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IEEE Journal of Photovoltaics
Article . 2011 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Spatial Modeling of Thin-Film Solar Modules Using the Network Simulation Method and SPICE

Authors: Bart E. Pieters;
Abstract
The use of the network simulation method (NSM) for the modeling of thin-film solar modules is discussed. It will be shown that for the accurate modeling of small defects using the NSM, a variable mesh is required to keep the computation time within reasonable limits. A simulation tool for thin-film solar modules is developed that implements the NSM with a variable, adaptive mesh. The results of this model will be compared with electroluminescence experiments on a Cu(In,Ga)Se2 solar module with a defect (shunt). Furthermore, it is demonstrated that the program can handle complex-shaped inhomogeneities such as local variations in solar cell properties, illumination, and contact layer resistance.
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citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).33 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%

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citations
Citations provided by BIP!
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
popularity
Popularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
33
Top 10%
Top 10%
Top 10%