MARIANO, E. B.; http://lattes.cnpq.br/4918047771213886; MARIANO, Everson Batista.
Resumo:
In this work, wind and wind power spatial and temporal variability were analyzed for the northern region. For this, the Brazilian development on the Regional Atmospheric Modeling System (BRAMS) atmospheric model was used, alongside National Center for Environmental Prediction (NCEP) reanalysis data. Observed wind speed data from three meso regions of Paraíba from October 1 to October 31, 2010 were used to validate the BRAMS model. Reanalyses of the ERA-Interim with spatial resolution of 0.75 ° x 0.75 ° were used as a second data source for the same purpose. In this comparison, we performed correlation analysis and verified its statistical significance, as well as the evaluation of the shape and fit parameters of the Weibull distribution. After further validation, wind simulations were generated in the months of March, June, September and December for the period from 1983 to 2013. Seasonal and interannual wind speed variation was evaluated in four cities with wind farms. The results show correlation coefficients above 0.70 with a statistical significance of 99% (α = 0.01). In the Weibull distribution, the shape and fit parameters were close to those obtained for the observed data. In the wind speed seasonal variation, September presented more intense, while March showed lower wind speeds with intermediate values verified in June and december. Spatial distribution of the average climatological wind speed and wind power topography influences are highlighted, with higher velocities and greater wind potential on higher altitude areas. Interannual variations, due to changes in the SST of the Pacific and Atlantic Tropical Oceans, have shown that in the years influenced by El Niño and positive Southern Gradient, the wind over the north east to Brazil is intensified and that the simultaneous action of both SST gradients amplifies this increase. With the results obtained the use of the Wind Power Density (WPD) simulation using the BRAMS model can be applied in any region of South America.