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Anne Gerd Imenes
Researcher at University of Agder
Publications - 34
Citations - 818
Anne Gerd Imenes is an academic researcher from University of Agder. The author has contributed to research in topics: Photovoltaic system & Zero-energy building. The author has an hindex of 10, co-authored 32 publications receiving 686 citations. Previous affiliations of Anne Gerd Imenes include University of Sydney.
Papers
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Proceedings ArticleDOI
Temperature profiles of field-aged multicrystalline silicon photovoltaic modules affected by microcracks
TL;DR: In this article, the temperature sensitivities of field-aged multicrystalline silicon PV modules affected by microcracks are investigated, and it is found that the temperature coefficient of efficiency of all modules has increased more than 10 times over the 20 years period, mainly due to a degradation in the temperature coefficients of fill factor.
Ray Tracing and Flux Mapping as a Design and Research Tool at the National Solar Energy Centre
Anne Gerd Imenes,Wes Stein,Jim Hinkley,Regano Benito,R Bolling,Philipp Schramek,Steffen Ulmer +6 more
TL;DR: In this article, the authors discuss simulation and optimisation efforts associated with optical aspects of the solar tower system, and show by example how these efforts have been used as a design and research tool at the NSEC.
Proceedings ArticleDOI
Performance of zero energy homes in smart village skarpnes
TL;DR: Investigating how the introduction of low-energy buildings equipped with PV systems is expected to change the power flow to and from the grid will require new models for efficient operation and investment in the future electric distribution grid.
Patent
A receiver for radiation
TL;DR: In this paper, a method of fabricating a receiver for radiation is presented, which comprises the step of determining a distribution of the radiation from at least one radiation concentrator that in use illuminates a receiving surface of the receiver.
Proceedings ArticleDOI
A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites
Anne Gerd Imenes,Nadia Saad Noori,Ole Andreas Nesvag Uthaug,Robert Kroni,Filippo Bianchi,Nabil Belbachir +5 more
TL;DR: In this paper, the authors explore and evaluate the use of computer vision and deep learning methods for automating the analysis of fault detection and classification in large scale photovoltaic module installations.