Based on power law (PL), a novel method is proposed to extrapolate surface wind speed to the wind turbine (WT) hub height, via assessment of wind shear coefficient (WSC), by only using surface turbulence intensity, a parameter actually regarded as a merely critical one in wind energy studies. A 2-year (2012-2013) dataset from the meteorological mast of Cabauw (Netherlands) was used, including 10-min records collected at 10, 20, 40, and 80 m. WT hub heights of 40 and 80 m have been targeted for the extrapolation, being accomplished based on turbulence intensity observations at 10 and 20 m. Trained over the year 2012, the method was validated over the year 2013. Good scores were returned both in wind speed and power density extrapolations, with biases within 7 and 8%, respectively. Wind speed extrapolation was better predicted 10-40 m (NRMSE=0.16, r=0.95) than 10-80 and 20-80 m (NRMSE=0.20-0.24, r=0.86-0.91), while for power density even finer scores than wind speed were achieved (r=0.98 at 40 m, and r=0.96 at 80 m). Method's skills were also assessed in predicting wind energy yield. Application over sites with different terrain features and stability conditions is expected to provide further insight into its application field.

Surface turbulence intensity as a predictor of extrapolated wind resource to the turbine hub height

Giovanni Gualtieri
2015

Abstract

Based on power law (PL), a novel method is proposed to extrapolate surface wind speed to the wind turbine (WT) hub height, via assessment of wind shear coefficient (WSC), by only using surface turbulence intensity, a parameter actually regarded as a merely critical one in wind energy studies. A 2-year (2012-2013) dataset from the meteorological mast of Cabauw (Netherlands) was used, including 10-min records collected at 10, 20, 40, and 80 m. WT hub heights of 40 and 80 m have been targeted for the extrapolation, being accomplished based on turbulence intensity observations at 10 and 20 m. Trained over the year 2012, the method was validated over the year 2013. Good scores were returned both in wind speed and power density extrapolations, with biases within 7 and 8%, respectively. Wind speed extrapolation was better predicted 10-40 m (NRMSE=0.16, r=0.95) than 10-80 and 20-80 m (NRMSE=0.20-0.24, r=0.86-0.91), while for power density even finer scores than wind speed were achieved (r=0.98 at 40 m, and r=0.96 at 80 m). Method's skills were also assessed in predicting wind energy yield. Application over sites with different terrain features and stability conditions is expected to provide further insight into its application field.
2015
Istituto di Biometeorologia - IBIMET - Sede Firenze
Turbulence intensity
Power law
Wind shear coefficient
Atmospheric stabi
Wind energy yield
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/225954
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