A statistical-based approach for fault detection and diagnosis in a photovoltaic system

Elyes Garoudja, Fouzi Harrou, Ying Sun, Kamel Kara, Aissa Chouder, Santiago Silvestre

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

14 Scopus citations

Abstract

This paper reports a development of a statistical approach for fault detection and diagnosis in a PV system. Specifically, the overarching goal of this work is to early detect and identify faults on the DC side of a PV system (e.g., short-circuit faults; open-circuit faults; and partial shading faults). Towards this end, we apply exponentially-weighted moving average (EWMA) control chart on the residuals obtained from the one-diode model. Such a choice is motivated by the greater sensitivity of EWMA chart to incipient faults and its low-computational cost making it easy to implement in real time. Practical data from a 3.2 KWp photovoltaic plant located within an Algerian research center is used to validate the proposed approach. Results show clearly the efficiency of the developed method in monitoring PV system status.
Original languageEnglish (US)
Title of host publication2017 6th International Conference on Systems and Control (ICSC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages75-80
Number of pages6
ISBN (Print)9781509039609
DOIs
StatePublished - Jul 10 2017

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