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Modeling of PV generators from different technologies — case study

Authors: Hristina Voynova; Valentin Milenov; Vladimir Lazarov; Zahari Zarkov; Ludmil Stoyanov;

Modeling of PV generators from different technologies — case study

Abstract

The paper deals with the modeling and comparison of the performance of photovoltaic (PV) generators with panels from different technologies. The generators are part of an experimental platform at the Technical University of Sofia and operate in real weather conditions. The modeling of the PV modules is based on the Durisch's model using two approaches. The comparison of the models with measured data shows good agreement. We observe that a limited number of characteristic days can be used for the modeling of the PV panels. The inverter's model is based on the manufacturer data. The comparison with the measured data shows good coincidence. Finally the combination of modules' and inverter models is compared with experimental data and we observe a good level of overlap.

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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).
    11
    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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Found an issue? Give us feedback
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Top 10%