• 경영과학
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• 제22권1호
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• pp.15-26
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• 2005

The bootstrap is a method of computational inference that simulates the creation of new data by resampling from a single data set. We propose a new job for the bootstrap: generating inputs from one historical trace using Threshold Bootstrap. In this regard, the most important quality of bootstrap samples is that they be functionally indistinguishable from independent samples of the same stochastic process. We describe a quantitative measure of difference between two time series, and demonstrate the sensitivity of this measure for discriminating between two data generating processes. Utilizing this distance measure for the task of generating inputs, we show a way of tuning the bootstrap using a single observed trace. This application of the threshold bootstrap will be a powerful tool for Monte Carlo simulation. Monte Carlo simulation analysis relies on built-in input generators. These generators make unrealistic assumptions about independence and marginal distributions. The alternative source of inputs, historical trace data, though realistic by definition, provides only a single input stream for simulation. One benefit of our method would be expanding the number of inputs achieving reality by driving system models with actual historical input series. Another benefit might be the automatic generation of lifelike scenarios for the field of finance.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1998년도 추계학술발표회요약집
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• pp.116-116
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• 1998

• Earthquakes and Structures
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• 제3권5호
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• pp.719-747
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• 2012

In this paper a novel approach is proposed to address the problem of deriving non-stationary stochastic processes which are compatible in the mean sense with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice. The appealing feature of the approach is that it is non-iterative and "one-step". This is accomplished by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors. These factors are determined by a plethora of reported new Monte Carlo studies which on their own possess considerable stochastic dynamics merit. In the proposed approach, generation and treatment of samples of the processes individually on a deterministic basis is not required as is the case with the various "two-step" approaches found in the literature addressing the herein considered task. The applicability and usefulness of the approach is demonstrated by furnishing extensive numerical data associated with the elastic design UHS of the current European (EC8) and the Chinese (GB 50011) aseismic code provisions. Purposely, simple and thus attractive from a practical viewpoint, uniformly modulated processes assuming either the Kanai-Tajimi (K-T) or the Clough-Penzien (C-P) spectral form are employed. The Monte Carlo studies yield damping and duration dependent median peak factor spectra, given in a polynomial form, associated with the first passage problem for UHS compatible K-T and C-P uniformly modulated stochastic processes. Hopefully, the herein derived stochastic processes and median peak factor spectra can be used to facilitate the aseismic design of structures regulated by contemporary code provisions in a Monte Carlo simulation-based or stochastic dynamics-based context of analysis.

• Earthquakes and Structures
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• 제3권3_4호
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• pp.581-609
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• 2012

In this paper a novel non-iterative approach is proposed to address the problem of deriving non-stationary stochastic processes which are compatible in the mean sense with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice. This is accomplished by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors. These factors are determined by a plethora of reported new Monte Carlo studies which on their own possess considerable stochastic dynamics merit. In the proposed approach, generation and treatment of samples of the processes individually on a deterministic basis is not required as is the case with the various approaches found in the literature addressing the herein considered task. The applicability and usefulness of the approach is demonstrated by furnishing extensive numerical data associated with the elastic design UHS of the current European (EC8) and the Chinese (GB 50011) aseismic code provisions. Purposely, simple and thus attractive from a practical viewpoint, uniformly modulated processes assuming either the Kanai-Tajimi (K-T) or the Clough-Penzien (C-P) spectral form are employed. The Monte Carlo studies yield damping and duration dependent median peak factor spectra, given in a polynomial form, associated with the first passage problem for UHS compatible K-T and C-P uniformly modulated stochastic processes. Hopefully, the herein derived stochastic processes and median peak factor spectra can be used to facilitate the aseismic design of structures regulated by contemporary code provisions in a Monte Carlo simulation-based or stochastic dynamics-based context of analysis.

• 한국경영과학회지
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• 제37권3호
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• pp.135-150
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• 2012

This paper presents a portfolio model for a long-term power generation mix problem. The proposed portfolio model evaluates generation mix by considering the tradeoffs between the expected cost for power generation and its variability. Unlike conventional portfolio models measuring variance, we introduce Conditional Value-at-Risk (CVaR) in designing the variability with aims to considering events that are enormously expensive but are rare such as nuclear power plant accidents. Further, we consider uncertainties associated with future electricity demand, fuel prices and their correlations, and capital costs for power plant investments. To obtain an objective generation by each energy source, we employ the sample average approximation method that approximates the stochastic objective function by taking the average of large sample values so that provides asymptotic convergence of optimal solutions. In addition, the method includes Monte Carlo simulation techniques in generating random samples from multivariate distributions. Applications of the proposed model and method are demonstrated through a case study of an electricity industry with nuclear, coal, oil (OCGT), and LNG (CCGT) in South Korea.

• 조명전기설비학회논문지
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• 제17권4호
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• pp.81-86
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• 2003

피크용 분산전원은 계통의 전체 운영비용을 줄일 수 있고, 대기용 분산전원은 수용가의 신뢰도를 향상시킬 수 있다. 피크용 분산전원과 대기용 분산전원은 해석하는데 있어서 다른 모델링을 세워야 하고 그에 따라 다른 방식으로 해석해야 하는데 이를 구현하기 위해서는 Monte-Carlo시뮬레이션 기법이 적합하다고 할 수 있다. 본 논문에서는 순차적 시뮬레이션 기법을 통해 두 가지 분산전원의 영향을 신뢰도 지수로 표현하고 이를 통해 두 가지 분산전원의 장단점을 살펴보도록 하겠다.

• International Journal of Advanced Culture Technology
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• 제10권3호
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• pp.307-312
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• 2022

The commercialization of the fifth generation (5G) mobile systems has quested enabling technologies, such as intelligent reflecting surface (IRS) transmissions, towards the sixth generation (6G) networks. In this paper, we present a bit-error rate (BER) performance analysis on IRS transmissions in 5G non-orthogonal multiple access (NOMA) networks. First, we derive a closed-form expression for the BER of IRS-NOMA transmissions under Rician fading channels. Then, by Monte Carlo simulations, we validate the proposed approximate BER expression, and show numerically that the derived BER expression is in good agreement with Monte Carlo simulations. Furthermore, we also analyze the BER performance of IRS-NOMA networks under Rician fading channels with different numbers of reflecting elements, and demonstrate that the performances improve monotonically as the number of reflecting devices increases.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1999년도 추계학술발표회요약집
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• pp.57.1-57
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• 1999

• 조명전기설비학회논문지
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• 제21권10호
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• pp.52-58
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• 2007

본 논문에서는 발전량 적정성 평가를 위한 풍력발전 모형의 제안하였다. 풍력 발전량과 계통 부하량은 일 년을 주기로 하는 주기함수 형태이므로, 둘 중 하나의 물리량이 주어지면 다른 물리량의 발생 확률을 계산할 수 있다. 본 논문에서는 가상의 데이터를 바탕으로 두 물리량을 k-means 클러스터링 알고리즘으로 단계화하였고, 각 단계간의 확률적인 관계를 계산하였다. 제안하는 풍력발전 모형은 상태샘플링(state sampling)에 기반을 둔 몬테카를로 모의로써 발전량 적정성을 평가하는데 적합하다.

• KIEE International Transactions on Power Engineering
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• 제4A권2호
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• pp.100-105
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• 2004

Installed capacity markets in the northeast of the United States ensure that adequate generation exists to satisfy regional loss of load probability (LOLP) criterion. LOLP studies are conducted to determine the amount of capacity that is needed, but they do not consider several factors that substantially affect the calculated distribution of available capacity. These studies do not account for the fact that generation availability increases during periods of high demand and therefore prices, common-cause failures that result in multiple generation units being unavailable at the same time, and the negative correlation between load and available capacity due to temperature and humidity. A categorization of incidents in an existing bulk power reliability database is proposed to analyze the existence and frequency of independent failures and those associated with resource dynamics. Findings are augmented with other empirical findings. Monte Carlo methods are proposed to model these resource dynamics. Using the IEEE Reliability Test System as a single-bus case study, the LOLP results change substantially when these factors are considered. Better data collection is necessary to support the more comprehensive modeling of resource adequacy that is proposed. In addition, a parallel processing method is used to offset the increase in computational times required to model these dynamics.