dc.contributor.author | Van Gompel, Jonas | |
dc.contributor.author | Spina, Domenico | |
dc.contributor.author | Develder, Chris | |
dc.date.accessioned | 2022-04-01T14:12:06Z | |
dc.date.available | 2021-11-02T15:56:20Z | |
dc.date.available | 2022-04-01T14:12:06Z | |
dc.date.issued | 2022 | |
dc.identifier.issn | 0306-2619 | |
dc.identifier.other | WOS:000702914500001 | |
dc.identifier.uri | https://imec-publications.be/handle/20.500.12860/37507.2 | |
dc.source | WOS | |
dc.title | Satellite based fault diagnosis of photovoltaic systems using recurrent neural networks | |
dc.type | Journal article | |
dc.contributor.imecauthor | Van Gompel, Jonas | |
dc.contributor.imecauthor | Spina, Domenico | |
dc.contributor.imecauthor | Develder, Chris | |
dc.contributor.orcidimec | Van Gompel, Jonas::0000-0002-4253-5842 | |
dc.contributor.orcidimec | Spina, Domenico::0000-0003-2379-5259 | |
dc.contributor.orcidimec | Develder, Chris::0000-0003-2707-4176 | |
dc.contributor.orcidimec | Verhoeven, Chantal::0000-0002-4253-5842 | |
dc.identifier.doi | 10.1016/j.apenergy.2021.117874 | |
dc.source.numberofpages | 9 | |
dc.source.peerreview | yes | |
dc.source.beginpage | 117874 | |
dc.source.journal | APPLIED ENERGY | |
dc.source.issue | na | |
dc.source.volume | 305 | |
imec.availability | Published - open access | |
dc.description.wosFundingText | This work was supported by the DAPPER project, which is financed by Flux50 and Flanders Innovation & Entrepreneurship, Belgium (project number HBC.2020.2144). We would like to thank Arnaud Schils for facilitating the PV simulations. | |