Abstract
Purpose: In this paper, we analyzed the intra-annual variability of complexity of wind dynamics in Petrolina, Brazil and its relation with the wind potential. Methodology: We applied the Multiscale Sample Entropy (MSE) method on wind speed temporal series for each month of 2010. The data are recorded every 10 min at 50m height. Results: The results showed higher entropy values at higher temporal scales indicating that wind speed fluctuations are les regular and less predictable when wind speed is observed at lower temporal frequency. For all months, average wind speed is above a cut in level 3.5 m, the speed at which turbines start operating and producing electricity, indicating that the location of Petrolina is promising for wind energy generation. We also found that the wind speed is positively correlated with entropy values for all months when recorded at 10min frequency and between August and December when recorded t 1 h frequency. Conclusion: In these periods wind speed temporal fluctuations are more irregular, which is considered as unfavorable condition for the operation of wind turbines, leading to lower efficiency in the capture of wind energy for electricity production.
Highlights
Among renewable energy sources wind power is one with most rapidly growing rate over the last decades because of its high efficiency and low pollution
In this work we evaluate the complexity of wind speed dynamics using Multiscale Entropy method which provides information about time series regularity for multiple temporal scales (Costa, Goldberger, & Peng, 2002)
We studied intra annual complexity of the time series of wind speed in Petrolina using Multiscale Sample Entropy method (MSE)
Summary
Among renewable energy sources wind power is one with most rapidly growing rate over the last decades because of its high efficiency and low pollution. It is projected to grow to 8.0%, in 2020, where half of the total capacity will be installed in the Northeastern region (Witzler, Ramos, Camargo, & Guarnier, 2016). This remarkable growth is the result of the government Program for Incentive of Alternative Electric Energy Sources (Programa de Incentivo às Fontes Alternativas de Energia Elétrica - Proinfa), which was created in 2002 to stimulate the electricity generation from wind power, biomass, and small hydroelectric plants (Dutra & Szklo, 2008). Due to intermittency and high spatio-temporal variability of wind speed, large scale integration of wind power into electricity grid is still challenging task (Behera, Sahoo, & Pati, 2015)
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