Date of Award

Spring 1-1-2014

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Physics

First Advisor

Michael H. Ritzwoller

Second Advisor

Julie K. Lundquist

Third Advisor

Robert Banta

Fourth Advisor

Judah Levine

Fifth Advisor

Dmitri Uzdensky

Abstract

Because of the dense arrays at most wind farms, the region of disturbed flow downstream of an individual turbine leads to reduced power production and increased structural loading for its leeward counterparts. Currently, wind farm wake modeling, and hence turbine layout optimization, suffer from an unacceptable degree of uncertainty, largely because of a lack of adequate experimental data for model verification. Accordingly, wake measurements were taken in two separate experiments, (1) using the ground-based High Resolution Doppler Lidar (HRDL) developed by the National Oceanic and Atmospheric Administration (NOAA) in the Turbine Wake and Inflow Characterization Study (TWICS) at the National Renewable Energy Laboratory (NREL), and (2) using nacelle-based long-range lidar at a wind farm in the western United States. The vantage point from the nacelle is favorable in that scans can more consistently transect the central part of the wake.

The work presented here outlines a set of quantitative procedures for determining critical parameters from these extensive datasets—such as the velocity deficit, the size of the wake boundary, and the location of the wake centerline—and the results are categorized by ambient wind speed, turbulence, and atmospheric stability. Despite specific reference to lidar, the methodology is general and can be applied to extract wake characteristics from other remote sensor datasets, as well as output from numerical simulations.

In an effort to help advance computational fluid dynamics (CFD) models of wind turbine wake dynamics, experimental results are compared to a large eddy simulation (LES) of a turbine operating in the stable boundary layer using the actuator disk parameterization in the Weather Research and Forecasting (WRF) Model. With the wake characteristics described above as metrics for model verification, the simulations show good agreement with the observations. Moreover, new features—namely rotor tilt and drag from the nacelle and tower—are added to the existing actuator disk framework in WRF. The inclusion of rotor tilt causes the vertical location of the wake center to shift upward, as confirmed by experimental measurements. Continued improvement to the actuator disk model in WRF will help lead to optimized turbine siting and controls at wind farms.

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