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Title: Wind Power Curve Modeling Using Statistical Models: An Investigation of Atmospheric Input Variables at a Flat and Complex Terrain Wind Farm

Abstract

The goal of our FY15 project was to explore the use of statistical models and high-resolution atmospheric input data to develop more accurate prediction models for turbine power generation. We modeled power for two operational wind farms in two regions of the country. The first site is a 235 MW wind farm in Northern Oklahoma with 140 GE 1.68 turbines. Our second site is a 38 MW wind farm in the Altamont Pass Region of Northern California with 38 Mitsubishi 1 MW turbines. The farms are very different in topography, climatology, and turbine technology; however, both occupy high wind resource areas in the U.S. and are representative of typical wind farms found in their respective areas.

Authors:
 [1];  [1];  [2];  [3];  [4];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Enel Green Power North America, Andover, MA (United States)
  3. Infigen Energy, Dallas, TX (United States)
  4. Univ. of Oklahoma, Norman, OK (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1223839
Report Number(s):
LLNL-TR-677602
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY

Citation Formats

Wharton, S., Bulaevskaya, V., Irons, Z., Qualley, G., Newman, J. F., and Miller, W. O. Wind Power Curve Modeling Using Statistical Models: An Investigation of Atmospheric Input Variables at a Flat and Complex Terrain Wind Farm. United States: N. p., 2015. Web. doi:10.2172/1223839.
Wharton, S., Bulaevskaya, V., Irons, Z., Qualley, G., Newman, J. F., & Miller, W. O. Wind Power Curve Modeling Using Statistical Models: An Investigation of Atmospheric Input Variables at a Flat and Complex Terrain Wind Farm. United States. doi:10.2172/1223839.
Wharton, S., Bulaevskaya, V., Irons, Z., Qualley, G., Newman, J. F., and Miller, W. O. Mon . "Wind Power Curve Modeling Using Statistical Models: An Investigation of Atmospheric Input Variables at a Flat and Complex Terrain Wind Farm". United States. doi:10.2172/1223839. https://www.osti.gov/servlets/purl/1223839.
@article{osti_1223839,
title = {Wind Power Curve Modeling Using Statistical Models: An Investigation of Atmospheric Input Variables at a Flat and Complex Terrain Wind Farm},
author = {Wharton, S. and Bulaevskaya, V. and Irons, Z. and Qualley, G. and Newman, J. F. and Miller, W. O.},
abstractNote = {The goal of our FY15 project was to explore the use of statistical models and high-resolution atmospheric input data to develop more accurate prediction models for turbine power generation. We modeled power for two operational wind farms in two regions of the country. The first site is a 235 MW wind farm in Northern Oklahoma with 140 GE 1.68 turbines. Our second site is a 38 MW wind farm in the Altamont Pass Region of Northern California with 38 Mitsubishi 1 MW turbines. The farms are very different in topography, climatology, and turbine technology; however, both occupy high wind resource areas in the U.S. and are representative of typical wind farms found in their respective areas.},
doi = {10.2172/1223839},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {9}
}

Technical Report:

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