Accurate and reliable fault detection in photovoltaic (PV) systems is essential for optimizing their performance and durability. This paper introduces a novel approach for fault detection and diagnosis in large-scale PV systems, utilizing power loss analysis and predictive models based on Random Forest (RF) and K-Nearest Neighbors (KNN) algorithms. The proposed methodology establishes a predictive baseline model of the system’s healthy behavior under normal operating conditions, enabling real-time detection of deviations between expected and actual performance. Faults such as string disconnections, module short-circuits, and shading effects have been identified using two key indicators: current error (Ec) and voltage error (Ev). By focusing on power losses as a fault indicator, this method provides high-accuracy fault detection without requiring extensive labeled data, a significant advantage for large-scale PV systems where data acquisition can be challenging. Additionally, a key contribution of this work is the identification and correction of faulty sensors, specifically pyranometer misalignment, which leads to inaccurate irradiation measurements and disrupts fault diagnosis. The approach ensures reliable input data for the predictive models, where RF achieved an R² of 0.99657 for current prediction and 0.99459 for power prediction, while KNN reached an R² of 0.99674 for voltage estimation, improving both the accuracy of fault detection and the system’s overall performance. The outlined approach was experimentally validated using real-world data from a 500 kWp grid-connected PV system in Ain El Melh, Algeria. The results demonstrate that this innovative method offers an efficient, scalable solution for real-time fault detection, enhancing the reliability of large PV systems while reducing maintenance costs.

The purpose of the work was to evaluate and compare the performances of silicon PV module under standard test and real test conditions. This paper provides a detailed analytical model for characterizing the electrical performance of silicon photovoltaic module. The simulation results have been performed in MATLAB/Simulink® environment. We proved that difference between the standard test and real test conditions, is attributed to various factors including effect of temperature variations and consequently some adjustments should be considered in electrical parameters to improve the PV module efficiency.

In the last decades, photovoltaic technology has become more employed by the industry, labs and universities, due its many benefits such as the exploitation and increasing of the solar energy conversion efficiency. In this paper, we will study and compare the performances of MPPT techniques control system consisting a PV system under different conditions of irradiation in the order to minimize the loss of energy provided by the PV module and to improve energy efficiency. This control is carried out by implementing of the MPPT based on Perturb and Observe algorithm (P&O) and Fuzzy Logic algorithm (FL) under MATLAB/Simulink® environment. Results of simulation showed that the FL controller exhibits a much better behavior than P&O controller.

In this work, a theoretical study is presented in the aim to evaluate the performance of two different types of silicon PV modules under Low Concentration Photovoltaic LCPV conditions. For this purpose, this paper describes a mathematical LCPV model implanted in MATLAB/Simulink ^® software. Based on the numerical results, we demonstrate and compare the limitation of using commercial mono-crystalline and poly-crystalline PV modules. We perceive from the characteristic parameters variation, the necessity of using a cooling system to improve the PV modules efficiency.

The solar photovoltaic device is one of the promising sources to generate high electricity. Hence, the PV cells depend on many factors to improve their efficiencies such as (the choice of materials, the number of junctions, the specific design...). This paper investigates, theoretically, the cell's temperature dependence of the performance of a triple junction solar cell with different structures in the temperature range of [25-150°C]. In the present work, a mathematical model is developed to describe the variation of Current -Voltage (I-V) and Power-Voltage (P-V) curves for Series junction solar cell SJSC and novel junction solar cell structure called Hybrid junction solar cell HJSC. Based on the simulation results, we discuss and compare the important influence of cell's temperature on these parameters, viz, short circuit current (I _sc ), open circuit voltage (V _oc ), fill factor (FF) and efficiency (η). Although, the hybrid junction offers a lower efficiency value compared to the series junction under Standard Test Conditions (STC), the variation of HJSC parameters shows generally less dependence to cell's temperature regarding SJSC. This study can be used to analyze little in terms of physical insight and design feedback for optimizing cell performance in terrestrial applications.