Dhimish, Mahmoud and Badran, Ghadeer (2019) Photovoltaic Hot-Spots Fault Detection Algorithm using Fuzzy Systems. IEEE Transactions on Device and Materials Reliability. pp. 671-679. ISSN 1530-4388
Abstract
Faults in photovoltaic (PV) modules, which might result in energy loss and reliability problems are often difficult to avoid, and certainty need to be detected. One of the major reliability problems affecting PV modules is hot-spotting, where a cell or group of cells heats up significantly compared to adjacent solar cells, hence decreasing the optimum power generated. In this article, we propose a fault detection of PV hot-spots based on the analysis of 2580 PV modules affected by different types of hot-spots, where these PV modules are operated under various environmental conditions, distributed across the U.K. The fault detection model comprises a fuzzy inference system (FIS) using Mamdani-type fuzzy controller including three input parameters, namely, percentage of power loss (PPL), short circuit current (I sc ), and open circuit voltage (V oc ). In order to test the effectiveness of the proposed algorithm, extensive simulation and experimental-based tests have been carried out; while the average obtained accuracy is equal to 96.7%.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © IEEE, 2019. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 02 Sep 2021 13:40 |
Last Modified: | 17 Oct 2024 08:49 |
Published Version: | https://doi.org/10.1109/TDMR.2019.2944793 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1109/TDMR.2019.2944793 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177703 |