Matthew L. Aitken

Quantifying Wind Turbine Wake Characteristics from Scanning Remote Sensor Data

AbstractBecause 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, suffers from an unacceptable degree of uncertainty, largely because of a lack of adequate experimental data for model validation. Accordingly, nearly 100 h of wake measurements were collected with long-range Doppler lidar at the National Wind Technology Center at the National Renewable Energy Laboratory in the Turbine Wake and Inflow Characterization Study (TWICS). This study presents quantitative procedures for determining critical parameters from this extensive dataset—such as the velocity deficit, the size of the wake boundary, and the location of the wake centerline—and categorizes the results by ambient wind speed, turbulence, and atmospheric stability. Despite specific reference to lidar, the methodology is gene...

Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications

A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011), the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems, one vertically profiling and another operated over a variety of scanning modes, were utilized to obtain forcing for the simulations, and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of ...

Performance of a Wind-Profiling Lidar in the Region of Wind Turbine Rotor Disks

AbstractAs the wind energy sector continues to grow, so does the need for reliable vertical wind profiles in the assessment of wind resources and turbine performance. In situ instrumentation mounted on meteorological towers can rarely probe the atmosphere across the full span of modern turbine rotor disks, which typically extend from 40 to 120 m above the surface. However, by measuring the Doppler shift of laser light backscattered by particles in the atmosphere, remote sensing lidar is capable of estimating wind speeds and turbulence at several altitudes in this range and above. Consequently, lidar has proven a promising technology for both wind resource assessment and turbine response characterization. The aim of this study is to quantify data availability for a coherent detection wind-profiling lidar—namely, the Leosphere Windcube.To determine situations of suitable data return rates, a Windcube, collocated with a Vaisala CL31 ceilometer, was deployed as part of the Skywatch Observatory at the Universi...

Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model

Recently, an actuator disk parameterization was implemented in the Weather Research and Forecasting (WRF) Model for large eddy simulation (LES) of wind turbine wakes. To thoroughly verify this model, simulations of various types of turbines and atmospheric conditions must be evaluated against corresponding experimental data. In this work, numerical simulations are compared to nacelle-based scanning lidar measurements taken in stable atmospheric conditions during a field campaign conducted at a wind farm in the western United States. Using several wake characteristics—such as the velocity deficit, centerline location, and wake width—as metrics for model verification, the simulations show good agreement with the observations. Notable results include a high average velocity deficit, decreasing from 73% at a downwind distance x of 1.2 rotor diameters (D) to 25% at x = 6.6D, resulting from a low average wind speed and therefore high average turbine thrust coefficient. Moreover, the wake width expands from 1.4D...

Utility-Scale Wind Turbine Wake Characterization Using Nacelle-Based Long-Range Scanning Lidar

AbstractTo facilitate the optimization of turbine spacing at modern wind farms, computational simulations of wake effects must be validated through comparison with full-scale field measurements of wakes from utility-scale turbines operating in the real atmosphere. Scanning remote sensors are particularly well suited for this objective, as they can sample wind fields over large areas at high temporal and spatial resolutions. Although ground-based systems are useful, the vantage point from the nacelle is favorable in that scans can more consistently transect the central part of the wake. To the best of the authors’ knowledge, the work described here represents the first analysis in the published literature of a utility-scale wind turbine wake using nacelle-based long-range scanning lidar.The results presented are of a field experiment conducted in the fall of 2011 at a wind farm in the western United States, quantifying wake attributes such as the velocity deficit, centerline location, and wake width. Notab...