Abstract
In recent years, solar PV panels have been increasingly used as an alternative to conventional energy resources. For the efficient operation of the PV array, maximum power has to be extracted. In general, PV panels are connected in series and parallel combinations, forming an array to meet the load demand. During operation, PV array systems are subjected to various faults such as line to line (LL), line to ground (LG), line to line ground (LLG) and bypass diode types. This causes a significant reduction in maximum power generation and may adversely affect the healthy panels. Therefore, in order to detect the instance of fault occurrence, the wavelet transform technique is used with inputs such as solar PV array voltage (\(V_{PV}\)) and current (\(I_{PV}\)). Upon fault detection, classification and the identification of the faulty string are made by applying a wavelet transform to a panel per string. For validation, the proposed technique is implemented for a 300 W (\(5 \times 3\)) PV array in a Simulink environment. Under various faults cases, for PV array values, the wavelet coefficient (approximate and detailed) shows appreciable changes and detects the fault accurately. In particular, the detailed coefficient varied from \(10^{-04}\) to \(10^{-01}\) range and for approximate coefficients, the values varies from 10.12 to 20 or 400 range depending upon the type of faults. Furthermore, for the fault location, the wavelet coefficient is able to identify the faulty string by which it can be isolated at an earlier stage. For various fault cases, the obtained results are presented and found to be satisfactory in detecting the fault, classifying and locating it.
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Appendices
Appendices
Matlab PV model 300 W | |
|---|---|
Parameters | Values |
\(V_{MPP}\) | 17.3 V |
\(I_{MPP}\) | 1.16 A |
\(P_{MPP}\) | 20 W |
\(V_{OC}\) | 21.1 V |
\(I_{SC}\) | 1.58 A |
No of panel in series | 5 |
No of panel in parallel | 3 |
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Arunachalam, V., Karthickraja, J. & Senthamizh Selvan, S. Wavelet transform based detection, classification and location of faults in a PV array. J Ambient Intell Human Comput 14, 11227–11237 (2023). https://doi.org/10.1007/s12652-023-04628-3
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DOI: https://doi.org/10.1007/s12652-023-04628-3