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

doi:10.1109/ICoSC.2017.7958710

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

^*Corresponding author for this work

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

25 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 language	English (US)
Title of host publication	2017 6th International Conference on Systems and Control, ICSC 2017
Editors	Driss Mehdi, Said Drid, Abdelouahab Aitouche
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	75-80
Number of pages	6
ISBN (Electronic)	9781509039609
DOIs	https://doi.org/10.1109/ICoSC.2017.7958710
State	Published - Jun 23 2017
Event	6th International Conference on Systems and Control, ICSC 2017 - Batna, Algeria Duration: May 7 2017 → May 9 2017

Publication series

Name	2017 6th International Conference on Systems and Control, ICSC 2017

Conference

Conference	6th International Conference on Systems and Control, ICSC 2017
Country/Territory	Algeria
City	Batna
Period	05/7/17 → 05/9/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

ASJC Scopus subject areas

Control and Optimization
Control and Systems Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ICoSC.2017.7958710

Cite this

Garoudja, E., Harrou, F., Sun, Y., Kara, K., Chouder, A., & Silvestre, S. (2017). A statistical-based approach for fault detection and diagnosis in a photovoltaic system. In D. Mehdi, S. Drid, & A. Aitouche (Eds.), 2017 6th International Conference on Systems and Control, ICSC 2017 (pp. 75-80). Article 7958710 (2017 6th International Conference on Systems and Control, ICSC 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICoSC.2017.7958710

Garoudja, Elyes ; Harrou, Fouzi ; Sun, Ying et al. / A statistical-based approach for fault detection and diagnosis in a photovoltaic system. 2017 6th International Conference on Systems and Control, ICSC 2017. editor / Driss Mehdi ; Said Drid ; Abdelouahab Aitouche. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 75-80 (2017 6th International Conference on Systems and Control, ICSC 2017).

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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",

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Garoudja, E, Harrou, F , Sun, Y, Kara, K, Chouder, A & Silvestre, S 2017, A statistical-based approach for fault detection and diagnosis in a photovoltaic system. in D Mehdi, S Drid & A Aitouche (eds), 2017 6th International Conference on Systems and Control, ICSC 2017., 7958710, 2017 6th International Conference on Systems and Control, ICSC 2017, Institute of Electrical and Electronics Engineers Inc., pp. 75-80, 6th International Conference on Systems and Control, ICSC 2017, Batna, Algeria, 05/7/17. https://doi.org/10.1109/ICoSC.2017.7958710

A statistical-based approach for fault detection and diagnosis in a photovoltaic system. / Garoudja, Elyes; Harrou, Fouzi ; Sun, Ying et al.
2017 6th International Conference on Systems and Control, ICSC 2017. ed. / Driss Mehdi; Said Drid; Abdelouahab Aitouche. Institute of Electrical and Electronics Engineers Inc., 2017. p. 75-80 7958710 (2017 6th International Conference on Systems and Control, ICSC 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Garoudja, Elyes

AU - Harrou, Fouzi

AU - Sun, Ying

AU - Kara, Kamel

AU - Chouder, Aissa

AU - Silvestre, Santiago

PY - 2017/6/23

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N2 - 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.

AB - 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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Garoudja E, Harrou F , Sun Y, Kara K, Chouder A, Silvestre S. A statistical-based approach for fault detection and diagnosis in a photovoltaic system. In Mehdi D, Drid S, Aitouche A, editors, 2017 6th International Conference on Systems and Control, ICSC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 75-80. 7958710. (2017 6th International Conference on Systems and Control, ICSC 2017). doi: 10.1109/ICoSC.2017.7958710

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

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

UN SDGs

Access to Document

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