Evaluation of a semi-empirical model for predicting the wind energy resource relevant to small-scale wind turbines

S.M. Weekes and A.S. Tomlin

Renewable Energy, 2013, vol. 50, issue C, 280-288

Abstract: An existing semi-empirical model for estimating the wind energy resource relevant to small-scale wind turbines has been investigated by comparing its predictions to wind speed data collected from 38 UK sites located in a variety of terrains. A range of error metrics have been used to judge the success of the model in predicting the mean wind speed and wind power density in each terrain type over five years. Averaged across all sites, the mean absolute and percentage errors were found to be 0.63 ms−1 and 18% with respect to the predicted mean wind speed and 23 wm−2 and 70% with respect to the predicted wind power density. The effect of tightening the definition of the canopy height, increasing the size of the fetch and incorporating directionally dependent regional roughness parameters, on the accuracy of the predictions was also investigated. It was found that by incorporating these factors into a modified model, the mean absolute and percentage errors could be reduced to 0.52 ms−1 and 16% with respect to the predicted mean wind speed. With the addition of an optimised Weibull shape factor, the average errors in the predicted wind power density were reduced to 20 wm−2 and 63%. The results indicate that while simple modifications can improve accuracy, these models should be applied with a degree of caution when attempting to make predictions of the viability of a proposed installation. Ideally, such models should be supplemented by other approaches in order to increase the confidence in the predicted wind resource.

Keywords: Small-scale wind energy; Wind resource assessment; Weibull shape factor (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:50:y:2013:i:c:p:280-288

DOI: 10.1016/j.renene.2012.06.053

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