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

Journal Article · · Wind Energy Science (Online)
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  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Ecole Polytechnique Federale Lausanne (Switzlerland)
  3. Univ. of Stuttgart, Stuttgart (Germany)
+ Show Author Affiliations

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. Furthermore, these results show that good agreement is obtained between the lidar data and the models under these different conditions.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1481841
Report Number(s):
NREL/JA--5000-72767
Journal Information:
Wind Energy Science (Online), Journal Name: Wind Energy Science (Online) Journal Issue: 2 Vol. 3; ISSN 2366-7451
Publisher:
European Wind Energy Association - CopernicusCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (13)

Observability of the ambient conditions in model‐based estimation for wind farm control: A focus on static models journal March 2020
Uncertainty Quantification of Wind Turbine Wakes Under Random Wind Conditions conference November 2019
Fast Processing Intelligent Wind Farm Controller for Production Maximisation journal February 2019
The helix approach: using dynamic individual pitch control to enhance wake mixing in wind farms preprint January 2019
Optimal closed-loop wake steering – Part 1: Conventionally neutral atmospheric boundary layer conditions journal January 2020
Optimizing wind farm control through wake steering using surrogate models based on high-fidelity simulations journal January 2020
Wake steering optimization under uncertainty journal January 2020
Modeling of the atmospheric boundary layer under stability stratification for wind turbine wake production journal October 2019
Initial Results From a Field Campaign of Wake Steering Applied at a Commercial Wind Farm: Part 1 posted_content February 2019
A simulation study demonstrating the importance of large-scale trailing vortices in wake steering journal January 2018
The aerodynamics of the curled wake: a simplified model in view of flow control journal January 2019
Initial results from a field campaign of wake steering applied at a commercial wind farm – Part 1 journal January 2019
Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm journal January 2019

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Related Subjects

17 WIND ENERGY
control systems
lidar
wakes
wind energy
wind farm controls