Model-based fault detection algorithm for photovoltaic system monitoring

Fouzi Harrou, Ying Sun, Ahmed Saidi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Reliable detection of faults in PV systems plays an important role in improving their reliability, productivity, and safety. This paper addresses the detection of faults in the direct current (DC) side of photovoltaic (PV) systems using a statistical approach. Specifically, a simulation model that mimics the theoretical performances of the inspected PV system is designed. Residuals, which are the difference between the measured and estimated output data, are used as a fault indicator. Indeed, residuals are used as the input for the Multivariate CUmulative SUM (MCUSUM) algorithm to detect potential faults. We evaluated the proposed method by using data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.
Original languageEnglish (US)
Title of host publication2017 IEEE Symposium Series on Computational Intelligence (SSCI)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Print)9781538627266
StatePublished - Feb 12 2018


Dive into the research topics of 'Model-based fault detection algorithm for photovoltaic system monitoring'. Together they form a unique fingerprint.

Cite this