• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.9
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• pp.425-432
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• 2000

Wavelet transform is a new method fro electric power quality analysis. Several types of mother wavelets are compared using voltage sag data. Investigations on the use of some mother wavelets, namely Daubechies, Symlets, Coiflets, Biorthogonal, are carried out. On the basis of extensive investigations, optimal mother wavelets for the detection of voltage sag are chosen. The recommended mother wavelet is 'Daubechies 4(db4)' wavelet. 'db4', the most commonly applied mother wavelet in the power quality analysis, can be used most properly in disturbance phenomena which occurs rapidly for a short time. This paper presents a discrete wavelet transform approach for determining the beginning time and end time of voltage sags. The technique is based on utilising the maximum value of d1(at scale 1) coefficients in multiresolution analysis(MRA) based on the discrete wavelet transform. The procedure is fully described, and the results are compared with other methods for determining voltage sag duration, such as the RMS voltage and STFT(Short-Time Fourier Transform) methods. As a result, the voltage sag detection using wavelet transform appears to be a reliable method for detecting and measuring voltage sags in power quality disturbance analysis.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.55.4-56
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• 2015

The Hilbert-Huang Transform (HHT) is composed of the Empirical Mode Decomposition (EMD) and the Hilbert Spectral Analysis (HSA). The EMD decomposes any time series data into a small number of components called the Intrinsic Mode Functions (IMFs), compared to the Discrete Fourier Transform which decomposes a data into a large number of harmonic functions. Each IMF has varying amplitude and frequency with respect to time, which can be obtained by HSA. The time resolution of the modes in HHT is the same as that of the given time series, while in the Wavelet Transform, Constant Q Transform and Short-Time Fourier Transform, there is a tradeoff between the resolutions in frequency and time. Based on the time-dependent amplitudes of IMFs, we develop an Event Trigger Generator and demonstrate its efficiency by applying it to gravitational-wave data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.498-503
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• 2009

As for Hadamard Transform, because the calculation time of this transform is slower than Discrete Cosine Transform (DCT) and Fast Fourier Transform (FFT), the effectiveness and the practicality are insufficient. Then, the computational complexity can be decreased by using the butterfly operation as well as FFT. We composed calculation time of FFT with that of Fast Complex Hadamard Transform by constructing the algorithm of Fast Complex Hadamard Transform. They are indirect conversions using program of complex number calculation, and immediate calculations. We compared calculation time of them with that of FFT. As a result, the reducing the calculation time of the Complex Hadamard Transform is achieved. As for the computational complexity and calculation time, the result that quadrinomial Fast Complex Hadamard Transform that don't use program of complex number calculation decrease more than FFT was obtained.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.303-306
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• 1996

We propose a robust tuning method of the quadratic criterion based iterative learning control(Q-ILC) algorithm for discrete-time linear batch system. First, we establish the frequency domain representation for batch systems. Next, a robust convergence condition is derived in the frequency domain. Based on this condition, we propose to optimize the weighting matrices such that the upper bound of the robustness measure is minimized. Through numerical simulation, it is shown that the designed learning filter restores robustness under significant model uncertainty.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.377-382
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• 2016

In 2013, a total capacity of 591.3 MW of installed wind power generation was achieved in Korea, with a total of 1,139 MWh of wind energy generated that year. More wind power plants will be installed in the coming years, and it is important to develop methods to reduce the output variability of these resources so as to provide stable power to the power grid of Korea. In this regard, this paper proposes the use of energy storage system (ESS) as a means to stabilize the output variability of wind power plants. Presented in this paper is a method that uses Discrete Fourier Transform (DFT) to determine the ESS capacity needed to provide a stable power output for ancillary services such as frequency regulation, economic dispatch, and emergency reserves. In the first step of the proposed method, four regions (namely, Samdal, Yeongdeok, Yeongyang, and Gangwon) in Korea that had the most wind power generation capacity were selected for analysis. In the second step, the individual and aggregated wind power outputs of the selected regions in 2013 were obtained This information was then used in the third step, where DFT analysis of the power outputs was used to drive the magnitudes of the output variation. And finally, the ESS capacity requirements needed to provide different ancillary services were determined based on the magnitudes of the output variation.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.695-706
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• 2014

Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.241-242
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• 2009

• Journal of Power Electronics
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• v.18 no.5
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• pp.1567-1576
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• 2018

The reliability of grid-connected inverters can be improved by algorithms capable of diagnosing faults in LCL filters. A fault diagnostic method during inverter startup is proposed. The proposed method can accurately generate and monitor information on the peak value and the location of the peak frequency component of the step response of a damped LCL filter. To identify faults, the proposed method compares the evaluated response with the response of a healthy higher-order damped LCL filter. The frequency components in the filter voltage response are first analytically obtained in closed form, which yields the expected trends for the filter faults. In the converter controller, the frequency components in the filter voltage response are computed using an appropriately designed fast Fourier transform and compared with healthy LCL response parameters using a finite state machine, which is used to sequence the proposed startup diagnostics. The performance of the proposed method is validated by comparing analytical results with the simulation and experimental results for a three-phase grid-connected inverter with a damped LCL filter.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.4
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• pp.201-208
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• 2002

In this paper, we present a new formulation using time-domain electric field integral equation (TD-EFIE) to obtain transient scattering response from arbitrarily shaped three-dimensional conducting bodies. The time derivative of the magnetic vector potential is approximated with a central finite difference and the scalar potential is time averaged by dividing it into two terms. This approach with an implicit method using central difference results in accurate and more stable transient scattering responses from conducting objects. Detailed mathematical steps are included and several numerical results are presented and compared with the inverse discrete Fourier transform (IDFT) of the frequency-domain solution.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.9
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• pp.937-946
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• 2002

In this paper, we present a stable solution of the transient electromagnetic scattering from the conducting objects. This method does not utilize the conventional marching-on in time (MOT) solution. Instead we solve the time domain integral equation by expressing the transient behavior of the induced current in terms of weighted Laguerre polynomials. By using this basis functions for the temporal variation, the time derivative in the integral equation can be handled analytically. Since these temporal basis functions converge to zero as time progresses, the transient response of the induced current does not have a late time oscillation. To show the validity of the proposed method, we solve a time domain electric feld integral equation and compare the results of MOT, Mie solution, and the inverse discrete Fourier transform (IDFT) of the solution obtained in the frequency domain.