• 제목/요약/키워드: WSVD

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발전기 탈락 시 Wavelet Transform과 Singular Value Decomposition을 이용한 특성 분석 (Effect Analysis of Generator Dropping Using Wavelet Singular Value Decomposition)

  • 노철호;김원기;한준;김철환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.49-50
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    • 2011
  • 본 논문에서는 WT(Wavelet Transform)와 SVD(Singular Value Decomposition)를 함께 사용한 WSVD(Wavelet Singular Value Decomposition)를 이용하여 발전기 탈락 시의 전압 변동 특성을 분석하였다. WSVD 특성 분석을 위해 부산 지역의 345kV급 송전계통을 EMTP-RV로 모델링하였으며, 이 계통모델에서 발전기 탈락을 모의하였다. MATLAB을 통해 이 때 측정된 전압의 WSVD를 계산하여 발전기 탈락에 따른 특성을 분석하였다.

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부하 탈락 시 Wavelet Transform과 Singular Value Decomposition을 이용한 특성 분석 (Effect Analysis of Load Shedding Using Wavelet Singular Value Decomposition)

  • 권기현;김원기;한준;김철환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.51-52
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    • 2011
  • 본 논문에서는 WT(Wavelet Transform)와 SVD(Singular Value Decomposition)기법을 결합한 WSVD(Wavelet Singular Value Decomposition)를 사용하여, 송전계통에서 부하 탈락 시 나타나는 특성 및 외란검출의 유효성을 분석하였다. WSVD 방식을 이용한 외란검출을 모의하기 위해 EMTP-RV를 이용하여 부산 및 경남 일부지역 345kV급 송전계통을 모델링하였고, 이 계통에서 부하 탈락을 모의하였다. WSVD의 계산은 MATLAB을 통해 수행하였으며, 이 결과를 바탕으로 전력계통에서 부하 탈략량의 변화에 따른 특징을 분석하였다

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Wavelet Singular Value Decomposition을 이용한 부하 탈락 검출 알고리즘 개발 (Development of Algorithm to Detect Load Shedding Using Wavelet Singular Value Decomposition)

  • 한준;김원기;이제원;김철환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.244-245
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    • 2011
  • In this paper, the algorithm for detecting load shedding based on Wavelet Singular Value Decomposition(WSVD) is proposed. WSVD is method of signal processing which combine Wavelet Transform(WT) and Singular Value Decomposition(SVD) to analyze transients in power system. 345kV Busan transmission system is modeled by EMTP-RV and simulations according to successive change of load capability are conducted. This paper analyzes characteristics of WSVD by using simulation results and proposes algorithm for detecting load shedding.

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Wavelet Singular Value Decomposition을 이용한 고장 판별 및 발전기 탈락 검출 알고리즘 (An Algorithm for Fault Classification and Detection of Generator Dropping Using Wavelet Singular Value Decomposition)

  • 김원기;한준;이제원;김철환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.205-206
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    • 2011
  • In this paper, algorithm for fault classification and detection of generator dropping using wavelet singular value decomposition (WSVD) is proposed. Busan area upper 345kV is modeled and generator dropping is simulated in EMTP-RV. Characteristic of generator dropping is analyzed and this algorithm is deducted by calculating WSVD in MATLAB.

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Development of Fault Detector for Series Arc Fault in Low Voltage DC Distribution System using Wavelet Singular Value Decomposition and State Diagram

  • Oh, Yun-Sik;Han, Joon;Gwon, Gi-Hyeon;Kim, Doo-Ung;Kim, Chul-Hwan
    • Journal of Electrical Engineering and Technology
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    • 제10권3호
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    • pp.766-776
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    • 2015
  • It is well known that series arc faults in Low Voltage DC (LVDC) distribution system occur at unintended points of discontinuity within an electrical circuit. These faults can make circuit breakers not respond timely due to low fault current. It, therefore, is needed to detect the series fault for protecting circuits from electrical fires. This paper proposes a novel scheme to detect the series arc fault using Wavelet Singular Value Decomposition (WSVD) and state diagram. In this paper, the fault detector developed is designed by using three criterion factors based on the RMS value of Singular value of Approximation (SA), Sum of the absolute value of Detail (SD), and state diagram. LVDC distribution system including AC/DC and DC/DC converter is modeled to verify the proposed scheme using ElectroMagnetic Transient Program (EMTP) software. EMTP/MODELS is also utilized to implement the series arc model and WSVD. Simulation results according to various conditions clearly show the effectiveness of the proposed scheme.

Pin Power Reconstruction of HANARO Fuel Assembly via Gamma Scanning and Tomography Method

  • Seo, Chul-Gyo;Park, Chang-Je;Cho, Nam-Zin;Kim, Hark-Rho
    • Nuclear Engineering and Technology
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    • 제33권1호
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    • pp.25-33
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    • 2001
  • To determine the pin power distribution without disassembling, HANARO fuel assemblies are gamma-scanned and then the distribution is reconstructed tv using the tomography method. The iterative least squares method (ILSM and the wavelet singular value decomposition method (WSVD) are chosen to solve the problem. An optimal convergence criterion is used to stop the iteration algorithm to overcome the potential divergence in ILSM. WSVD gives better results than ILSM , and the average values from the two methods give the best results. The RMSE (root mean square errors) to the reference data are 5.1, 6.6, 5.0, 6.5, and 6.4% and the maximum relative errors are 10.2, 13.7, 12.2, 13.6, and 14.3%, respectively. It is found that the effect of random positions of the pins is important. Although the effect can be accommodated by the iterative calculations simulating the random positions, the use of experimental equipment with a slit covering the whole range of the assembly horizontally is recommended to obtain more accurate results. We made a new apparatus using the results of this study and are conducting an experiment in order to obtain more accurate results.

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고장전류의 누적 에너지를 이용한 저압직류 배전계통의 고저항 지락고장 검출 알고리즘 개발 (Development of an Algorithm for Detecting High Impedance Fault in Low Voltage DC Distribution System using Accumulated Energy of Fault Current)

  • 오윤식;노철호;김두웅;권기현;한준;김철환
    • 조명전기설비학회논문지
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    • 제29권5호
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    • pp.71-79
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    • 2015
  • Recently, new Low Voltage DC (LVDC) power distribution systems have been constantly researched as uses of DC in end-user equipment are increased. As in conventional AC distribution system, High Impedance Fault (HIF) which may cause a failure of protective relay can occur in LVDC distribution system as well. It, however, is hard to be detected since change in magnitude of current due to the fault is too small to detect the fault by the protective relay using overcurrent element. In order to solve the problem, this paper presents an algorithm for detecting HIF using accumulated energy in LVDC distribution system. Wavelet Singular Value Decomposition (WSVD) is used to extract abnormal high frequency components from fault current and accumulated energy of high frequency components is considered as the element to detect the fault. LVDC distribution system including AC/DC and DC/DC converter is modeled to verify the proposed algorithm using ElectroMagnetic Transient Program (EMTP) software. Simulation results considering various conditions show that the proposed algorithm can be utilized to effectively detect HIF.