Caracterización y análisis de la variabilidad del viento en la zona de influencia de la central eólica Villonaco

Abstract

The present thesis focuses on the characterization and analysis of wind variability at the Villonaco Wind Farm during the 2020-2023 period. The main objective is to conduct a detailed statistical analysis of how the wind varies over these four years, using tools such as seasonality indices and time series decomposition through STL (Seasonal and Trend Decomposition using Loess). Additionally, the k-means clustering algorithm is implemented to determine the optimal number of groups that represent different wind behaviors. These clusters are represented using boxplot diagrams, allowing for a clear and precise characterization of the variability patterns in each identified group. This methodology aims to optimize the planning and operation of the wind farm, contributing to better management of wind resource variability and, consequently, greater stability in energy generation.