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Title: IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering

Journal Article · · Journal of Physics. Conference Series
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [2];  [3]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States). National Wind Technology Center
  2. Flensburg Univ. of Applied Sciences, Flensburg (Germany)
  3. Technical Univ. of Denmark, Roskilde (Denmark). Dept. of Wind Energy
+ Show Author Affiliations

Lidar-assisted control is a promising technology for reducing the levelized cost of energy from wind turbines, but quantifying its impact at the overall system level requires sophisticated systems engineering analysis and optimization frameworks. The joint workshop on Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering was held by the International Energy Agency Wind Task 32 (Lidar) and Task 37 (Systems Engineering) in October 2019 to address this challenge. This paper summarizes the outcome of the workshop and presents a road map for further research. The most promising applications of lidar-assisted control identified at the workshop and discussed here include 1) increasing annual energy production, 2) decreasing capital expenditure costs by reducing design loads, 3) extending turbine lifetime by reducing operating loads, and 4) enabling wind turbine class upgrades. For each application, we review the state of the art and highlight remaining research needs. Finally, we discuss strategies for addressing these research needs by conducting high-fidelity systems engineering optimizations.

Research Organization:
National Renewable Energy Lab. (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:
1665800
Report Number(s):
NREL/JA-5000-76869; MainId:10513; UUID:da2cef7d-5350-4b3a-9b80-0d70c5258738; MainAdminID:15183
Journal Information:
Journal of Physics. Conference Series, Vol. 1618; ISSN 1742-6588
Publisher:
IOP PublishingCopyright Statement
Country of Publication:
United States
Language:
English

References (9)

Wind direction estimation using SCADA data with consensus-based optimization journal January 2019
Optimizing Lidars for Wind Turbine Control Applications—Results from the IEA Wind Task 32 Workshop journal June 2018
Field-test results using a nacelle-mounted lidar for improving wind turbine power capture by reducing yaw misalignment journal June 2014
Combined preliminary–detailed design of wind turbines journal January 2016
Integration of multiple passive load mitigation technologies by automated design optimization-The case study of a medium-size onshore wind turbine journal September 2018
Integrated aero-structural optimization of wind turbines journal November 2015
Determination of optimal wind turbine alignment into the wind and detection of alignment changes with SCADA data journal January 2018
Turbulent Extreme Event Simulations for Lidar-Assisted Wind Turbine Control journal September 2016
Wind turbine control applications of turbine-mounted LIDAR journal December 2014

Figures / Tables (3)

Figure 1(p. 3)figure Figure 1
Table 1(p. 8)table Table 1
Figure 2(p. 9)figure Figure 2

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Related Subjects

17 WIND ENERGY
IEA Wind
lidar-assisted control
systems engineering
wind turbine optimization