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Title: Improved Wind Turbine Drivetrain Reliability using a Combined Experimental, Computational, and Analytical Approach (Presentation)

Abstract

Nontorque loads induced by the wind turbine rotor overhang weight and aerodynamic forces can greatly affect drivetrain loads and responses. If not addressed properly, these loads can result in a decrease in gearbox component life. This work uses analytical modeling, computational modeling, and experimental data to evaluate a unique drivetrain design that minimize the effects of nontorque loads on gearbox reliability: the Pure Torque drivetrain developed by Alstom. The drivetrain has a hub-support configuration that transmits nontorque loads directly into the tower rather than through the gearbox as in other design approaches. An analytical model of Alstom's Pure Torque drivetrain provides insight into the relationships among turbine component weights, aerodynamic forces, and the resulting drivetrain loads. Main shaft bending loads are orders of magnitude lower than the rated torque and are hardly affected by wind speed and turbine operations.

Authors:
; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1166666
Report Number(s):
NREL/PR-5000-62679
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the ASME 2014 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, 17-20 August 2014, Buffalo, New York; Related Information: NREL (National Renewable Energy Laboratory)
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; 97 MATHEMATICS AND COMPUTING; NONTORQUE LOADS; WIND TURBINE DRIVETRAIN; GEARBOX; MODELING; NREL

Citation Formats

Guo, Yi, Bergua, R., van Dam, J., Jove, J., and Campbell, J.. Improved Wind Turbine Drivetrain Reliability using a Combined Experimental, Computational, and Analytical Approach (Presentation). United States: N. p., 2014. Web.
Guo, Yi, Bergua, R., van Dam, J., Jove, J., & Campbell, J.. Improved Wind Turbine Drivetrain Reliability using a Combined Experimental, Computational, and Analytical Approach (Presentation). United States.
Guo, Yi, Bergua, R., van Dam, J., Jove, J., and Campbell, J.. Fri . "Improved Wind Turbine Drivetrain Reliability using a Combined Experimental, Computational, and Analytical Approach (Presentation)". United States. doi:. https://www.osti.gov/servlets/purl/1166666.
@article{osti_1166666,
title = {Improved Wind Turbine Drivetrain Reliability using a Combined Experimental, Computational, and Analytical Approach (Presentation)},
author = {Guo, Yi and Bergua, R. and van Dam, J. and Jove, J. and Campbell, J.},
abstractNote = {Nontorque loads induced by the wind turbine rotor overhang weight and aerodynamic forces can greatly affect drivetrain loads and responses. If not addressed properly, these loads can result in a decrease in gearbox component life. This work uses analytical modeling, computational modeling, and experimental data to evaluate a unique drivetrain design that minimize the effects of nontorque loads on gearbox reliability: the Pure Torque drivetrain developed by Alstom. The drivetrain has a hub-support configuration that transmits nontorque loads directly into the tower rather than through the gearbox as in other design approaches. An analytical model of Alstom's Pure Torque drivetrain provides insight into the relationships among turbine component weights, aerodynamic forces, and the resulting drivetrain loads. Main shaft bending loads are orders of magnitude lower than the rated torque and are hardly affected by wind speed and turbine operations.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Aug 01 00:00:00 EDT 2014},
month = {Fri Aug 01 00:00:00 EDT 2014}
}

Conference:
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  • Nontorque loads induced by the wind turbine rotor overhang weight and aerodynamic forces can greatly affect drivetrain loads and responses. If not addressed properly, these loads can result in a decrease in gearbox component life. This work uses analytical modeling, computational modeling, and experimental data to evaluate a unique drivetrain design that minimizes the effects of nontorque loads on gearbox reliability: the Pure Torque(R) drivetrain developed by Alstom. The drivetrain has a hub-support configuration that transmits nontorque loads directly into the tower rather than through the gearbox as in other design approaches. An analytical model of Alstom's Pure Torque drivetrainmore » provides insight into the relationships among turbine component weights, aerodynamic forces, and the resulting drivetrain loads. Main shaft bending loads are orders of magnitude lower than the rated torque and are hardly affected by wind conditions and turbine operations.« less
  • This presentation was given at the 2011 Wind Turbine Reliability Workshop sponsored by Sandia National Laboratories in Albuquerque, NM on August 2-3, 2011. It discusses work for the Gearbox Reliability Collaborative including downtime caused by turbine subsystems, annual failure frequency of turbine subsystems, cost benefits of condition monitoring (CM), the Gearbox Reliability Collaborative's condition monitoring approach and rationale, test setup, and results and observations.
  • This presentation details the Gearbox Reliability Collaborative Condition Monitoring program at NREL.
  • High operation and maintenance costs still hamper the development of the wind industry despite its quick growth worldwide. To reduce unscheduled downtime and avoid catastrophic failures of wind turbines and their components have been and will be crucial to further raise the competitiveness of wind power. Condition monitoring is one of the key tools for achieving such a goal. To enhance the research and development of advanced condition monitoring techniques dedicated to wind turbines, we present an overview of wind turbine condition monitoring, discuss current practices, point out existing challenges, and suggest possible solutions.
  • Presented at Pennsylvania State University on September 15, 2014.