Fault Detection for Photovoltaic Panels in Solar Power Plants by Using Linear Iterative Fault Diagnosis (LIFD) Technique Based on Thermal Imaging System

Solar energy generation Photovoltaic modules that work reliably for 20-30 years in environmental conditions can only be cost-effective. The temperature inside the PV cell is not uniform due to an increase in defects in the cells. Monitoring the heat of the PV panel is essential. Therefore, research on photovoltaic modules is necessary. Infrared thermal imaging (IRT) has a significant role in determining the severity of problems in solar panels. Thus, in this work, a maximum power point tracking (MPPT) system based on a new image for thermal imaging is proposed to solve the photovoltaic (PV) defects using linear iterative fault diagnosis method. The thermal camera and new MPPT solution used for fault detection were developed to change the operating point to match the optimized MPP. The simulation work does go through the use of the proposed low-income food-deficient method in the MATLAB environment. The simulation results show the effectiveness of the proposed Linear Iterative Fault Diagnosis (LIFD) method and its ability to detect the fault and track the maximum power of the PV panel. The sensitivity, specificity and accuracy of the proposed work are 98%, 94% and 97%.