scholarly journals Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

2018 ◽  
Author(s):  
Jennifer Annoni ◽  
Paul Fleming ◽  
Andrew Scholbrock ◽  
Jason Roadman ◽  
Scott Dana ◽  
...  
Keyword(s):  
Wind Farm ◽  
Lidar Data ◽  
National Renewable Energy Laboratory ◽  
Atmospheric Conditions ◽  
Modeling Tools ◽  
Lidar Measurements ◽  
Utility Scale ◽  
The Impact ◽  
Turbine Wake ◽  
Good Agreement

Abstract. Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this campaign, the turbine was operated at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.

scholarly journals Analysis of control-oriented wake modeling tools using lidar field results

2018 ◽  
Vol 3 (2) ◽  
pp. 819-831 ◽  
Author(s):  
Jennifer Annoni ◽  
Paul Fleming ◽  
Andrew Scholbrock ◽  
Jason Roadman ◽  
Scott Dana ◽  
...  
Keyword(s):  
Lidar Data ◽  
Atmospheric Conditions ◽  
Modeling Tools ◽  
Technology Center ◽  
Lidar Measurements ◽  
Scanning Lidar ◽  
Utility Scale ◽  
Turbine Wake ◽  
Good Agreement ◽  
Plant Control

Abstract. The objective of this paper is to compare field data from a scanning lidar mounted on a turbine to control-oriented wind turbine wake models. The measurements were taken from the turbine nacelle looking downstream at the turbine wake. This field campaign was used to validate control-oriented tools used for wind plant control and optimization. The National Wind Technology Center in Golden, CO, conducted a demonstration of wake steering on a utility-scale turbine. In this campaign, the turbine was operated at various yaw misalignment set points, while a lidar mounted on the nacelle scanned five downstream distances. Primarily, this paper examines measurements taken at 2.35 diameters downstream of the turbine. The lidar measurements were combined with turbine data and measurements of the inflow made by a highly instrumented meteorological mast on-site. This paper presents a quantitative analysis of the lidar data compared to the control-oriented wake models used under different atmospheric conditions and turbine operation. These results show that good agreement is obtained between the lidar data and the models under these different conditions.

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

2014 ◽  
Vol 31 (7) ◽  
pp. 1529-1539 ◽  
Author(s):  
Matthew L. Aitken ◽  
Julie K. Lundquist
Keyword(s):  
Wind Turbine ◽  
Long Range ◽  
Wind Farm ◽  
Thrust Coefficient ◽  
Velocity Deficit ◽  
Scanning Lidar ◽  
Range Scanning ◽  
Utility Scale ◽  
Turbine Wake ◽  
Wind Turbine Wake

Abstract To 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. Notable findings include a high average velocity deficit, decreasing from 60% at a downwind distance x of 1.8 rotor diameters (D) to 40% at x = 6D, resulting from a low average wind speed and therefore a high average turbine thrust coefficient. Moreover, the wake width was measured to expand from 1.5D at x = 1.8D to 2.5D at x = 6D. Both the wake growth rate and the amplitude of wake meandering were observed to be greater for high ambient turbulence intensity and daytime conditions as compared to low turbulence and nocturnal conditions.

scholarly journals The Iowa Atmospheric Observatory: Revealing the Unique Boundary Layer Characteristics of a Wind Farm

2019 ◽  
Vol 23 (2) ◽  
pp. 1-27 ◽  
Author(s):  
Eugene S. Takle ◽  
Daniel A. Rajewski ◽  
Samantha L. Purdy
Keyword(s):  
Boundary Layer ◽  
Wind Farm ◽  
Agricultural Landscape ◽  
Potential Temperature ◽  
Wind Farms ◽  
Vertical Profiles ◽  
Atmospheric Conditions ◽  
Wide Range ◽  
Water Vapor Mixing Ratio ◽  
Utility Scale

Abstract The Iowa Atmospheric Observatory was established to better understand the unique microclimate characteristics of a wind farm. The facility consists of a pair of 120-m towers identically instrumented to observe basic landscape–atmosphere interactions in a highly managed agricultural landscape. The towers, one within and one outside of a utility-scale low-density-array wind farm, are equipped to measure vertical profiles of temperature, wind, moisture, and pressure and can host specialized sensors for a wide range of environmental conditions. Tower measurements during the 2016 growing season demonstrate the ability to distinguish microclimate differences created by single or multiple turbines from natural conditions over homogeneous agricultural fields. Microclimate differences between the two towers are reported as contrasts in normalized wind speed, normalized turbulence intensity, potential temperature, and water vapor mixing ratio. Differences are analyzed according to conditions of no wind farm influence (i.e., no wake) versus wind farm influence (i.e., waked flow) with distance downwind from a single wind turbine or a large group of turbines. Differences are also determined for more specific atmospheric conditions according to thermal stratification. Results demonstrate agreement with most, but not all, currently available numerical flow-field simulations of large wind farm arrays and of individual turbines. In particular, the well-documented higher nighttime surface temperature in wind farms is examined in vertical profiles that confirm this effect to be a “suppression of cooling” rather than a warming process. A summary is provided of how the wind farm boundary layer differs from the natural boundary layer derived from concurrent measurements over the summer of 2016.

scholarly journals Do Wind Turbines Pose Roll Hazards to Light Aircraft?

2018 ◽  
Author(s):  
Jessica M. Tomaszewski ◽  
Julie K. Lundquist ◽  
Matthew J. Churchfield ◽  
Patrick J. Moriarty
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
The United States ◽  
General Aviation ◽  
Open Spaces ◽  
Increased Risk ◽  
Large Eddy ◽  
Utility Scale ◽  
Turbine Wake ◽  
Small Aircraft

Abstract. Wind energy accounted for 5.6 % of all electricity generation in the United States in 2016. Much of this development has occurred in rural locations, where open spaces favorable for harnessing wind also serve general aviation airports. As such, nearly 40 % of all U.S. wind turbines exist within 10 km of a small airport. Wind turbines generate electricity by extracting momentum from the atmosphere, creating downwind wakes characterized by wind-speed deficits and increased turbulence. Recently, the concern that turbine wakes pose hazards for small aircraft has been used to limit wind farm development. Herein, we assess roll hazards to small aircraft using large-eddy simulations of a utility-scale turbine wake. Wind-generated rolling moments on hypothetical aircraft transecting the wake in stably and neutrally stratified conditions are calculated. In both cases, only 0.001 % of rolling moments experienced by hypothetical aircraft during down-wake and cross-wake transects lead to an increased risk of rolling.

scholarly journals Documenting Wind Speed and Power Deficits behind a Utility-Scale Wind Turbine

2013 ◽  
Vol 52 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Brian D. Hirth ◽  
John L. Schroeder
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Large Variability ◽  
Cost Of Energy ◽  
The Mean ◽  
Utility Scale ◽  
Turbine Wake

AbstractHigh-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.

scholarly journals Development of a LIDAR array to study and classify wakes at the U.S. Department of Energy (DOE)/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility

2018 ◽  
Vol 43 (1) ◽  
pp. 26-34
Author(s):  
Tassia Penha Pereira ◽  
Suhas Pol ◽  
Arquimedes Ruiz-Columbie ◽  
Carsten Westergaard
Keyword(s):  
Wind Farm ◽  
Direct Detection ◽  
Department Of Energy ◽  
Atmospheric Conditions ◽  
Validation Process ◽  
Statistical Characterization ◽  
Texas Tech University ◽  
Turbine Wake ◽  
Measurement Approach

Wind turbine wake has the wind speed deficit and the increased turbulent flow to the downstream turbines as signatures. Various experiments and simulations have been performed over the years to investigate the wake parameters; however, a statistical characterization of wake states is still to be uncovered. An innovative wake measurement approach that uses five ground-based Spidar Light Detection and Ranging (LIDAR) has been developed in partnership with Texas Tech University (TTU), Sandia National Laboratories, and Pentalum Technologies to develop, test, and validate a system and methodology that enables the capture of statistically significant wake dynamics in real atmospheric conditions. This article will discuss the potential of this new direct detection remote sensing equipment for studying the wake states as well as report the validation process of the LIDAR and the feasibility of continuing to pursue the primary purpose of the initiative.

Using the WRF Model in an Operational Streamflow Forecast System for the Jordan River

2011 ◽  
Vol 51 (2) ◽  
pp. 285-299 ◽  
Author(s):  
Amir Givati ◽  
Barry Lynn ◽  
Yubao Liu ◽  
Alon Rimmer
Keyword(s):  
High Resolution ◽  
Hydrological Modeling ◽  
Wrf Model ◽  
Assessment Process ◽  
Jordan River ◽  
Modeling Tools ◽  
Streamflow Forecast ◽  
Rain Gauges ◽  
The Impact ◽  
Good Agreement

AbstractThe Weather Research and Forecasting (WRF) model was employed to provide precipitation forecasts during the 2008/09 and 2009/10 winters (wet season) for Israel and the surrounding region where complex terrain dominates. The WRF precipitation prediction has been coupled with the Hydrological Model for Karst Environment (HYMKE) to forecast the upper Jordan River streamflow. The daily WRF precipitation forecasts were verified against the measurements from a dense network of rain gauges in northern and central Israel, and the simulation results using the high-resolution WRF indicated good agreement with the actual measurements. The daily precipitation amount calculated by WRF at rain gauges located in the upper parts of the Jordan River basin showed good agreement with the actual measurements. Numerical experiments were carried out to test the impact of the WRF model resolution and WRF microphysical schemes, to determine an optimal model configuration for this application. Because of orographic forcing in the region, it is necessary to run WRF with a 4–1.3-km grid increment and with sophisticated microphysical schemes that consider liquid water, ice, snow, and graupel to produce quality precipitation predictions. The hydrological modeling system that ingests the high-resolution WRF forecast precipitation produced good results and improved upon the operational streamflow forecast method for the Jordan River that is now in use. The modeling tools presented in this study are used to support the water-resource-assessment process and studies of seasonal hydroclimatic forecasting in this region.

scholarly journals Mechanisms of dynamic near-wake modulation of a utility-scale wind turbine

2021 ◽  
Vol 926 ◽  
Author(s):  
Aliza Abraham ◽  
Luis A. Martínez-Tossas ◽  
Jiarong Hong
Keyword(s):  
Wind Turbine ◽  
Time Scales ◽  
Time Scale ◽  
Wind Farm ◽  
Control Strategies ◽  
Dynamic Control ◽  
Wake Flow ◽  
Utility Scale ◽  
Turbine Wake ◽  
Wind Turbine Wake

The current study uses large eddy simulations to investigate the transient response of a utility-scale wind turbine wake to dynamic changes in atmospheric and operational conditions, as observed in previous field-scale measurements. Most wind turbine wake investigations assume quasi-steady conditions, but real wind turbines operate in a highly stochastic atmosphere, and their operation (e.g. blade pitch, yaw angle) changes constantly in response. Furthermore, dynamic control strategies have been recently proposed to optimize wind farm power generation and longevity. Therefore, improved understanding of dynamic wake behaviours is essential. First, changes in blade pitch are investigated and the wake expansion response is found to display hysteresis as a result of flow inertia. The time scales of the wake response to different pitch rates are quantified. Next, changes in wind direction with different time scales are explored. Under short time scales, the wake deflection is in the opposite direction of that observed under quasi-steady conditions. Finally, yaw changes are implemented at different rates, and the maximum inverse wake deflection and time scale are quantified, showing a clear dependence on yaw rate. To gain further physical understanding of the mechanism behind the inverse wake deflection, the streamwise vorticity in different parts of the wake is quantified. The results of this study provide guidance for the design of advanced wake flow control algorithms. The lag in wake response observed for both blade pitch and yaw changes shows that proposed dynamic control strategies must implement turbine operational changes with a time scale of the order of the rotor time scale or slower.

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