• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.5
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• pp.363-373
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• 2014

In this study, computational multi-body dynamic analyses for the drivetrain system of a 5 MW class offshore wind turbine have been conducted using efficient equivalent modeling technique based on the design guideline of GL 2010. The present drivetrain system is originally modeled and its related system data is adopted from the NREL 5 MW wind turbine model. Efficient computational method for the drivetrain system dynamics is proposed based on an international guideline for the certification of wind turbine. Structural dynamic behaviors of drivetrain system with blade, hub, shaft, gearbox, supports, brake disk, coupling, and electric generator have been analyzed and the results for natural frequency and equivalent torsional stiffness of the drivetrain system are presented in detail. It is finally shown that the present multi-body dynamic analysis method gives good agreement with the previous results of the 5 MW class wind turbine system.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.286-289
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• 2008

Wind turbine industry is booming and spending a lot on research for improving the performance of its present machines and increasing their capacity. Wind turbine requires service life of about 20 years and each components of wind turbine requires high durability, because installation and maintenance costs are more expensive than generated electricity by wind-turbine. So the design of wind turbine must be verified in various condition before production step. For this work, high reliability model for analysis is required. Drivetrain model is modeled by multibody dynamic modeling method. The model constituted with rotor blades, hub, main shaft, gear box, high speed shaft and generator. Natural frequency and torsional stiffness of drivetrain are calculated and analyzed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.583-586
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• 2012

Wind turbine industry is booming and spending a lot on research for improving the performance of its present machines and increasing their capacity. Wind turbine requires service life of about 20 years and each canponents of wind turbine requires high durability, because installation and maintenance costs are more expensive than generated electricity by wind-turbine. So the design of wind turbine must be verified in various condition before production step. For this work, high reliability model for analysis is required. Drivetrain model is modeled by multibody dynamic modeling method. The model constituted with rotor blades, hub, main shaft, gear box, high speed shaft and generator. Natural frequency and torsional stiffness of drivetrain are calculated and analyzed.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.33-41
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• 2023

As carbon-free has been getting interest, renewable energy sources have been increasing. However, renewable energy is intermittent and variable so it is difficult to predict the produced electrical energy from a renewable energy source. In this study, digital-twin concept is applied to solve difficulties in predicting electrical energy from a renewable energy source. Considering that rotation of wind turbine has high correlation with produced electrical energy, a model which simulates rotation in the drivetrain of a wind turbine is developed. The base of a drivetrain simulation model is set with well-known state equation in mechanical engineering, which simulates the rotating system. Simulation based machine learning is conducted to get unknown parameters which are not provided by manufacturer. The simulation is repeated and parameters in simulation model are corrected after each simulation by optimization algorithm. The trained simulation model is validated with 27 real wind turbine operation data set. The simulation model shows 4.41% error in average compared to real wind turbine operation data set. Finally, it is assessed that the drivetrain simulation model represents the real wind turbine drivetrain system well. It is expected that wind-energy-prediction accuracy would be improved as wind turbine digital twin including the developed drivetrain simulation model is applied.

• Journal of Wind Energy
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• v.14 no.3
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• pp.34-42
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• 2023

The reduction of operation and maintenance (O&M) costs is a critical factor in determining the competitiveness of wind energy. Predictive maintenance based on the estimation of remaining useful life (RUL) is a key technology to reduce logistic costs and increase the availability of wind turbines. Although a mechanical component usually has sudden changes during operation, most RUL estimation methods use the trend of a state index over the whole operation period. Therefore, overestimation of RUL causes confusion in O&M plans and reduces the effect of predictive maintenance. In this paper, two RUL estimation methods (load based and data driven) are proposed for the bearings of a wind turbine with the results of trend classification, which differentiates constant and increasing states of the state index. The proposed estimation method is applied to a bearing degradation test, which shows a conservative estimation of RUL.