Wind Power in Girau do Ponciano, Alagoas, Brazil Using Anemometric Data and Microscale Modeling

Abstract The wind potential in the Agreste region of Northeastern Brazil has important features for energy exploration, but, stills unexplored. This work analyzes 3.1 yrs anemometer tower measurements in the Girau do Ponciano, Alagoas state. The observational data was recorded from October 2007 to O...

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Hauptverfasser: Ramos, Diogo Nunes Da Silva, Lyra, Roberto Fernando Da Fonseca, Rosiberto Salustiano Da Silva Júnior, Geórgenes Hilário Cavalcante Segundo, Lopes, Gerson Ernesto Varela
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creator Ramos, Diogo Nunes Da Silva
Lyra, Roberto Fernando Da Fonseca
Rosiberto Salustiano Da Silva Júnior
Geórgenes Hilário Cavalcante Segundo
Lopes, Gerson Ernesto Varela
description Abstract The wind potential in the Agreste region of Northeastern Brazil has important features for energy exploration, but, stills unexplored. This work analyzes 3.1 yrs anemometer tower measurements in the Girau do Ponciano, Alagoas state. The observational data was recorded from October 2007 to October 2010. Three periods were defined to constrain the seasonal wind patterns: Annual, Dry (October-January) and Wet (May-August). Hourly and monthly series showed the average wind speed was higher than 7 m s-1, reaching 8.5 m s-1 during the dry season. Further, the wind direction was also favorable with less variability, concentrated between NE and SE. During nighttime the wind speed ≥ 10 m s-1 were more frequent. The Weibull fit is more distributed (concentrated) during the dry (wet) season close to 8 m s-1 (7 m s-1). The AEP (Cf) parameter estimated by the WAsP model varied between 3 to 10 GWh (35% to 65%). Nevertheless, Girau do Ponciano domain was positioned nearby two highways and close to an electrical substation in the Arapiraca city. Other geographic conditions (topography inclination < 15°, the absence of obstacles, and low vegetation) are also favorable to future wind farm installation in this area.
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Meteorology
title Wind Power in Girau do Ponciano, Alagoas, Brazil Using Anemometric Data and Microscale Modeling
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