Locating faults in photovoltaic systems data

Authors Alexander Kogler
Patrick Traxler
Editors W. L. Woon
Z. Aung
O. Kramer
S. Madnick
Title Locating faults in photovoltaic systems data
Booktitle Data Analytics for Renewable Energy Integration - Proc. 4th ECML PKDD Workshop, DARE 2016
Type in proceedings
Series Lecture Notes in Artificial Intelligence
Volume 10097
ISBN 978-3-319-50946-4
DOI 10.1007/978-3-319-50947-1_1
Month January
Year 2017
Pages 1-9
SCCH ID# 16064

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.