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Insensitivity to propagation timing in a preview-enabled wind turbine control experiment

Journal Article · · Frontiers in Mechanical Engineering
 [1];  [2];  [3];  [2];  [4];  [2];  [5]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. University of Oldenburg (Germany)
  3. Univ. of Colorado, Boulder, CO (United States)
  4. Univ. of Colorado, Boulder, CO (United States); Munich University of Applied Science (Germany)
  5. Univ. of Colorado, Boulder, CO (United States); Renewable and Sustainable Energy Inst. (RASEI), Boulder, CO (United States)
+ Show Author Affiliations
Lidar scanners are capable of taking measurements of a wind field upstream of a wind turbine. The wind turbine controller can use these measurements as a “preview” of future disturbances impacting the turbine. Such preview-enabled (or feedforward) controllers show superior performance to standard wind turbine control configurations based purely on a feedback architecture. To capitalize on the performance improvements that preview wind measurements can provide, feedforward control actions should be timed to coincide with the arrival of the wind field at the wind turbine location. However, the time of propagation of the wind field between the lidar measurement location and the wind turbine is not perfectly known. Moreover, the best time to take feedforward control action may not perfectly coincide with the true arrival time of the wind disturbance. This contribution presents results from an experiment where preview-enabled model predictive control was deployed on a fully-actuated, scaled model wind turbine operating in a wind tunnel testbed. In the study, we investigate the sensitivity of the controller performance to the assumed propagation delay using a range of wind input sequences. We find that the preview-enabled controller outperforms the feedback only case across a wide range of assumed propagation delays, demonstrating a level of robustness to the time alignment of the incoming disturbances.
Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1975544
Report Number(s):
NREL/JA-5000-86037; MainId:86810; UUID:aee3446a-7831-4fda-9a3d-70237db4e6b4; MainAdminID:69474
Journal Information:
Frontiers in Mechanical Engineering, Journal Name: Frontiers in Mechanical Engineering Vol. 9; ISSN 2297-3079
Publisher:
Frontiers Research FoundationCopyright Statement
Country of Publication:
United States
Language:
English

References (12)

Nonparametric Statistics for Non-Statisticians: A Step‐by‐Step Approach book January 2009
Wind Energy Handbook book May 2011
Analysis of light detection and ranging wind speed measurements for wind turbine control: Analysis of LIDAR measurements journal February 2013
Predictive control of an experimental wind turbine using preview wind speed measurements journal January 2014
The upstream flow of a wind turbine: blockage effect journal January 2011
Exploring the capabilities of active grids journal May 2021
Characterization of wind velocities in the upstream induction zone of a wind turbine using scanning continuous-wave lidars journal January 2016
Scaled wind turbine setup in a turbulent wind tunnel journal October 2018
Experimental Testing of a Preview-Enabled Model Predictive Controller for Blade Pitch Control of Wind Turbines journal March 2022
Definition of a 5-MW Reference Wind Turbine for Offshore System Development report February 2009
Optimizing Lidars for Wind Turbine Control Applications—Results from the IEA Wind Task 32 Workshop journal June 2018
A reference open-source controller for fixed and floating offshore wind turbines journal January 2022

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Related Subjects

17 WIND ENERGY
disturbance measurement
disturbance preview
feedforward control
lidar
model predictive control
scaled model experiment
wind advection
wind tunnel