Result: Evaluation of Environmental Factors Influencing Photovoltaic System Efficiency Under Real-World Conditions.

The study addresses the impact of selected environmental factors on the energy production of photovoltaic systems under real outdoor conditions, with particular emphasis on the application of evolutionary computation techniques. The experiment was carried out on a dedicated test stand, where measurements were made under natural environmental conditions. Parameters such as solar irradiance, wind speed, temperature, air pollution, and obtained PV power were continuously recorded. Initial correlation analysis using Pearson and Spearman coefficients confirmed associations between environmental factors and power output, especially solar irradiance. In order to advance the analysis beyond conventional methods, a linear regression model was developed in which the model weights were optimized using evolutionary algorithms, allowing for a more robust assessment of the contribution of each parameter. The results showed that solar irradiance accounted for 97.79% of the variance in photovoltaic power, while temperature (0.95%), air pollution (0.72%), and wind speed (0.54%) had significantly lower impacts. The implementation of evolutionary algorithms represents a novel approach in this context and has proven to be effective in quantifying environmental influence under complex real-world conditions. Furthermore, the findings highlight the indirect role of air pollution in attenuating irradiance and reducing system efficiency. These insights provide a foundation for the development of adaptive control strategies and predictive models to optimize the performance of the photovoltaic system in dynamic environmental settings. [ABSTRACT FROM AUTHOR]