Photovoltaic Hot-Spots Fault Detection Algorithm Using Fuzzy Systems
| Autor: | Mahmoud Dhimish, Ghadeer Badran |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
010302 applied physics
Fuzzy classification Photovoltaic system Order (ring theory) Fuzzy control system Topology 01 natural sciences Fuzzy logic Fault detection and isolation Electronic Optical and Magnetic Materials Power (physics) Control theory 0103 physical sciences Electrical and Electronic Engineering Safety Risk Reliability and Quality Mathematics |
| Zdroj: | IEEE Transactions on Device and Materials Reliability. 19:671-679 |
| ISSN: | 1558-2574 1530-4388 |
| DOI: | 10.1109/tdmr.2019.2944793 |
| Popis: | 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 ( $\text{I}_{\mathrm{ sc}}$ ), and open circuit voltage ( $\text{V}_{\mathrm{ oc}}$ ). 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%. |
| Databáze: | OpenAIRE |
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