Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6765809 | Renewable Energy | 2016 | 9 Pages |
Abstract
Reanalysis data are attractive for wind-power studies because they can offer wind speed data for large areas and long time periods and in locations where historical data are not available. However, reanalysis-predicted wind speeds can have significant uncertainties and biases relative to measured wind speeds. In this work we develop a model of the bias and uncertainty of CFS reanalysis wind speed than can be used to correct the data and identify sources of error. We find the CFS reanalysis data underestimate wind speeds at high elevations, at high measurement heights, and in unstable atmospheric conditions. For example, at a site with an elevation of 500Â m and hub height of 80Â m, a CFS reanalysis wind speed of 8Â m/s is 0.2Â m/s higher to 1.3Â m/s lower than the measured wind speed. We also find a seasonal bias that correlates with surface roughness length used by the reanalysis model during the spring season. The corrections we propose reduce the average bias of reanalysis wind speed extrapolated to hub height to nearly zero, an improvement of 0.3-0.9Â m/s. These corrections also reduce the RMS error by 0.1-0.4Â m/s, a small improvement compared to the uncorrected RMS errors of 1.5-2.4Â m/s.
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Stephen Rose, Jay Apt,