Quantifying sources of uncertainty in reanalysis derived wind speed

RENEWABLE ENERGY

卷:94

Article

Rose, Stephen^1,3  Apt, Jay^1,2 

[1] Carnegie Mellon Univ, Tepper Sch Business, Pittsburgh, PA 15213 USA

[2] Carnegie Mellon Univ, Dept Engn & Publ Policy, Pittsburgh, PA 15213 USA

[3] Univ Minnesota, Humphrey Sch Publ Affairs, Minneapolis, MN USA

关键词: CFS reanalysis;    Wind integration;    Linear mixed-effect model;   

DOI  :  10.1016/j.renene.2016.03.028

来源: Elsevier

【 摘 要 】

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 500 m and hub height of 80 m, a CFS reanalysis wind speed of 8 m/s is 0.2 mis higher to 13 mis 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 03-0.9 mis. These corrections also reduce the RMS error by 0.1-0.4 m/s, a small improvement compared to the uncorrected RMS errors of 1.5-2.4 m/s. (C) 2016 Elsevier Ltd. All rights reserved.

【 授权许可】

Free