Based on power law, a novel method is proposed to extrapolate surface wind speed (v) to the wind turbine (WT) hub height, via prediction of the wind shear coefficient (WSC) daily course, by only using the surface turbulence intensity (I) daily course. Work's main outcome is a strict (almost 1:1) relationship between WSC and I daily courses which was found after applying a linear regression analysis. Practical usefulness of this finding for wind energy applications is straightforward, as merely using I values routinely collected at surface heights a WSC predicting model may be used to fairly estimate energy yield at WT hub height. A 2-year (2012-2013) dataset from the meteorological mast of Cabauw (Netherlands) was used, including 10-min records collected at heights of 10, 20, 40, and 80 m. Methods were trained over a 1-year period (2012) and then validated over an independent 1-year period (2013). WT hub heights of 40 and 80 m have been targeted for the extrapolation, being accomplished based on I observations at two surface levels: 10 and 20 m. As a result, good scores were returned by the proposed method over the most challenging height intervals: between 10 and 80 m, a 5% mean bias was achieved in extrapolated v values and at worst a 11.51% in calculated energy yield; between 20 and 80 m, extrapolated v values were biased by 2%, while energy output at worst by 6.62%.
The strict relationship between surface turbulence intensity and wind shear coefficient daily courses: a novel method to extrapolate wind resource to the turbine hub height
Giovanni Gualtieri
2015
Abstract
Based on power law, a novel method is proposed to extrapolate surface wind speed (v) to the wind turbine (WT) hub height, via prediction of the wind shear coefficient (WSC) daily course, by only using the surface turbulence intensity (I) daily course. Work's main outcome is a strict (almost 1:1) relationship between WSC and I daily courses which was found after applying a linear regression analysis. Practical usefulness of this finding for wind energy applications is straightforward, as merely using I values routinely collected at surface heights a WSC predicting model may be used to fairly estimate energy yield at WT hub height. A 2-year (2012-2013) dataset from the meteorological mast of Cabauw (Netherlands) was used, including 10-min records collected at heights of 10, 20, 40, and 80 m. Methods were trained over a 1-year period (2012) and then validated over an independent 1-year period (2013). WT hub heights of 40 and 80 m have been targeted for the extrapolation, being accomplished based on I observations at two surface levels: 10 and 20 m. As a result, good scores were returned by the proposed method over the most challenging height intervals: between 10 and 80 m, a 5% mean bias was achieved in extrapolated v values and at worst a 11.51% in calculated energy yield; between 20 and 80 m, extrapolated v values were biased by 2%, while energy output at worst by 6.62%.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


