• Journal of the Korean Solar Energy Society
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• v.38 no.2
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• pp.1-13
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• 2018

This paper deals with the NREL (National Renewable Energy Laboratory) 5-MW reference wind turbine. The controller which include MPPT (Maximum power point tracking) control algorithm and tower load reduction control algorithm was designed by MATLAB Simulink. This paper propose a tower damper algorithm to improve the existing tower damper algorithm. To improve the existing tower damper algorithm, proposed tower damper algorithm were applied the thrust sensitivity scheduling and PI control method. The thrust sensitivity scheduling was calculated by thrust force formula which include thrust coefficient table. Power and Tower root moment DEL (Damage Equivalent Load) was set as a performance index to verify the load reduction algorithm. The simulation were performed 600 seconds under the wind conditions of the NTM (Normal Turbulence Model), TI (Turbulence Intensity)16% and 12~25m/s average wind speed. The effect of the proposed tower damper algorithm is confirmed through PSD (Power Spectral Density). The proposed tower damper algorithm reduces the fore-aft moment DEL of the tower up to 6% than the existing tower damper algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1808-1818
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• 2015

Recently, the wind power has experienced great attentions and growths among many renewable energy sources. To increase the power generation performance and economic feasibility, the size of wind turbine (WT) is getting bigger and most of wind power plants are being constructed on offshore. Therefore, the maintenance cost is relatively high because boats or helicopters are needed operators to reach the WT. In order to combat this kind of problem, remote monitoring and control system for the WT is needed. In this paper, the small-scale WT monitoring and control system is implemented using wireless sensor network technologies. To do this, sensor devices are installed to measure and send the WT status and control device is installed to receive control message for specific operation. The WT is managed by control center through graphic user interface (GUI) based monitoring and control software. Also, smart device based web-program is implemented to make the remote monitoring of the WT possible even though operators are not in control room.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.603-609
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• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance procedures. Condition Monitoring System(CMS) can be used to aid plant owners in achieving these goals. Its aim is to provide operators with information regarding the health of their machines, which in turn, can help them improve operational efficiency. In this work, systematic design procedure for artificial neural network based normal behavior model which can be applied for fault detection of various devices is proposed. Furthermore, to verify the design method SCADA(Supervisor Control and Data Acquisition) data from 850KW wind turbine system installed in Beaung port were utilized.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1173-1178
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• 2011

The power generated by wind turbines changes rapidly because of the continuous fluctuation of wind speed and direction. It is important for the power industry to have the capability to predict the changing wind power. In this paper, neural network based wind power prediction scheme which uses wind speed and direction is considered. In order to get a better prediction result, compression function which can be applied to the measurement data is introduced. Empirical data obtained from wind farm located in Kunsan is considered to verify the performance of the compression function.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1232-1233
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• 2007

As the number of wind turbines installed increase, the power from wind energy starts to replace conventional generation units and its influence on power system can not be neglected. Because of the intermittent nature of wind resource, the output power of wind turbine fluctuates according to wind speed variation. In this point of view, it is necessary for wind turbines to be equipped with power regulation ability. The doubly fed induction generator (DFIG) is one of the main techniques used in variable speed wind turbines. This thesis focuses on the development of modified control scheme of DFIG to regulate output power. The proposed control scheme achieves active power output regulation so as to stabilize the power system.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.59-68
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• 2017

In accordance with the policy of local government, the large scale of wind farms have been installed in Jeju power system. However, The intermittent characteristics of wind power output may cause grid voltage and frequency variation, especially in weak power system. One of the solution to solve this problem is installation of Energy storage system (ESS). In this case, the ESS will regulate the active power generated from wind farm to mitigate fluctuation. Actually, the local government of Jeju island constructed ESS connected to Hangwon wind turbine in 2016. From this point, this paper analyzes requirement capacity of ESS to mitigate wind power fluctuation based on measured data from Hangwon wind turbine and ESS. The simulation results will be carried out by Matlab program.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1080-1088
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• 2014

By combining a wind turbine with an energy storage system (ESS), we are able to attenuate the intermittent wind power characteristic making the power derived from a wind farm dispatchable. This paper evaluates the influence of the phase delay of the low-pass filter in the conventional smoothing power control on the ESS capacity; longer phase delays require a larger ESS capacity. In order to eliminate the effect of the phase delay, we optimize the power dispatch using a zero-phase low-pass filter that results in a non-delayed response in the power dispatch. The proposed power dispatching method significantly minimizes the ESS capacity. In addition, the zero-phase low-pass filter, which is a symmetrical forward-reverse finite impulse response type, is designed simply with a small number of coefficients. Therefore, the proposed dispatching method is not only optimal, but can also be feasibly applied to real wind farms. The efficacy of the proposed dispatching method is verified by integrating a 3 MW wind turbine into the grid using wind data measured on Jeju Island.

• Smart Structures and Systems
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• v.18 no.4
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• pp.683-705
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• 2016

A semi-active algorithm for edgewise vibration control of the spar-type floating offshore wind turbine (SFOWT) blades, nacelle and spar platform is developed in this paper. A tuned mass damper (TMD) is placed in each blade, in the nacelle and on the spar to control the vibrations for these components. A Short Time Fourier Transform algorithm is used for semi-active control of the TMDs. The mathematical formulation of the integrated SFOWT-TMDs system is derived by using Euler-Lagrangian equations. The theoretical model derived is a time-varying system considering the aerodynamic properties of the blade, variable mass and stiffness per unit length, gravity, the interactions among the blades, nacelle, spar, mooring system and the TMDs, the hydrodynamic effects, the restoring moment and the buoyancy force. The aerodynamic loads on the nacelle and the spar due to their coupling with the blades are also considered. The effectiveness of the semi-active TMDs is investigated in the numerical examples where the mooring cable tension, rotor speed and the blade stiffness are varying over time. Except for excessively large strokes of the nacelle TMD, the semi-active algorithm is considerably more effective than the passive one in all cases and its effectiveness is restricted by the low-frequency nature of the nacelle and the spar responses.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.710-715
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• 2010

As wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is how to efficiently operate the wind turbines in a wide range of wind speeds. The wind speed has a huge impact on the dynamic response of wind turbine. For this purpose, many control algorithms are in need for a method to measure wind speed to increase performance. Unfortunately, no accurate measurement of the effective wind speed is online available from direct measurements, which means that it must be estimated in order to make such control methods applicable in practice. In this paper, a new method based on Kalman filter and artificial neural network is presented for the estimation of the effective wind speed. To verify the performance of the proposed scheme, some simulation studies are carried out.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.10a
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• pp.248-255
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• 1998