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

Abstract

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.

Authors:
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
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
OSTI Identifier:
1665800
Report Number(s):
NREL/JA-5000-76869
Journal ID: ISSN 1742-6588; MainId:10513;UUID:da2cef7d-5350-4b3a-9b80-0d70c5258738;MainAdminID:15183
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Physics. Conference Series
Additional Journal Information:
Journal Volume: 1618; Journal ID: ISSN 1742-6588
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English
Subject:
49 EE - Wind and Water Power Program - Wind (EE-4W); IEA Wind; lidar-assisted control; systems engineering; wind turbine optimization

Citation Formats

Simley, Eric, Bortolotti, Pietro, Scholbrock, Andrew, Schlipf, David, and Dykes, Katherine. IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering. United States: N. p., 2020. Web. doi:10.1088/1742-6596/1618/4/042029.
Simley, Eric, Bortolotti, Pietro, Scholbrock, Andrew, Schlipf, David, & Dykes, Katherine. IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering. United States. doi:10.1088/1742-6596/1618/4/042029.
Simley, Eric, Bortolotti, Pietro, Scholbrock, Andrew, Schlipf, David, and Dykes, Katherine. Tue . "IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering". United States. doi:10.1088/1742-6596/1618/4/042029. https://www.osti.gov/servlets/purl/1665800.
@article{osti_1665800,
title = {IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering},
author = {Simley, Eric and Bortolotti, Pietro and Scholbrock, Andrew and Schlipf, David and Dykes, Katherine},
abstractNote = {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.},
doi = {10.1088/1742-6596/1618/4/042029},
journal = {Journal of Physics. Conference Series},
issn = {1742-6588},
number = ,
volume = 1618,
place = {United States},
year = {2020},
month = {9}
}

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Works referenced in this record:

Wind direction estimation using SCADA data with consensus-based optimization
journal, January 2019

  • Annoni, Jennifer; Bay, Christopher; Johnson, Kathryn
  • Wind Energy Science, Vol. 4, Issue 2
  • DOI: 10.5194/wes-4-355-2019

Optimizing Lidars for Wind Turbine Control Applications—Results from the IEA Wind Task 32 Workshop
journal, June 2018

  • Simley, Eric; Fürst, Holger; Haizmann, Florian
  • Remote Sensing, Vol. 10, Issue 6
  • DOI: 10.3390/rs10060863

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

  • Bortolotti, Pietro; Bottasso, Carlo L.; Croce, Alessandro
  • Wind Energy Science, Vol. 1, Issue 1
  • DOI: 10.5194/wes-1-71-2016

Integration of multiple passive load mitigation technologies by automated design optimization-The case study of a medium-size onshore wind turbine
journal, September 2018

  • Bortolotti, Pietro; Bottasso, Carlo L.; Croce, Alessandro
  • Wind Energy, Vol. 22, Issue 1
  • DOI: 10.1002/we.2270

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