CO2 emissions, while maintaining an acceptable level of reliability. The evaluation phase applies the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) ranking method that uses objective criteria weights calculated using MEREC (MEthod based on the Removal Effects of Criteria). This method is applied to a case‐study of an off‐grid Wind/PV/Diesel/Battery HRES. The results reveal that this newly proposed framework generates a unique top‐ranking configuration with an LCOE of 0.199 $/kWh, 0% wastage of RE, and 982 tons of CO2.https://doi.org/10.1002/eng2.13074batteryleaders and followers algorithmmulti‐objective optimizationparticle swarm optimizationrenewable energy |
| spellingShingle | Tebello Ntsiki Don Mathaba Khaled Abo‐Al‐Ez Design of Hybrid Renewable Energy Systems: Integrating Multi‐Objective Optimization Into a Multi‐Criteria Decision‐Making Framework Engineering Reports battery leaders and followers algorithm multi‐objective optimization particle swarm optimization renewable energy |
| title | Design of Hybrid Renewable Energy Systems: Integrating Multi‐Objective Optimization Into a Multi‐Criteria Decision‐Making Framework |
| title_full | Design of Hybrid Renewable Energy Systems: Integrating Multi‐Objective Optimization Into a Multi‐Criteria Decision‐Making Framework |
| title_fullStr | Design of Hybrid Renewable Energy Systems: Integrating Multi‐Objective Optimization Into a Multi‐Criteria Decision‐Making Framework |
| title_full_unstemmed | Design of Hybrid Renewable Energy Systems: Integrating Multi‐Objective Optimization Into a Multi‐Criteria Decision‐Making Framework |
| title_short | Design of Hybrid Renewable Energy Systems: Integrating Multi‐Objective Optimization Into a Multi‐Criteria Decision‐Making Framework |
| title_sort | design of hybrid renewable energy systems integrating multi objective optimization into a multi criteria decision making framework |
| topic | battery leaders and followers algorithm multi‐objective optimization particle swarm optimization renewable energy |
| url | https://doi.org/10.1002/eng2.13074 |
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