Hybrid Global Maximum Power Point Tracking Algorithm for a Thermoelectric Generation System
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jang, Yohan | - |
dc.contributor.author | Lee, Chaeeun | - |
dc.contributor.author | Ji, Sanghyuk | - |
dc.contributor.author | Bae, Sungwoo | - |
dc.date.accessioned | 2022-07-06T10:54:16Z | - |
dc.date.available | 2022-07-06T10:54:16Z | - |
dc.date.created | 2022-03-07 | - |
dc.date.issued | 2021-12 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/140071 | - |
dc.description.abstract | This paper proposes a new hybrid global maximum power point (GMPP) tracking algorithm which is a linear extrapolation-based grey wolf optimization algorithm (LEGWO). The LEGWO combines the advantages of a grey wolf optimization algorithm (GWO) and a linear extrapolation-based maximum power point tracking algorithm. As a result, this algorithm enables fast and accurate tracking of the GMPP. The proposed algorithm is verified by comparison simulation results of a perturbation and observation algorithm and the GWO in MATLAB/Simulink. The results validate that the LEGWO does not converge at the local maximum power point and tracks the exact GMPP. Also, the tracking time of the LEGWO is 53.09% faster than the GWO. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Hybrid Global Maximum Power Point Tracking Algorithm for a Thermoelectric Generation System | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Bae, Sungwoo | - |
dc.identifier.doi | 10.23919/ICEMS52562.2021.9634344 | - |
dc.identifier.scopusid | 2-s2.0-85123958332 | - |
dc.identifier.wosid | 000790083500050 | - |
dc.identifier.bibliographicCitation | ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems, pp.267 - 271 | - |
dc.relation.isPartOf | ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems | - |
dc.citation.title | ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems | - |
dc.citation.startPage | 267 | - |
dc.citation.endPage | 271 | - |
dc.type.rims | ART | - |
dc.type.docType | Proceedings Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | Extrapolation | - |
dc.subject.keywordPlus | Global optimization | - |
dc.subject.keywordPlus | MATLAB | - |
dc.subject.keywordPlus | Tracking (position) | - |
dc.subject.keywordPlus | Gray wolves | - |
dc.subject.keywordPlus | Linear extrapolation | - |
dc.subject.keywordPlus | Maximum power point | - |
dc.subject.keywordPlus | Maximum Power Point Tracking | - |
dc.subject.keywordPlus | Maximum Power Point Tracking algorithms | - |
dc.subject.keywordPlus | Non-uniform temperature condition | - |
dc.subject.keywordPlus | Nonuniform temperature | - |
dc.subject.keywordPlus | Optimization algorithms | - |
dc.subject.keywordPlus | Temperature conditions | - |
dc.subject.keywordPlus | Thermoelectric generation systems | - |
dc.subject.keywordPlus | Maximum power point trackers | - |
dc.subject.keywordAuthor | Maximum power point tracking | - |
dc.subject.keywordAuthor | Non-uniform temperature conditions | - |
dc.subject.keywordAuthor | Thermoelectric generation system | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/9634344 | - |
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