research-article

A survey of fault detection and identification methods for Photovoltaic systems based on I-V curves

Authors:

Stylianos Voutsinas,

Dimitrios Karolidis,

Ioannis Voyiatzis,

Maria SamarakouAuthors Info & Claims

PCI '20: Proceedings of the 24th Pan-Hellenic Conference on Informatics

Pages 281 - 284

https://doi.org/10.1145/3437120.3437325

Published: 04 March 2021 Publication History

Abstract

Photovoltaic systems (PVS), like all energy production systems, must be monitored in order to be able to detect failures in near real-time so that they will maintain their performance to an optimum level, thus achieving the greatest possible reliability. There are several algorithms for identifying faults during the operation of a PVS based on I-V curves. These algorithms can be applied to PVS telemetry data either locally or remotely. Implementations can be simple like the recording and comparing measurements, but they can also be more advanced like the use of neural networks to detect PV faults. In the present paper, fault detection and identification methods based on I-V curves are presented. The discussed methods are selected according to the recent literature, are presented and analyzed so that their differences, advantages, and limits are pointed out.

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Cited By

Voutsinas SKarolidis DVoyiatzis ISamarakou M(2022)Development of an IoT power management system for photovoltaic power plants2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)10.1109/MOCAST54814.2022.9837652(1-5)Online publication date: 8-Jun-2022
https://doi.org/10.1109/MOCAST54814.2022.9837652
Voutsinas SKarolidis DVoyiatzis ISamarakou M(2021)Development of a fault detection algorithm for Photovoltaic SystemsProceedings of the 25th Pan-Hellenic Conference on Informatics10.1145/3503823.3503839(84-87)Online publication date: 26-Nov-2021
https://dl.acm.org/doi/10.1145/3503823.3503839

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cover image ACM Other conferences

PCI '20: Proceedings of the 24th Pan-Hellenic Conference on Informatics

November 2020

433 pages

ISBN:9781450388979

DOI:10.1145/3437120

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 04 March 2021

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This research has been co?financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH ? CREATE ? INNOVATE

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PCI 2020

PCI 2020: 24th Pan-Hellenic Conference on Informatics

November 20 - 22, 2020

Athens, Greece

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Overall Acceptance Rate 190 of 390 submissions, 49%

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Cited By

Voutsinas SKarolidis DVoyiatzis ISamarakou M(2022)Development of an IoT power management system for photovoltaic power plants2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)10.1109/MOCAST54814.2022.9837652(1-5)Online publication date: 8-Jun-2022
https://doi.org/10.1109/MOCAST54814.2022.9837652
Voutsinas SKarolidis DVoyiatzis ISamarakou M(2021)Development of a fault detection algorithm for Photovoltaic SystemsProceedings of the 25th Pan-Hellenic Conference on Informatics10.1145/3503823.3503839(84-87)Online publication date: 26-Nov-2021
https://dl.acm.org/doi/10.1145/3503823.3503839

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