Publication:

Satellite based fault diagnosis of photovoltaic systems using recurrent neural networks

Date

2022
Journal article
https://doi.org/10.1016/j.apenergy.2021.117874
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dc.contributor.authorVan Gompel, Jonas
dc.contributor.authorSpina, Domenico
dc.contributor.authorDevelder, Chris
dc.contributor.imecauthorVan Gompel, Jonas
dc.contributor.imecauthorSpina, Domenico
dc.contributor.imecauthorDevelder, Chris
dc.contributor.orcidimecVan Gompel, Jonas::0000-0002-4253-5842
dc.contributor.orcidimecSpina, Domenico::0000-0003-2379-5259
dc.contributor.orcidimecDevelder, Chris::0000-0003-2707-4176
dc.contributor.orcidimecVerhoeven, Chantal::0000-0002-4253-5842
dc.date.accessioned2022-04-01T14:12:06Z
dc.date.available2021-11-02T15:56:20Z
dc.date.available2022-04-01T14:12:06Z
dc.date.issued2022
dc.description.wosFundingTextThis 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.
dc.identifier.doi10.1016/j.apenergy.2021.117874
dc.identifier.issn0306-2619
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/37507
dc.publisherELSEVIER SCI LTD
dc.source.beginpage117874
dc.source.issuena
dc.source.journalAPPLIED ENERGY
dc.source.numberofpages9
dc.source.volume305
dc.subject.keywordsVOLTAGE
dc.subject.keywordsFOREST
dc.title

Satellite based fault diagnosis of photovoltaic systems using recurrent neural networks

dc.typeJournal article
dspace.entity.typePublication
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