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

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis 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.Peer ReviewedPostprint (author's final draft