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, John Zack

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

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. The root mean square errors (RMSEs) and biases of forecasted hub-height winds are significantly reduced using both bias correction methods. RMSEs were reduced by 20% and 15% for TBC and PBC, respectively. When evaluating forecast performance from a reliability perspective, PBC better corrects both high and low forecast probabilities for high-wind thresholds. The penalty associated with deviation of the wind energy forecasts from observed values is reduced by 8.7% and 8.0% for TBC and PBC, respectively. It is notable that PBC produces a greater penalty reduction during the high wind bias forecast period (6 p.m.–8 a.m. local standard time); during this time period, PBC reduces the penalty by 25.8% while TBC reduces it by just 19.2%.

Original languageEnglish
Pages (from-to)281-291
Number of pages11
JournalRenewable Energy
Volume140
DOIs
StatePublished - Sep 2019

Keywords

  • Model bias and bias correction
  • Probability forecast
  • Wind energy
  • Wind forecast

Fingerprint

Dive into the research topics of 'Application of bias corrections to improve hub-height ensemble wind forecasts over the Tehachapi Wind Resource Area'. Together they form a unique fingerprint.

Cite this