• Journal of Power Electronics
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• 제17권3호
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• pp.579-589
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• 2017

In this study a new high step-up dc-dc converter is presented. The operation of the proposed converter is based on the capacitor switching and coupled inductor with a single active power switch in its structure. A passive voltage clamp circuit with two capacitors and two diodes is used in the proposed converter for elevating the converter's voltage gain with the recovered energy of the leakage inductor, and for lowering the voltage stress on the power switch. A switch with a low $R_{DS}$ (on) can be adopted to reduce conduction losses. In the generalized mode of the proposed converter, to reach a desired voltage gain, capacitor stages with parallel charge and series discharge techniques are extended from both sides of secondary side of the coupled inductor. The proposed converter has the ability to alleviate the reverse recovery problem of diodes with circuit parameters. The operating principle and steady-states analyses are discussed in detail. A 40W prototype of the proposed converter is implemented in the laboratory to verify its operation.

• 대한수학회지
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• 제51권6호
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• pp.1251-1267
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• 2014

The semicommutative property of rings was introduced initially by Bell, and has done important roles in noncommutative ring theory. This concept was generalized to one of nil-semicommutative by Chen. We first study some basic properties of nil-semicommutative rings. We next investigate the structure of Ore extensions when upper nilradicals are ${\sigma}$-rigid ${\delta}$-ideals, examining the nil-semicommutative ring property of Ore extensions and skew power series rings, where ${\sigma}$ is a ring endomorphism and ${\delta}$ is a ${\sigma}$-derivation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.285-288
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• 1998

A least-squares identification method is studied that estimates a finite number of coefficients in the series expansion of a transfer function, where the expansion is in terms of recently introduced generalized basis functions, We will expand and generalize the orthogonal functions as basis functions for dynamical system representations. To this end, use is made of balanced realizations as inner transfer functions. The orthogonal functions can be considered as generalizations of, for example, the pulse functions, Laguerre functions, and Kautz functions, and give rise to an alternative series expansion of rational transfer functions. We show that the Laplace transform of the expansion for some sets$\Psi_{\kappa}(Z)$ is equivalent to a series expansion . Techniques based on this result are presented for obtaining the coefficients $c_{n}$ as those of a series. One of their important properties is that, if chosen properly, they can substantially increase the speed of convergence of the series expansion. This leads to accurate approximate models with only a few coefficients to be estimated. The set of Kautz functions is discussed in detail and, using the power-series equivalence, the truncation error is obtained.

• Korean Journal of Mathematics
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• 제30권3호
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• pp.467-474
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• 2022

In this article, we consider the integral operator 𝓒^b,c, which is defined as follows: $${\mathcal{C}}^{b,c}(f)(z)={\displaystyle\smashmargin{2}{\int\nolimits_{0}}^z}{\frac{f(w)*F(1,1;c;w)}{w(1-w)^{b+1-c}}}dw,$$ where * denotes the Hadamard/ convolution product of power series, F(a, b; c; z) is the classical hypergeometric function with b, c > 0, b + 1 > c and f(0) = 0. We investigate the boundedness of the 𝓒^b,c operators on Bloch spaces.

• 산업경영시스템학회지
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• 제39권1호
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• KIEE International Transactions on Power Engineering
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• 제4A권3호
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• pp.159-166
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• 2004

Forecasting prices in electricity markets is critical for consumers and producers in planning their operations and managing their price risk. We utilize the generalized autoregressive conditionally heteroskedastic (GARCH) method to forecast the electricity prices in two regions of New York： New York City and Central New York State. We contrast the one-day forecasts of the GARCH against techniques such as dynamic regression, transfer function models, and exponential smoothing. We also examine the effect on our forecasting of omitting some of the extreme values in the electricity prices. We show that accounting for the extreme values and the heteroskedactic variance in the electricity price time-series can significantly improve the accuracy of the forecasting. Additionally, we document the higher volatility in New York City electricity prices. Differences in volatility between regions are important in the pricing of electricity options and for analyzing market performance.

• 전력전자학회논문지
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• 제3권4호
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• pp.353-364
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• 1998

본 논문에서는 시스템수준 시뮬레이션 언어를 통해 전력전자회로의 시뮬레이션을 행하기 위한 회로 모형화의 체계적인 접근방식을 제시하였다. 회로 내의 요소들을 입출력 조건에 따라 네가지 기본적 형태로 나타낼 수 있음을 보이고 병렬요소와 직렬요소들에 대한 일반 모델을 도출한 다음 이들을 조립하여 일반적인 컨버터시스템의 모델을 개발하는 방법을 제안하였다. 그 과정에서 모델간의 입출력 조건을 만족하면서 대수적 순환루우프의 발생의 방지라는 두 제약조건을 동시에 만족시키기 위해서는 일반적으로 모델간의 원활한 접속을 위한 가상 접속블록의 도입이 필요함을 보였다. 제시된 방법을 간단한 체강형 컨버터 회로를 대상으로 구현한 예를 보였고 접속블록의 도입을 일반적인 모델간 변환의 개념으로 확장하여 설명하였다.

• 전력전자학회논문지
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• 제22권2호
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• pp.102-108
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• 2017

Proper design guides are proposed for a practical dual-active bridge (DAB) converter based on the mathematical model on the steady state. The DAB converter is popular in bidirectional application due to its zero-voltage capability and easy bidirectional operation for seamless control, high efficiency, and performance. Some design considerations are taken to overcome the limitation of the DAB converter. The practical design methodology of power stage is discussed to minimize the conduction and switching losses of the DAB converter. Small-signal model and frequency response are derived and analyzed based on the generalized average method, which considers equivalent series resistance, to improve the dynamics, stability, and reliability with voltage regulation of the practical DAB converter. The design of closed-loop control is discussed by the derived small-signal model to obtain the pertinent gain and phase margin in steady-state operation. Experimental results of a 3.3 kW prototype of DAB converter demonstrate the validity and effectiveness of the proposed methods.

• Journal of the Korean Data and Information Science Society
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• 제26권4호
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• pp.885-894
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• 2015

전력시스템의 안정적이고 효과적인 운영을 위해선 전력수요예측이 필요하다. 본 연구에서는 일별전력수요패턴의 시간에 따른 커브를 군집분석 하려고 한다. 2009년 1월 1일부터 2011년 12월 31일까지의 일별 시간단위 전력수요 자료는 추세성분 제거와 로그변환을 통해 계절성분과 오차성분으로 구성된 시계열자료로 변환되었다. 변환된 자료는 Ma 등 (2006)이 제안한 함수적 군집모형을 사용하여 분석되었고, 모수는 EM알고리즘과 일반화교차검정을 통해 추정되었다. 군집의 수는 휴일과 평일을 잘 분류하는 10개로 결정하였다. 분석결과 월요일, 평일 (화요일~금요일), 토요일, 일요일 또는 공휴일과 계절요인으로 전력수요 평균곡선이 설명된다. 함수적 군집분석을 통한 전력수요패턴의 과학적인 분류는 향후 단기전력수요예측에 활용된다.

• Journal of the Korean Data and Information Science Society
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• 제20권3호
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• pp.475-483
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• 2009

본 연구에서는 한국종합주가지수 데이터를 이용하여 다양한 비선형 시계열 모형들을 소개하였다. 조건부 평균의 선형 모형으로는 상수항 모형, 자기회귀 모형을 살펴보았으며, 비선형 모형으로는 분계점 자기회귀 모형, 지수적 자기회귀 모형을 살펴보았다. 조건부 분산 모형으로는 일반 자기회귀 이분산 모형과 지수적 일반 자기회귀 이분산 모형, Glosten 등 (1993)의 모형 그리고 일반화 이항멱변환 분계점 일반 자기회귀 이분산 모형을 살펴보았다. 한편, 일반화 이항멱변환 분계점 일반 자기회귀 이분산 모형은 대표적 비대칭성 이분산성 모형인 Zakoian (1993) 모형과 Li와 Li (1996) 모형을 효과적으로 통합할 수 있는 변형된 모형이다. 본 연구에서는, 한국종합주가지수 데이터를 분석하여 새로운 모형의 효율성을 증명하였다.