Novel Photovoltaic Hot-spotting Fault Detection Algorithm

Mahmoud Dhimish, Peter Mather, Violeta Holmes

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


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%.

Original languageEnglish
Article number8685128
Pages (from-to)378-386
Number of pages9
JournalIEEE Transactions on Device and Materials Reliability
Issue number2
Early online date11 Apr 2019
Publication statusPublished - 5 Jun 2019


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