Forecast Optimization of Wind Speed in the North Coast of the Yucatan Peninsula, Using the Single and Double Exponential Method

Abstract

Installation of new wind farms in areas such as the north coast of the Yucatan peninsula is of vital importance to face the local energy demand. For the proper functioning of these facilities it is important to perform wind data analysis, the data having been collected by anemometers, and to consider the particular characteristics of the studied area. However, despite the great development of anemometers, forecasting methods are necessary for the optimal harvesting of wind energy. For this reason, this study focuses on developing an enhanced wind forecasting method that can be applied to wind data from the north coast of the Yucatan peninsula (in general, any type of data). Thus, strategies can be established to generate a greater amount of energy from the wind farms, which supports the local economy of this area. Four variants have been developed based on the traditional double and single exponential methods. Furthermore, these methods were compared to the experimental data to obtain the optimal forecasting method for the Yucatan area. The forecasting method with the highest performance has obtained an average relative error of 7.9510% and an average mean error of 0.3860 m/s.

Keywords

• forecasting method
• wind speed
• exponential smoothing
• moving average