Fault detection and diagnosis methods for photovoltaic systems: A review
Faults in any components (modules, connection lines, converters, inverters, etc.) of photovoltaic (PV) systems (stand-alone, grid-connected or hybrid PV systems) can seriously affect the efficiency, energy yield as well as the security and reliability of the entire PV plant, if not detected and corr...
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Published in | Renewable & sustainable energy reviews Vol. 91; pp. 1 - 17 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.08.2018
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Subjects | |
Online Access | Get full text |
ISSN | 1364-0321 1879-0690 |
DOI | 10.1016/j.rser.2018.03.062 |
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Abstract | Faults in any components (modules, connection lines, converters, inverters, etc.) of photovoltaic (PV) systems (stand-alone, grid-connected or hybrid PV systems) can seriously affect the efficiency, energy yield as well as the security and reliability of the entire PV plant, if not detected and corrected quickly. In addition, if some faults persist (e.g. arc fault, ground fault and line-to-line fault) they can lead to risk of fire. Fault detection and diagnosis (FDD) methods are indispensable for the system reliability, operation at high efficiency, and safety of the PV plant. In this paper, the types and causes of PV systems (PVS) failures are presented, then different methods proposed in literature for FDD of PVS are reviewed and discussed; particularly faults occurring in PV arrays (PVA). Special attention is paid to methods that can accurately detect, localise and classify possible faults occurring in a PVA. The advantages and limits of FDD methods in terms of feasibility, complexity, cost-effectiveness and generalisation capability for large-scale integration are highlighted. Based on the reviewed papers, challenges and recommendations for future research direction are also provided.
•Different type of faults including affected components, causes and effects are reported.•Fault detection and diagnosis (FDD) methods of PVSs are extensively reviewed.•Advantages and limits of different FDD methods are illustrated and discussed.•A challenging issue in fault detection and diagnosis of PVS are reported.•Recommendations for future research direction in FDD methods are provided. |
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AbstractList | Faults in any components (modules, connection lines, converters, inverters, etc.) of photovoltaic (PV) systems (stand-alone, grid-connected or hybrid PV systems) can seriously affect the efficiency, energy yield as well as the security and reliability of the entire PV plant, if not detected and corrected quickly. In addition, if some faults persist (e.g. arc fault, ground fault and line-to-line fault) they can lead to risk of fire. Fault detection and diagnosis (FDD) methods are indispensable for the system reliability, operation at high efficiency, and safety of the PV plant. In this paper, the types and causes of PV systems (PVS) failures are presented, then different methods proposed in literature for FDD of PVS are reviewed and discussed; particularly faults occurring in PV arrays (PVA). Special attention is paid to methods that can accurately detect, localise and classify possible faults occurring in a PVA. The advantages and limits of FDD methods in terms of feasibility, complexity, cost-effectiveness and generalisation capability for large-scale integration are highlighted. Based on the reviewed papers, challenges and recommendations for future research direction are also provided.
•Different type of faults including affected components, causes and effects are reported.•Fault detection and diagnosis (FDD) methods of PVSs are extensively reviewed.•Advantages and limits of different FDD methods are illustrated and discussed.•A challenging issue in fault detection and diagnosis of PVS are reported.•Recommendations for future research direction in FDD methods are provided. |
Author | Kalogirou, S.A. Tina, G.M. Mellit, A. |
Author_xml | – sequence: 1 givenname: A. orcidid: 0000-0002-3654-1437 surname: Mellit fullname: Mellit, A. email: amellit@ictp.it organization: Renewable Energy Laboratory, Faculty of Sciences and Technology, University of Jijel, P.O. Box .98, Jijel 18000, Algeria – sequence: 2 givenname: G.M. surname: Tina fullname: Tina, G.M. organization: DIEEI: Department of Electric, Electronic and Computer Engineering, University of Catania, v.le A. Doria 6, 95125 Catania, Italy – sequence: 3 givenname: S.A. surname: Kalogirou fullname: Kalogirou, S.A. organization: Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603, Cyprus |
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