@inproceedings{a85e0b862ca34a049202b7308ac93808,
title = "A statistical-based approach for fault detection and diagnosis in a photovoltaic system",
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.",
author = "Elyes Garoudja and Fouzi Harrou and Ying Sun and Kamel Kara and Aissa Chouder and Santiago Silvestre",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 6th International Conference on Systems and Control, ICSC 2017 ; Conference date: 07-05-2017 Through 09-05-2017",
year = "2017",
month = jun,
day = "23",
doi = "10.1109/ICoSC.2017.7958710",
language = "English (US)",
series = "2017 6th International Conference on Systems and Control, ICSC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "75--80",
editor = "Driss Mehdi and Said Drid and Abdelouahab Aitouche",
booktitle = "2017 6th International Conference on Systems and Control, ICSC 2017",
address = "United States",
}
