Parameter identification and generality analysis of photovoltaic module dual-diode model based on artificial hummingbird algorithm

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorLi, Zhenen_US
dc.contributor.authorHu, Jiankeen_US
dc.contributor.authorHan, Yifengen_US
dc.contributor.authorLi, Hefengen_US
dc.contributor.authorWang, Junen_US
dc.contributor.authorLund, Peteren_US
dc.contributor.departmentSoutheast University, Nanjingen_US
dc.contributor.departmentPowerChina Huadong Engineeringen_US
dc.contributor.departmentNew Energy Technologiesen_US
dc.contributor.departmentDepartment of Applied Physicsen
dc.date.accessioned2023-12-11T09:29:16Z
dc.date.available2023-12-11T09:29:16Z
dc.date.issued2023-12-01en_US
dc.description.abstractThe aim of this study is to propose a photovoltaic (PV) module simulation model with high accuracy under practical working conditions and strong applicability in the engineering field to meet various PV system simulation needs. Unlike previous model-building methods, this study combines the advantages of analytical and metaheuristic algorithms. First, the applicability of various metaheuristic algorithms is comprehensively compared and the seven parameters of the PV cell under standard test conditions are extracted using the double diode model, which verifies that the artificial hummingbird algorithm has higher accuracy than other algorithms. Then, the seven parameters under different conditions are corrected using the analytical method. In terms of the correction method, the ideal factor correction is added on the basis of previous methods to solve the deviation between simulated data and measured data in the non-linear section. Finally, the root mean squared error between the simulated current data and the measured current data of the proposed model under three different temperatures and irradiance is 0.0697, 0.0570 and 0.0289 A, respectively.en
dc.description.versionPeer revieweden
dc.format.extent1219–1232
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationLi , Z , Hu , J , Han , Y , Li , H , Wang , J & Lund , P 2023 , ' Parameter identification and generality analysis of photovoltaic module dual-diode model based on artificial hummingbird algorithm ' , Clean Energy , vol. 7 , no. 6 , pp. 1219–1232 . https://doi.org/10.1093/ce/zkad066en
dc.identifier.doi10.1093/ce/zkad066en_US
dc.identifier.issn2515-4230
dc.identifier.issn2515-396X
dc.identifier.otherPURE UUID: 0c39f903-e419-4049-bc84-eb846634fc8cen_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/0c39f903-e419-4049-bc84-eb846634fc8cen_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85178349068&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/129168057/SCI_Li_etal_Clean_Energy_2023.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/124768
dc.identifier.urnURN:NBN:fi:aalto-202312117136
dc.language.isoenen
dc.publisherOxford University Press
dc.relation.ispartofseriesClean Energyen
dc.relation.ispartofseriesVolume 7, issue 6en
dc.rightsopenAccessen
dc.titleParameter identification and generality analysis of photovoltaic module dual-diode model based on artificial hummingbird algorithmen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion
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