Predicting the response of wind farms to changing flow conditions is necessary for optimal design and operation. In this work, simulation and analysis of a frontal passage through a utility scale wind farm is achieved for the first time using a seamless multi-scale modeling approach. A generalized actuator disk (GAD) wind turbine model is used to represent turbine–flow interaction, and results are compared to novel radar observations during the frontal passage. The Weather Research and Forecasting (WRF) model is employed with a nested grid setup that allows for coupling between multi-scale atmospheric conditions and turbine response. Starting with mesoscale forcing, the atmosphere is dynamically downscaled to the region of interest, where the interaction between turbulent flows and individual wind turbines is simulated with 10 m grid spacing. Several improvements are made to the GAD model to mimic realistic turbine operation, including a yawing capability and a power output calculation. Ultimately, the model is able to capture both the dynamics of the frontal passage and the turbine response; predictions show good agreement with observed background velocity, turbine wake structure, and power output after accounting for a phase shift in the mesoscale forcing. This study demonstrates the utility of the WRF-GAD model framework for simulating wind farm performance under complex atmospheric conditions.

Observations of the wake generated by a single utility-scale turbine and collected by the Texas Tech University Ka-band mobile research radars on 27 October 2011 are introduced. Remotely sensed turbine wake observations using lidar technology have proven effective; however, the presented radar capabilities provide a larger observational footprint and greater along-beam resolution than current scanning lidar systems. Plan-position indicator and range–height indicator scanning techniques are utilized to produce various wake analyses. Preliminary analyses confirm radial velocity and wind speed deficits immediately downwind of the turbine hub to be on the order of 50%. This introduction lays the groundwork for more in-depth analyses of wake structure and evolution using the Texas Tech University Ka-band radar systems, including wake meandering and wake-to-wake interaction in large wind park deployments.

The American WAKE ExperimeNt (AWAKEN) is a multi-institutional field campaign focused on gathering critical observations of wind farm–atmosphere interactions. These interactions are responsible for a large portion of the uncertainty in wind plant modeling tools that are used to represent wind plant performance both prior to construction and during operation and can negatively impact wind energy profitability. The AWAKEN field campaign will provide data for validation, ultimately improving modeling and lowering these uncertainties. The field campaign is designed to address seven testable hypotheses through the analysis of the observations collected by numerous instruments at 13 ground-based locations and on five wind turbines. The location of the field campaign in Northern Oklahoma was chosen to leverage existing observational facilities operated by the U.S. Department of Energy Atmospheric Radiation Measurement program in close proximity to five operating wind plants. The vast majority of the observations from the experiment are publicly available to researchers and industry members worldwide, which the authors hope will advance the state of the science for wind plants and lead to lower cost and increased reliability of wind energy systems.

High-spatial-and-temporal-resolution radial velocity measurements surrounding a single utility-scale wind turbine were collected using the Texas Tech University Ka-band mobile research radars. The measurements were synthesized to construct the first known dual-Doppler analyses of the mean structure and variability of a single turbine wake. The observations revealed a wake length that subjectively exceeded 20 rotor diameters, which far exceeds the typically employed turbine spacing of 7–10 rotor diameters. The mean horizontal wind speed deficits found within the turbine wake region relative to the free streamflow were related to potential reductions in the available power for a downwind turbine. Mean wind speed reductions of 17.4% (14.8%) were found at 7 (10) rotor diameters downwind, corresponding to a potential power output reduction of 43.6% (38.2%). The wind speed deficits found within the wake also exhibit large variability over short time intervals; this variability would have an appreciable impact on the inflow of a downstream turbine. The full understanding and application of these newly collected data have the potential to alter current wind-farm design and layout practices and to affect the cost of energy.

The structure of the coastal internal boundary layer (IBL) during a landfalling hurricane has important ramifications on operational forecasting, structural design, and poststorm damage assessment. Despite these important issues, the mean IBL structure at the coastline during landfall is poorly understood. Knowledge of the vertical kinematic structure within tropical cyclones over water has improved greatly through aircraft reconnaissance missions and the advent of GPS dropsondes and stepped frequency microwave radiometers. Unfortunately, reconnaissance and research aircraft are limited to overwater missions, resulting in a poor understanding of vertical kinematic structure near the coastal interface, where changes in IBL structure are expected due to changes in surface roughness. Composite single- and dual-Doppler radar observations collected by the Shared Mobile Atmospheric Research and Teaching Radars during the landfall of Hurricane Frances (2004) are presented. Data analyses from the Cape Canaveral, Florida, region reveal a pronounced IBL throughout the data collection period. As a result, significant variability in the analyzed wind speed and direction are found across and near the coastal interface. IBL height is found to be suppressed when compared to an accepted empirical growth model, while multiple abrupt roughness transitions associated with the Cape Canaveral region contribute to a complex mean IBL structure.

A new Doppler radar prototype has been developed and deployed at Texas Tech University with a focus on enhancing the technologies' capability to contribute to wind plant relevant complex flow measurements. In particular, improvements in data availability, total data coverage, and autonomous operation were targeted to enable contributions to a wider range of wind energy applications. Doppler radar offers rapid scan speeds, extended maximum range and excellent along-beam range resolution allowing for the simultaneous measurement of various wind phenomena ranging from regional and wind plant scales to inflow and wake flow assessment for an individual turbine. Data examples and performance improvements relative to a previous edition of the technology are presented, including insights into the influence of diurnal atmospheric stability evolution of wind structure and system performance.