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Title: Fleetwide data-enabled reliability improvement of wind turbines

Abstract

Wind farms are an indispensable driver toward renewable and nonpolluting energy resources. However, as ideal sites are limited, placement in remote and challenging locations results in higher logistics costs and lower average wind speeds. Therefore, it is critical to increase the reliability of the turbines to reduce maintenance costs. Robust implementation requires a thorough understanding of the loads subject to the turbine's control. Yet, such dynamically changing multidimensional loads are uncommon with other machinery, and generally underresearched. Therefore, a multitiered approach is proposed to investigate the load spectrum occurring in wind farms. Our approach relies on both fundamental research using controllable test rigs, as well as analyses of real-world loading conditions in high-frequency supervisory control and data acquisition data. A method is introduced to detect operational zones in wind farm data and link them with load distributions. Additionally, while focused research further investigates the load spectrum, a method is proposed that continuously optimizes the farm's control protocols without the need to fully understand the loads that occur. A case of gearbox failure is investigated based on a vast body of past experiments and suspect loads are identified. Starting from this evidence on the cause and effects of dynamic loads, themore » potential of our methods is shown by analyzing real-world farm loading conditions on a steady-state case of wake and developing a preventive row-based control protocol for a case of cascading emergency brakes induced by a storm.« less

Authors:
 [1];  [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2];  [3]
  1. Vrije Univ., Brussels (Belgium)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Vrije Univ., Brussels (Belgium); OWI-Lab, Geverlee (Belgium)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1510419
Alternate Identifier(s):
OSTI ID: 1637090
Report Number(s):
NREL/JA-5000-73245
Journal ID: ISSN 1364-0321
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Renewable and Sustainable Energy Reviews
Additional Journal Information:
Journal Volume: 109; Journal Issue: C; Journal ID: ISSN 1364-0321
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; wind turbine reliability; data-enabled load analysis; failure avoidance

Citation Formats

Verstraeten, Timothy, Nowe, Ann, Keller, Jonathan A, Guo, Yi, Sheng, Shuangwen, and Helsen, Jan. Fleetwide data-enabled reliability improvement of wind turbines. United States: N. p., 2019. Web. doi:10.1016/j.rser.2019.03.019.
Verstraeten, Timothy, Nowe, Ann, Keller, Jonathan A, Guo, Yi, Sheng, Shuangwen, & Helsen, Jan. Fleetwide data-enabled reliability improvement of wind turbines. United States. https://doi.org/10.1016/j.rser.2019.03.019
Verstraeten, Timothy, Nowe, Ann, Keller, Jonathan A, Guo, Yi, Sheng, Shuangwen, and Helsen, Jan. Mon . "Fleetwide data-enabled reliability improvement of wind turbines". United States. https://doi.org/10.1016/j.rser.2019.03.019. https://www.osti.gov/servlets/purl/1510419.
@article{osti_1510419,
title = {Fleetwide data-enabled reliability improvement of wind turbines},
author = {Verstraeten, Timothy and Nowe, Ann and Keller, Jonathan A and Guo, Yi and Sheng, Shuangwen and Helsen, Jan},
abstractNote = {Wind farms are an indispensable driver toward renewable and nonpolluting energy resources. However, as ideal sites are limited, placement in remote and challenging locations results in higher logistics costs and lower average wind speeds. Therefore, it is critical to increase the reliability of the turbines to reduce maintenance costs. Robust implementation requires a thorough understanding of the loads subject to the turbine's control. Yet, such dynamically changing multidimensional loads are uncommon with other machinery, and generally underresearched. Therefore, a multitiered approach is proposed to investigate the load spectrum occurring in wind farms. Our approach relies on both fundamental research using controllable test rigs, as well as analyses of real-world loading conditions in high-frequency supervisory control and data acquisition data. A method is introduced to detect operational zones in wind farm data and link them with load distributions. Additionally, while focused research further investigates the load spectrum, a method is proposed that continuously optimizes the farm's control protocols without the need to fully understand the loads that occur. A case of gearbox failure is investigated based on a vast body of past experiments and suspect loads are identified. Starting from this evidence on the cause and effects of dynamic loads, the potential of our methods is shown by analyzing real-world farm loading conditions on a steady-state case of wake and developing a preventive row-based control protocol for a case of cascading emergency brakes induced by a storm.},
doi = {10.1016/j.rser.2019.03.019},
journal = {Renewable and Sustainable Energy Reviews},
number = C,
volume = 109,
place = {United States},
year = {2019},
month = {4}
}

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