Abstract
Faults of photovoltaic systems often result in an energy drop and therefore decrease the efficiency of the system. Detecting and analyzing faults is thus an important problem in the analysis of photovoltaic systems data. We consider the problem of estimating the starting time and end time of a fault, i.e. we want to locate the fault in time series data. We assume to know the power output, plane-of-array irradiance and optionally the module temperature. We demonstrate how to use our fault location algorithm to classify shading events. We present results on real data with simulated and real faults.
The research reported in this paper has been supported by the Austrian Ministry for Transport, Innovation and Technology, the Federal Ministry of Science, Research and Economy, and the Province of Upper Austria in the frame of the COMET center SCCH.
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Kogler, A., Traxler, P. (2017). Locating Faults in Photovoltaic Systems Data. In: Woon, W., Aung, Z., Kramer, O., Madnick, S. (eds) Data Analytics for Renewable Energy Integration. DARE 2016. Lecture Notes in Computer Science(), vol 10097. Springer, Cham. https://doi.org/10.1007/978-3-319-50947-1_1
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DOI: https://doi.org/10.1007/978-3-319-50947-1_1
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