A Novel Method to Detect Partial Shadow Effects in Perovskite-Based Simulated Solar Cell System Faults

Abstract

When a fault occurs in photovoltaic systems, a human expert should be present at the scene and perform tests to determine the location and type of the fault. In such a situation, in order to maintain the safety of the specialist, protective measures such as shutting down the power plant or isolating the faulty part are usually taken. Given the fact that the equipment and technology of photovoltaic systems are expensive and their efficiency is currently relatively low (about 20%), a complete shutdown of the plant or part of it can be economical, return on investment and achieve profitability. Therefore, as much as possible, efforts should be made to detect and eliminate errors in the shortest possible time without shutting down the power plant. On the other hand, most solar power plants are located in desert areas, which make them difficult to access and visit. In this case, training skilled manpower and the constant presence of an expert on site can be very costly and uneconomical. Also, if these errors are not detected and fixed in time, they can lead to power loss (not using the maximum potential of the panel), device failure and eventually fire. In this research, using fuzzy detection method, a suitable method for detecting the error of partial shadow occurrence in solar cells is presented. Based on the simulation results, the efficiency of the proposed method is confirmed.

Analysis and Monitoring of Maximum Solar Potential for Energy Production Optimization Using Photovoltaic Panels

“…Shadow effects: Shadows on the panels can significantly reduce their efficiency. Therefore, it is important to avoid shadows on the panels, especially during hours when the intensity of sunlight is crucial [40,41].…”