Degree Type
Thesis
Date of Award
2015
Degree Name
Master of Science
Department
Geological and Atmospheric Sciences
First Advisor
Eugene S. Takle
Second Advisor
William A. Gallus Jr.
Abstract
Day-ahead bids of wind farm power production depend greatly on the accuracy of wind speed forecasts. Forecasts can be improved by expanding knowledge of the wind characteristics across the wind turbine rotor layer (40 - 120 m) and examining wind direction forecasts, as errors in these forecasts can lead to missed effects of wind turbine wakes. Several high shear events with a change in wind speed of up to 15 m s-1 and changes in wind direction up to 30° between 50 and 200 m were observed across an Iowa tall tower network. The strength of these events could lead to damage of wind turbine components and therefore are important to forecast accurately. A six member Weather Research and Forecasting ensemble forecast was developed to evaluate the ability of the model to forecast wind speed, wind direction, wind shear, and stability at several levels across the rotor layer. Four bias correction methods were tested for each parameter to determine the best forecast method. After correction, wind speed forecasts were improved by up to 19%.
DOI
https://doi.org/10.31274/etd-180810-3986
Copyright Owner
Renee Amber Walton
Copyright Date
2015
Language
en
File Format
application/pdf
File Size
54 pages
Recommended Citation
Walton, Renee Amber, "Strong wind shear events and improved numerical prediction of the wind turbine rotor layer in an Iowa tall tower network" (2015). Graduate Theses and Dissertations. 14435.
https://lib.dr.iastate.edu/etd/14435
