Sensitivity Analysis of Environmental Parameters (Temperature and Irradiance) on the Efficiency of Silicon Solar Cells Using an Analytical Model Implemented in Python

Solar energy is one of the most promising renewable sources, yet the performance of silicon solar cells is highly dependent on environmental conditions, particularly temperature and irradiance. In this study, a single-diode analytical model incorporating temperature and irradiance dependencies is implemented in Python to simulate the electrical behavior of four commercial silicon solar cell technologies: monocrystalline, polycrystalline, PERC, and HJT. The model is validated under standard test conditions (STC), showing less than ۱% deviation from nominal values. A sensitivity analysis is conducted over a temperature range of ۱۵-۷۵ °C and an irradiance range of ۲۰۰-۱۰۰۰ W/m² using normalized sensitivity indices (S and S_G). The results indicate that HJT cells exhibit the lowest temperature sensitivity (S = -۰.۰۹۵), making them the most suitable for hot climates, while PERC cells demonstrate the highest STC efficiency (۱۹.۸%) and superior low-irradiance performance (S_c = ۰.۹۴). Polycrystalline cells show the highest temperature sensitivity (S_T = -۰.۱۲۸) but remain cost-effective for small-scale applications. The proposed Python-based framework provides a quantitative tool for predicting solar cell performance under varying environmental conditions and assists in technology selection for photovoltaic system design.

کلیدواژه ها:

Single-Diode Model ، Temperature Sensitivity ، Irradiance Sensitivity ، PERC and HJT solar cells ، Python-based simulation