Fault detection and diagnosis of photovoltaic system based on neural networks approach

Abstract

Solar energy has become one of the most important renewable energies in the world. With the increasing installation of power plants in the world, the supervision and diagnosis of photovoltaic systems have become an important challenge with the increased occurrence of various internal and external faults. Indeed, this work proposes a new solar power plant diagnosis based on the artificial neural network approach. The developed model was to improve the performance and reliability of the power plant located in Tamanrasset, Algeria, which is subjected to varying weather conditions in terms of radiation and ambient temperature. By using the real data collected from the studied system, this approach allow to increase electricity production and address any issues that may arise quickly, ensuring uninterrupted power supply for the region. Neural networks have shown interesting results with high accuracy. This fault diagnosis approach allows to determine the time of occurrence of a fault affecting the examined PV system. Also, allow an early detection of failures and degradation of the system, which contributes to improving the productivity of this photovoltaic installation. With a significant reduction in the time needed to repair the damage caused by these faults and improve the reliability and continuity of the electrical energy production service.

A Comprehensive Review of Supervised Learning Algorithms for the Diagnosis of Photovoltaic Systems, Proposing a New Approach Using an Ensemble Learning Algorithm

“…However, the accuracy of defect detection may vary depending on the principle and model architecture of the machine learning (ML) used [75]. There are various types of supervised learning models available, with the most common being k-nearest neighbors (KNN), decision trees (DT), artificial neural networks (ANN), fuzzy logic (FL), random forest (RF), support vector machines (SVM), and so on [31,34,57,[76][77][78]. Depending on the expected result, an author can choose to use a single model or combine two or three models to assess the relevance of their work.…”

Intelligent fault detection of photovoltaic panel using neural networks

“…The mathematical model for the single-diode equivalent circuit of a photovoltaic cell can be expressed by the following equation (Mohd Amiruddin et al, 2020b;Rahmoune et al, 2023), (Bouzidi et al, 2021a(Bouzidi et al, , 2022a:…”

“…It constitutes essential supplies in driving production, achieving economic and social stability and growth, providing job opportunities, improving living standards, and reducing poverty. Therefore, most countries in the world are interested in developing this energy source and setting it as a goal to be achieved (Mohd Amiruddin et al, 2020a;Rahmoune et al, 2023).…”