Parameter identification and generality analysis of photovoltaic module dual-diode model based on artificial hummingbird algorithm
dc.contributor | Aalto-yliopisto | fi |
dc.contributor | Aalto University | en |
dc.contributor.author | Li, Zhen | en_US |
dc.contributor.author | Hu, Jianke | en_US |
dc.contributor.author | Han, Yifeng | en_US |
dc.contributor.author | Li, Hefeng | en_US |
dc.contributor.author | Wang, Jun | en_US |
dc.contributor.author | Lund, Peter | en_US |
dc.contributor.department | Department of Applied Physics | en |
dc.contributor.groupauthor | New Energy Technologies | en |
dc.contributor.organization | Southeast University, Nanjing | en_US |
dc.contributor.organization | Power China Huadong Engineering Corporation Limited | en_US |
dc.date.accessioned | 2023-12-11T09:29:16Z | |
dc.date.available | 2023-12-11T09:29:16Z | |
dc.date.issued | 2023-12-01 | en_US |
dc.description.abstract | The 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.version | Peer reviewed | en |
dc.format.extent | 1219–1232 | |
dc.format.mimetype | application/pdf | en_US |
dc.identifier.citation | Li, 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/zkad066 | en |
dc.identifier.doi | 10.1093/ce/zkad066 | en_US |
dc.identifier.issn | 2515-4230 | |
dc.identifier.issn | 2515-396X | |
dc.identifier.other | PURE UUID: 0c39f903-e419-4049-bc84-eb846634fc8c | en_US |
dc.identifier.other | PURE ITEMURL: https://research.aalto.fi/en/publications/0c39f903-e419-4049-bc84-eb846634fc8c | en_US |
dc.identifier.other | PURE LINK: http://www.scopus.com/inward/record.url?scp=85178349068&partnerID=8YFLogxK | en_US |
dc.identifier.other | PURE FILEURL: https://research.aalto.fi/files/129168057/SCI_Li_etal_Clean_Energy_2023.pdf | en_US |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/124768 | |
dc.identifier.urn | URN:NBN:fi:aalto-202312117136 | |
dc.language.iso | en | en |
dc.publisher | Oxford University Press | |
dc.relation.ispartofseries | Clean Energy | en |
dc.relation.ispartofseries | Volume 7, issue 6 | en |
dc.rights | openAccess | en |
dc.title | Parameter identification and generality analysis of photovoltaic module dual-diode model based on artificial hummingbird algorithm | en |
dc.type | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä | fi |
dc.type.version | publishedVersion |