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Title: Wind Power Curve Modeling in Simple and Complex Terrain

Our previous work on wind power curve modeling using statistical models focused on a location with a moderately complex terrain in the Altamont Pass region in northern California (CA). The work described here is the follow-up to that work, but at a location with a simple terrain in northern Oklahoma (OK). The goal of the present analysis was to determine the gain in predictive ability afforded by adding information beyond the hub-height wind speed, such as wind speeds at other heights, as well as other atmospheric variables, to the power prediction model at this new location and compare the results to those obtained at the CA site in the previous study. While we reach some of the same conclusions at both sites, many results reported for the CA site do not hold at the OK site. In particular, using the entire vertical profile of wind speeds improves the accuracy of wind power prediction relative to using the hub-height wind speed alone at both sites. However, in contrast to the CA site, the rotor equivalent wind speed (REWS) performs almost as well as the entire profile at the OK site. Another difference is that at the CA site, adding wind veermore » as a predictor significantly improved the power prediction accuracy. The same was true for that site when air density was added to the model separately instead of using the standard air density adjustment. At the OK site, these additional variables result in no significant benefit for the prediction accuracy.« less
Authors:
 [1] ;  [1] ;  [2] ;  [3]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Enel Green Power North America, Andover, MA (United States)
  3. Pentalum, Colleyville, TX (United States)
Publication Date:
OSTI Identifier:
1183543
Report Number(s):
LLNL-TR--667088
DOE Contract Number:
AC52-07NA27344
Resource Type:
Technical Report
Research Org:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING, POLICY AND ECONOMY; 17 WIND ENERGY