A statistical based approach for fault detection and diagnosis in a photovoltaic system
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
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.
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CitationGaroudja, E., harrou, F., Sun, Y., kara, K., Chouder, A., Silvestre, S. A statistical based approach for fault detection and diagnosis in a photovoltaic system. A: International Conference on Systems and Control. "2017 6th International Conference on Systems and Control (ICSC 2017): Batna, Algeria: 7-9 May 2017". Batna: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 75-80.
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