Application of bias corrections to improve hub-height ensemble wind forecasts over the Tehachapi Wind Resource Area

Shu-Hua Chen, Shu-Chih Yang, Chih-Ying Chen, C.P. van Dam, Aubryn Cooperman, Henry Shiu, Clinton MacDonald and John Zack

Renewable Energy, 2019, vol. 140, issue C, 281-291

Abstract: This study demonstrates improvements in ensemble wind forecasts at hub height due to bias correction strategies and their impact on wind energy forecasts at the Alta II wind farm in southern California. The ensemble consists of twenty members that differ in physics schemes used. Ensemble wind forecasts are produced for three months. Hub-height sodar wind observations are used to evaluate forecast performance. Time-dependent bias correction (TBC) and probability bias correction (PBC) are proposed to calibrate hub-height ensemble wind forecasts.

Keywords: Wind energy; Wind forecast; Probability forecast; Model bias and bias correction (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:140:y:2019:i:c:p:281-291

DOI: 10.1016/j.renene.2019.03.043

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