What is it about?
Studies show that the performance of photovoltaic modules is strongly influenced by temperature and irradiance, with efficiency decreasing at higher temperatures and increasing with higher irradiance. In this context, this work conducts a high-precision quantitative characterization of four module technologies — CdTe, CIGS, HIT, and monocrystalline silicon — using the Self-Adaptive Differential Evolution algorithm applied to current–voltage datasets from NREL. The main contribution lies in the precise extraction of temperature and irradiance coefficients for the single-diode model parameters (Iph, I0, n, Rs, and Rsh), enabling reliable modeling and comparison of technologies under different operating conditions. The results provide reference values for simulation, performance prediction, and optimization of photovoltaic systems, enhancing the accuracy of analyses and serving as a practical foundation for researchers and engineers in the field.
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Why is it important?
The study is important because it combines precise modeling, data science, and solar energy, providing practical tools for researchers, engineers, and photovoltaic system planners, while contributing to the optimization of efficiency and reliability in real-world applications.
Perspectives
The precise characterization of photovoltaic module parameters enables the development of advanced predictive models capable of simulating solar cell performance under different environmental conditions. In the future, these models can be integrated into intelligent monitoring and control systems, used for optimizing module and solar plant designs, and for efficient energy generation planning, contributing to the expansion of solar energy and the transition toward a sustainable energy matrix.
Alessandro Silva
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This page is a summary of: Parametric evaluation of CdTe, CIGS, HIT, and mSi solar modules as a function of temperature and irradiance variation, Journal of Renewable and Sustainable Energy, September 2025, American Institute of Physics,
DOI: 10.1063/5.0289606.
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