Dhimish, Mahmoud, Mather, Peter and Holmes, Violeta (2019) Novel Photovoltaic Hot-spotting Fault Detection Algorithm. IEEE Transactions on Device and Materials Reliability. pp. 378-386.
Abstract
In this paper, a novel photovoltaic (PV) hot-spotting fault detection algorithm is presented. The algorithm is implemented using the analysis of 2580 polycrystalline silicon PV modules distributed across the U.K. The evaluation of the hot-spots is analyzed based on the cumulative density function (CDF) modeling technique, whereas the percentage of power loss (PPL) and PV degradation rate are used to categorize the hot-spots into eight different categories. Next, the implemented CDF models are used to predict possible PV hot-spots affecting the PV modules. The developed algorithm is evaluated using three different PV modules affected by three different hot-spots. Remarkably, the proposed CDF models precisely categorize the PV hot-spots with a high rate of accuracy of almost above 80%.
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 13:30 |
Last Modified: | 16 Oct 2024 17:49 |
Published Version: | https://doi.org/10.1109/TDMR.2019.2910196 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1109/TDMR.2019.2910196 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177704 |