Photovoltaic system faults detection using fractional multiresolution signal decomposition
| Autor: | A. Lanani, D. Djamai, A. Beddiaf, A. Saidi, A. Abboudi |
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| Jazyk: | English<br />Russian<br />Ukrainian |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Electrical engineering & Electromechanics, Vol 2024, Iss 4, Pp 48-54 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2074-272X 2309-3404 14647826 |
| DOI: | 10.20998/2074-272X.2024.4.06 |
| Popis: | Introduction. In this paper, we present an innovative methodology based on fractional wavelets for detecting defects in photovoltaic systems. Photovoltaic solar systems play a key role in the transition to a low-carbon economy, but they are susceptible to various defects such as microcracks, wiring faults, and hotspots. Early detection of these anomalies is crucial to prevent energy losses and extend the lifespan of installations. Novelty of the proposed work resides in its pioneering nature, leveraging a family of fractional wavelets, with a specific emphasis on fractional Haar wavelets. This approach enhances sensitivity in anomaly detection, introducing a fresh and promising perspective to enhance the reliability of photovoltaic installations. Purpose of this study is to develop a defect detection methodology in photovoltaic systems using fractional wavelets. We aim to improve detection sensitivity with a specific focus on low-amplitude defects such as microcracks. Method. Our innovative methodology is structured around two phases. Firstly, we undertake a crucial step of filtering photovoltaic signals using fractional Haar wavelets. This preliminary phase is of paramount importance, aiming to rid signals of unwanted noise and prepare the ground for more precise defect detection. The second phase of our approach focuses on the effective detection of anomalies. We leverage the multiresolution properties of fractional wavelets, particularly emphasizing fractional Haar wavelets. This step achieves increased sensitivity, especially in the detection of low-amplitude defects. Results. By evaluating the performance of our method and comparing it with techniques based on classical wavelets, our results highlight significant superiority in the accurate detection of microcracks, wiring faults, and hotspots. These substantial advances position our approach as a promising solution to enhance the reliability and efficiency of photovoltaic installations. Practical value. These advancements open new perspectives for preventive maintenance of photovoltaic installations, contributing to strengthening the sustainability and energy efficiency of solar systems. This methodology offers a promising solution to optimize the performance of photovoltaic installations and ensure their long-term reliability. References 21, tables 3, figures 10. |
| Databáze: | Directory of Open Access Journals |
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