• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.22-28
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• 2014

This paper proposes the fuzzy modeling and robust stability analysis of wind farm based on prediction model for wind speed. Owing to the sensitivity of wind speed, it is necessary to study the dynamic equation of the variable speed wind turbine. In this paper, based on the least-square method, the wind speed prediction model which is varied by the surrounding environment is proposed so that it is possible to evaluate the practicability of our model. And, we propose the composition of intelligent wind farm and use the fuzzy model which is suitable for the design of fuzzy controller. Finally, simulation results for wind farm which is modeled mathematically are demonstrated to visualize the feasibility of the proposed method.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.744-750
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• 2001

In now a days, the concern to environment and energy saving problem is increased worldly. So many countries are developing the wind power system as clean energy system. In our country, Cheju local government has the plan of the Cheju Island wind farm and 600kW class 2 wind turbines, 660kW class 2 turbines, 225kW class 1 turbine and 750kW class 2 turbines has been operated at Hangwon. In this paper the field operation data of the wind turbines was analyzed and was compared with the characteristics & performance of each turbines. As the results, we would find the possibility of wind turbine in domestic and suggest the direction of developing technology.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.412-418
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• 2011

The scale of wind turbines has continuously increased over the last decade. Especially, the rapid growth of the rotor diameter has brought about the increase of the tower height and the load on the rotor blade, as can be seen in the case of a 5MW class wind turbine with 126m rotor diameter. This trend means the increasing possibility of system failure. In addition to that, it is impossible for human operators to stay and manage all the turbines in the case of a large-scale wind farm. For these reasons, the operation and maintenance technology is getting more importance. In this paper, we present an unmanned remote monitoring system for MW class wind turbines and its application to YeungHeung wind test bed.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.1
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• pp.78-83
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• 2005

Currently in Japan, the use of the small wind turbine is an upward trend. There are already many well established small wind turbine generators in use and their various failures have been reported. The most commonly sighted failure is blade damage. Thus the research purpose was set to develop a simple failure diagnostic system, where an Acoustic Emission (AE) signal was produced from the failure part of a blade which was measured by AE sensor. The failure diagnostic technique was thoroughly examined. Concurrently, the damage part of the blade was imitated, the AE signal was measured, and a FFT(Fast Fourier Transform) analysis was carried out, and was compared with the output characteristic. When one sheet of a blade was damaged 40mm or more, the level was computed at which failure could be diagnosed.

• Tribology and Lubricants
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• v.27 no.4
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• pp.204-208
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• 2011

Yaw brakes are used in wind turbines to control the orientation of blades to be perpendicular to the wind. These devices are very important machine elements because they are closely related to the overall efficiency of wind turbines. One unit of yaw brakes is composed of a friction pad and a caliper. In this study, a tangential force between the friction pad and the disk is calculated when the brake is acting in 750 kW wind turbine. Then, stress distribution and the deformation of the caliper are calculated using a finite element analysis. An experimental equipment is also developed to verify the exactness of calculated results. The analytical and experimental results are presented and discussed.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.17-20
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• 2004

This paper presents a modeling and simulation of a grid-connected wind turbine generation system with respect to wind variations and three-phase fault in the system. It describes the modeling of the wind turbine system including the drive train model, induction generator model, and grid-interface model on MATLAB/Simulink. Case studies demonstrate that the pitch angle control is carried out to achieve maximum power extraction for wind speed variations and the duration of a fault on the system influences on the output of the wind turbine generator.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.623-624
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• 2011

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.6
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• pp.695-701
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• 2018

For a power grid that has a high wind penetration level, when wind speeds are continuously fluctuating, the maximum power point tracking (MPPT) operation of a variable-speed wind turbine (VSWT) causes the significant output power fluctuation of a VSWT, thereby significantly fluctuating the system frequency. In this paper, an improved power-smoothing scheme of a VSWT is presented that significantly mitigates the frequency fluctuation caused by varying wind speeds. The proposed scheme employs an additional control loop based on the frequency deviation that operates in combination with the MPPT control loop. To improve the power-smoothing capability of a VSWT in the over-frequency section (OFS), the control gain of the additional loop, which is set to be inversely proportional to the rotor speed, is proposed. In contrast, the control gain in the under-frequency section is set to be proportional to the rotor speed to improve the power-smoothing capability while avoiding over-deceleration of the rotor speed of a VSWT. The proposed scheme significantly improves the performance of the power-smoothing capability in the OFS, thereby smoothing the frequency fluctuation. The results clearly demonstrate that the proposed scheme significantly mitigates the frequency fluctuation by employing the different control gain for the OFS under various wind penetration scenarios.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.77-87
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• 2023

Wind turbines playing a critical role in renewable energy generation, accurately assessing their operational status is crucial for maximizing energy production and minimizing downtime. This study conducts a comparative analysis of different neural network models for wind turbine condition diagnosis, evaluating their effectiveness using a dataset containing sensor measurements and historical turbine data. The study utilized supervisory control and data acquisition data, collected from 2 MW doubly-fed induction generator-based wind turbine system (Model HQ2000), for the analysis. Various neural network models such as artificial neural network, long short-term memory, and recurrent neural network were built, considering factors like activation function and hidden layers. Symmetric mean absolute percentage error were used to evaluate the performance of the models. Based on the evaluation, conclusions were drawn regarding the relative effectiveness of the neural network models for wind turbine condition diagnosis. The research results guide model selection for wind turbine condition diagnosis, contributing to improved reliability and efficiency through advanced neural network-based techniques and identifying future research directions for further advancements.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.6
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• pp.87-95
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• 2004

In this paper, an efficient method for modeling a dual-rotor type wind turbine generator system and simulation results are presented. The wind turbine is treated as a collection of several rigid bodies, each of which represents, respectively, main and auxiliary rotor blades, high/low speed shafts, generator, and gear system. Simulation software WINSIM is developed to implement the proposed modeling method and is used to investigate the transient and steady-state performance of the wind turbine system.