• 대한전기학회논문지:전력기술부문A
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• 제51권5호
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• pp.209-216
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• 2002

Recently, there is greater demand for stable supply of electric power as higher level of our living. It becomes the important problem that the cause of fault in power system is found out in early stage, if once it occurs. In this respect, accurate classification of arcing faults in power systems is vitally important. This paper presents a new classification method for arcing faults in power system. To obtain data of various faults including high impedance fault(HIF) and low impedance fault(LIF), HIF model with the ZnO arrester is adopted and implemented within the overall transmission system model based on the electromagnetic transients program(EMTP). Results of phase plane trajectory if Clarke modal transformation using postfault current and voltage are utilized to classify types of arcing faults. The performance of the proposed method is tested on a typical 154 kV korean transmission system under various fault conditions. As can be seen from results, phase plane trajectory of postfault current should be combined with that of o component from Clarke modal transformation to give reliability of clear fault classification. Thus the proposed method can classify arcing faults including LIFs and HIFs accurately in power systems.

• 한국농공학회지
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• 제34권4호
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• pp.39-47
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• 1992

Derivation of reasonable design low flows was attempted by comparative analysis of design low flows was derived by Power and SMEMAX transformations for the normalizations of skewed distribution and by Type m extremal distribution presented in the first report of this study with annual low flows in the five watersheds of main river basins in Korea. The results were anslyzed and summarized as follows. 1.Basic statistics of annual low flows for the selected watersheds were calculated by using Power and SMEMAX transformations. 2.Power thansformation has found to be the best for the normalization of skewed distribution among others including log, square root and SMEMAX transformations. 3.Design low flows for the selected watersheds were derived by the Power and SMEMAX transformations. 4.Judging by the relative suitabilities of the Type III extremal distribution, Power and SMEMAX transformation, it was found that design low flows of all methods are closer to the observed data within 10 years of the return period and those of Power transformation can be acknowledzed as a reasonable one among others from the viewpoint of the median between values of Type m extremal distribution and SMEMAX transformation in addition to closing the observed than others over 10 years of the return period.

• 응용통계연구
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• 제35권6호
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• pp.755-764
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• 2022

본 논문에서는 금융 시계열 변동성 추정을 위한 준-모수(quasi-likelihood) 방법을 다루고 있다. 모형식에서 오차항의 분포를 미지(unknown)로 하여 준-우도 함수를 통한 모수 추정을 하는 경우 이노베이션의 지정을 멱변환을 통해 구성하였다. 고정된 멱변환에 대한 프로파일-정보 행렬을 비교하여 최대값을 제공하는 멱변환을 제안하였다. 이차원 이노베이션으로의 확장을 다루었으며 코로나 펜데믹 기간의 높은 변동성을 보이는 국내 9개 주가 자료 분석을 통해 방법론을 예시하고 있다.

• 한국안전학회지
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• 제11권4호
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• pp.49-53
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• 1996

Corona discharges in air insulated electric power systems cause power loss, produce interfering electromagnetic radiation, and can indicate incipient failure. An understanding of corona discharges in air gap is clearly Important. The Wavelet transformation is an extended method of fourier transformation. The fourier method is a powerful tool for signal analysis, but it can't include information for time. However the wavelet transformation analysis can include on the information of time and frequencies at the same time. In this paper we apply the wavelet transformation to the corona signals in needle-plane air gap for the purpose of analysis of developing aspects of corona discharges. We analyzed the developing aspects of corona discharges, namely, corona discharge current, repetition rates, width of Pulse distribution region, pulseless region and frequencies distribution of corona discharge pulses.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.357-366
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• 2001

The present paper develops a method to check the propriety of link functions for binary data. In order to parameterize a certain type of goodness of the link, a family of link functions indexed by a shape parameter is proposed. I first investigate the maximum likelihood estimation of the shape parameter as well as regression parameters and then derive their large sample behaviors of the estimators. A score test is considered to evaluate the goodness of the current link function. For illustration, I employ two families of power transformations, the modulus transformation by John and Draper (1980) and the extended power transformation by Yeo and Johnson (2000), which are appropriate to detect symmetric and asymmetric inadequacy of the selected link function. respectively.

• ETRI Journal
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• 제35권4호
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• pp.714-717
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• 2013

Peak power reduction techniques in orthogonal frequency division multiplexing (OFDM) has been an important subject for many researchers for over 20 years. In this letter, we propose a side-information-free technique that is based on the concept of random variable (RV) transformation. The suggested method transforms RVs into other RVs, aiming to reshape the constellation that will consequently produce OFDM symbols with a reduced peak-to-average power ratio. The proposed method has no limitation on the mapping type or the mapping order and has no significant effect on the bit error rate performance compared to other methods presented in the literature. Additionally, the computational complexity does not increase.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.967-976
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• 2011

The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.451-458
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• 2017

An Electric Vehicle (EV) is operated with the electric energy of a battery in place of conventional fossil fuels. Thus, a suitable charging infrastructure must be provided to expand the use of electric vehicles. Because the battery of an EV must be charged to operate the EV, expanding the number of EVs will have a significant influence on the power supply and demand. Therefore, to maintain the balance of power supply and demand, it is important to be able to predict the numbers of charging EVs and monitor the events that occur in the distribution system. In this paper, we predict the hourly charging rate of electric vehicles using transformation matrix, which can describe all behaviors such as resting, charging, and driving of the EVs. Simulation with transformation matrix in a specific region provides statistical results using the Monte-Carlo Method.

• 대한전기학회논문지:전력기술부문A
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• 제51권8호
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• pp.409-416
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• 2002

This paper presents a fault location algorithm using direct 3-phase circuit analysis for distribution power networks. The unbalanced feature of distribution networks due to single phase loads or asymmetric operation prohibits us from using the conventional symmetrical component transformation. Even though the symmetrical component transformation provides us with a very easy tool in three phase network analysis, it is limited to balanced systems in utilizing its strong point, which is not suitable for distribution networks. In this paper, a fault location algorithm using direct 3-phase circuit analysis is developed. The algorithm is derived and it Is shown that the proposed method if we use matrix inverse lemma, is not more difficult then the conventional methods using symmetrical component transformation. Since the symmetrical component transformation is not used in the suggested method, unbalanced networks also can be handled with the same difficulty as balanced networks. The case study results show the correctness and effectiveness of the proposed algorithm.

• Journal of Power Electronics
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• 제9권3호
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• pp.507-515
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• 2009

This paper proposes an autonomous decentralized control for a parallel connected uninterruptible power supply (UPS) system based on a fast power detection method using a FPGA based hardware controller for a single phase system. Each UPS unit detects only its output voltage and current without communications signal exchange and a quasi dq transformation method is applied to detect the phase and amplitude of the output voltage and the output current for the single phase system. Fast power detection can be achieved based on a quasi dq transformation, which results in a realization of very fast transient response under rapid load change. In the proposed method, the entire control system is implemented in one FPGA chip. Complicated calculations are assigned to hardware calculation logic, and the parallel processing circuit makes it possible to realize minimized calculation time. Also, an Nios II CPU core is implemented in the same FPGA chip, and the software can be applied for non-time critical calculations. Applying this control system, an autonomous decentralized UPS system with very fast transient response is realized. Feasibility and stable operation are confirmed by means of an experimental setup with three UPSs connected in parallel. Also, rapid load change is applied and excellent performance of the system is confirmed in terms of transient response and stability.