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%.

Copyright Owner

Renee Amber Walton

Language

en

File Format

application/pdf

File Size

54 pages

Included in

Meteorology Commons

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