Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Bart E. Pieters"'
Autor:
Stephanie Reidt, Bart E. Pieters
Publikováno v:
AIP Advances, Vol 9, Iss 2, Pp 025102-025102-14 (2019)
An analytical model for illuminated p-i-n structures such as Solar Cells and related devices has been developed. Starting from the semiconductor equations in their most general form, and introducing assumptions for the recombination and electrical fi
Externí odkaz:
https://doaj.org/article/5a666321279c44e0801eeb7b7dbe39ed
Publikováno v:
Solar RRL. 7
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bbb4975c9eeb990bee66e091305ad970
https://doi.org/10.1002/solr.202200593
https://doi.org/10.1002/solr.202200593
Autor:
Kaining Ding, Lars Korte, Manuel Brunner, S. Wöhe, Hilke Fischer, Bernd Stannowski, Hermann Nonnenmacher, Rolf Brendel, Andreas Lambertz, Henning Schulte-Huxel, Bart E. Pieters, Andreas Schiessl, Andrei Salavei, Marc Köntges, Gustav Wetzel, Susanne Blankemeyer, Jan Krügener, Robby Peibst, Felix Haase, Reinhard Wecker, Stefan Janke, Heiko Mehlich, Christina Hollemann
Publikováno v:
Solar RRL 6(5), 2100516 (2022). doi:10.1002/solr.202100516
The setting up of a practical electrically driven light commercial demonstration vehicle with integrated photovoltaics PV is reported. The demonstrator vehicle is equipped with 15 modules based on the crystalline Si amorphous Si heterojunction techno
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::611ef61384f7c92a60b35ac0574f9db6
https://hdl.handle.net/2128/32700
https://hdl.handle.net/2128/32700
Autor:
Ansgar Steland, Bart E. Pieters
Publikováno v:
Artificial Intelligence, Big Data and Data Science in Statistics ISBN: 9783031071546
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69c443a883a763b6d3212138883e30db
https://doi.org/10.1007/978-3-031-07155-3_1
https://doi.org/10.1007/978-3-031-07155-3_1
Autor:
Evgenii Sovetkin, Bart E. Pieters
Publikováno v:
Artificial Intelligence, Big Data and Data Science in Statistics ISBN: 9783031071546
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13ceaa51de29f098c2bca2f9c3abd3b6
https://doi.org/10.1007/978-3-031-07155-3_14
https://doi.org/10.1007/978-3-031-07155-3_14
Publikováno v:
EPJ Photovoltaics. 14:3
In this work, we present a method to study thermal runaway effects in thin-film solar cells. Partial shading of solar cells often leads to permanent damage to shaded cells and degrades the performance of solar modules over time. Under partial shading
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea1baa3b0d9c7d70620115351deb4ce9
https://doi.org/10.1051/epjpv/2022030
https://doi.org/10.1051/epjpv/2022030
Autor:
T. S. Vaas, Bart E. Pieters
Publikováno v:
2021 IEEE 48th Photovoltaic Specialists Conference (PVSC).
Detailed monitoring the reliability of photovoltaic (PV) modules often relies on analyzing the standard solar cell parameters over time. However, with current-voltage (I-V) sweeps available to determine the solar cell parameters, much information is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c3ef1b3044f35d551fc70ade8fe7242
https://doi.org/10.1109/pvsc43889.2021.9519102
https://doi.org/10.1109/pvsc43889.2021.9519102
Autor:
Suheir Nofal, Bart E. Pieters
Publikováno v:
2021 IEEE 48th Photovoltaic Specialists Conference (PVSC).
This paper introduces a novel non-destructive characterization method to investigate reverse bias hot-spot formation in Cu(In,Ga)Se2 (CIGS) solar cell technologies based on lock-in thermography (LIT). CIGS solar cells technology is an innovative thin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fdd3c1f6f824f26b5a7cf7065e2a0b6
https://doi.org/10.1109/pvsc43889.2021.9518804
https://doi.org/10.1109/pvsc43889.2021.9518804
Publikováno v:
Physical Review Applied. 14
This study investigates the phenomenon of $r\phantom{\rule{0}{0ex}}e\phantom{\rule{0}{0ex}}s\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}u\phantom{\rule{0}{0ex}}a\phantom{\rule{0}{0ex}}l$ $l\phantom{\rule{0}{0ex}}u\phantom{\
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::689e604ae749d74998a65f9ccb2eb109
https://doi.org/10.1103/physrevapplied.14.014046
https://doi.org/10.1103/physrevapplied.14.014046
Publikováno v:
IEEE journal of photovoltaics 11(2), 444-452 (2021). doi:10.1109/JPHOTOV.2020.3041240
We consider a series of image segmentation methods based on the deep neural networks in order to perform semantic segmentation of electroluminescence (EL) images of thin-film modules. We utilize the encoder-decoder deep neural network architecture. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0b2e752246f4719c86420a8dbb673fa