A simulation-based framework for pre-installation solar PV feasibility assessment using long-term climatic data

Generation of electricity from solar photovoltaic (PV) panels is an economical, clean, and renewable energy solution; however, achieving the desired power output during installation remains a challenging task. This study presents a method to estimate solar potential prior to the installation of a solar power plant at a given location. A discrepancy often exists between the installed and actual capacity of PV systems due to environmental factors, system losses, and PV cell efficiency. To address this issue, a 100 kW grid-connected solar PV system is modeled using an average Voltage Source Converter controller integrated with a Maximum Power Point Tracking algorithm based on the perturb and observe technique. Long-term climatological datasets of temperature and irradiance are obtained from the National Aeronautics and Space Administration (NASA) POWER database for the Bahawalpur region (Punjab, Pakistan). These data are used as input to the MATLAB/Simulink model to simulate power generation and power loss under varying conditions of direct normal irradiance, diffuse irradiance, and temperature. The results show good agreement with theoretical expectations. The generated power varies between 23.43% and 87.07%, while power loss ranges from 12.93% to 76.57% under different operating conditions. The proposed approach can be applied to other regions, subject to the availability of relevant climatic data.