Wind states and power curve modeling: A case study for La Rumorosa I Wind Farm

This paper analyzes La Rumorosa I Wind Farm's wind states and their characteristics in the operation of two wind turbines over the course of one year of records. This information identifies the impact of wind states on wind power output. The study used the Gaussian Mixture Model to classify the occurrence and frequency of the dominant wind states in the generation of energy from the turbines. Results were obtained for mesoscale wind states and local scale wind states, such as cold fronts and Santa Ana winds, as well as daytime, nighttime and hot days, respectively, which were statistically analyzed to determine their relationship to power output by generating power and power coefficient curves. Between the cut-in speed and the rated speed of the wind turbines, cold fronts show higher efficiency, unlike nighttime wind states, which are the most efficient past the rated speed. In addition, cold fronts are also those that occur to the greatest extent, contributing 31.26% of the energy produced per year, compared with the Santa Ana winds, which occur to a lesser extent; however, they contribute 22.11% of the energy produced per year.