Abstract:

The integration of renewable energy sources (RES) into the power grid has significantly grown in response to the rise in energy demand. Since wind energy tends to be intermittent and is continuously incorporated into the grid, it is crucial to properly forecast wind speed to maintain the reliability of the power system and the balance between supply and demand. In this study, using R-Studio software, daily and monthly data of wind speed of Ras Gharib-Egypt were modeled using statistical models (time series forecasting methods). The best parameters related to each method that result in the best model are identified through a careful examination of various values for each parameter. Then, using various error metrics calculated for each model, a process of model assessment is used to determine the best models among the investigated forecasting techniques. The precise models selected are extremely important because they can be employed to address both short-term operating issues and long-term planning concerns in the power system to get more trustworthy results over a variety of timescales.

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