Photovoltaic module performance: Modeling, parameter estimation, and environmental effects

Abstract

This research addresses the pressing need for clean energy solutions by focusing on the increasing adoption of photovoltaic (PV) modules as alternatives to fossil fuel-based energy sources. Despite their promise, PV modules face challenges in maintaining efficiency under varying environmental conditions. To tackle this, the study develops a one-diode model of PV modules using the Gravitational Search Algorithm (GSA) to obtain the optimal PV parameters so that the performance of the PV modules across diverse weather conditions can be obtained. The integration of a microcontroller and sensors in the experimental setup allows for real-time monitoring of critical environmental variables such as irradiance, temperature, and humidity, alongside voltage and current measurements. While there are certain constraints, such as the sensitivity of sensor data to weather conditions and the significant dependency of estimated parameters on measurements. However, by analyzing the performance of three specific PV modules SOLTECH215, PHOTOWATT220, and KC200GT under varying conditions, this research provides invaluable insights into optimizing energy production and efficiency in practical applications. By bridging theoretical modeling with experimental validation, it lays the groundwork for more efficient and reliable solar energy systems, thus driving the transition towards a cleaner and more sustainable energy future.