A novel approach to wind energy modeling in the context of climate change at Zaafrana region in Egypt.

Global warming, driven by the excessive emission of greenhouse gases from the combustion of fossil fuels, has emerged as a critical environmental challenge which is considered as a motivation for this research. Where, the switch to sustainable energy sources is crucial because of the pressing need to slow down climate change and lower carbon footprints. Of all the renewable energy sources, wind energy is particularly important as a means of reducing carbon emissions from the generation of electricity. With the increase in the penetration of renewable energy resources in electrical power systems, the stochastic behavior of the renewable energy resources has to be taken into account for better analysis in power systems. However, the stochastic behavior of the renewable energy is also affected by the environmental conditions. In this context, The main objective of this paper is to present a novel wind energy modeling that includes the effect of ambient temperature on the wind turbine capabilities. This effect is presented as the de-rating curve for wind turbine output power to respect the thermal capabilities of the electrical components of the wind turbine. That's why this novel model is developed to consider the effect of ambient temperature to represent the practical limitations of wind turbines which wasn't considered by previous literature although the temperature has a siginicant impact on the wind turbine output power. In this Paper, Gamesa G80 wind turbine is used to perform the numerical analysis of the proposed new model. Moreover, Exponential Distribution Optimizer (EDO), Aquila Optimizer (AO), and Equilibrium Optimizer (EO) algorithms are used to find various probability distribution functions (PDFs) parameters to model wind speed data from Zaafrana region in Egypt using Root Mean Square Error (RMSE) and Coefficient of Correlation (R^2) as judging criteria. In addition, real temperature data from the same site are used to validate the proposed model compared to the manufacturer's capabilities. The results show that mixed PDFs provide a better representation for the wind speed data. Moreover, the study demonstrates that ambient temperature cannot be neglected in wind power modeling, as the wind turbine output power varies significantly. Additionally, this work highlights the impact of climate change on the efficiency of renewable energy sources like the wind energy. The proposed wind energy model could be valuable to system operators as a decision-making aid when dealing with and analyzing complex power systems.