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:

Verstraeten, Timothy ^[1]; Nowe, Ann ^[1]; Keller, Jonathan A  ^[2];

• Search DOE PAGES for author "Keller, Jonathan A"
• Search DOE PAGES for ORCID "0000-0001-7724-3885"

Guo, Yi  ^[2];

• Search DOE PAGES for author "Guo, Yi"
• Search DOE PAGES for ORCID "0000-0002-6413-947X"

Sheng, Shuangwen  ^[2];

• Search DOE PAGES for author "Sheng, Shuangwen"
• Search DOE PAGES for ORCID "0000-0003-0134-0907"

Helsen, Jan ^[3]

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+ Show Author Affiliations

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:

Mon Apr 22 00:00:00 EDT 2019

Research Org.:

National Renewable Energy Laboratory (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