Wind Speed Seasonality in a Brazilian Amazon-Savanna Region from the Global Land Data Assimilation System

Abstract

The objective of this study was to develop a methodology for the use of remote sensing data for the planning of wind energy projects in Maranhão. Monthly wind speed and precipitation data from 2000 to 2016 were used. Initially, wind velocity data were processed using the principal component analysis (PCA) technique. Next, the grouping technique known as k-means was used. Finally, a linear regression analysis was performed with the objective of identifying the parameters to be used in the validation of the data estimated by the Global Land Data Assimilation System (GLDAS) base against the data measured by the meteorological stations. Four homogeneous zones were identified; the zone with the highest values of monthly average wind speeds is in the northern region of the state on the coast. The period of greatest intensity of the winds was identified to be in the months of October and November. The lowest values of precipitation were observed during these months. The analyses carried out by this study show a favorable scenario for the production of wind energy in the state of Maranhão.