• 응용통계연구
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• 제27권3호
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• pp.475-485
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• 2014

일반화 선형모형(GLM)에 기초한 확률적 날씨 발생기(Stochastic weather generator)는 일일 날씨를 생성하는데 가장 일반적으로 사용되는 방법인다. 본 논문에서는 다층구조를 이용하여 기존의 GLM weather generator에 공간구조를 소개하였다. 계절별 총강우량의 overdispersion 현상을 효과적으로 제거하기 위해서 smoothing된 계절별 총강우량을 모형에 포함하였고 공간구조를 소개하기 위해서 Stochastic weather generator의 모형계수에 공간구조를 가지는 다변량 정규분포를 가정하였다. 그리고 제안된 공간구조를 가지는 GLM weather generator 모형을 우리나라 76개 지역에서 39년간 측정된 일별 강우량 관측자료에 적용하였다.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1309-1317
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• 2012

Stochastic weather generators are commonly used to simulate time series of daily weather, especially precipitation amount. Recently, a generalized linear model (GLM) has been proposed as a convenient approach to fitting these weather generators. In this paper, a stochastic weather generator is considered to model the time series of daily precipitation at Seoul in South Korea. As a covariate, global temperature is introduced to relate long-term temporal scale predictor to short-term temporal predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate time series of seasonal total precipitation in the GLM weather generator as covariates. It is veri ed that the addition of these covariates does not distort the performance of the weather generator in other respects.

• 응용통계연구
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• 제26권3호
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• pp.413-420
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• 2013

확률적 날씨 발생기(Stochastic weather generator)는 일일 날씨를 생성하는데 일반적으로 사용되는 방법으로 최근에는 일반화선형모형에 기초한 확률적 날씨 발생 방법이 제안되었다. 본 논문에서는 서울지역의 일일 기온을 모형화하하기 위해서 일반화선형모형에 기초한 확률적 날씨 발생기를 고려하였다. 이 모형에서는 계절성을 나타내는 변수와 강우발생 유무가 공변수로 사용되었다. 일반적으로 확률적 날씨 발생기에서는 생성된 일일 날씨가 월별 또는 계절별 총강우량이나 평균온도에 충분한 변동을 만들어 내지 못하는 과대산포 현상이 발생하는데, 이러한 한계를 극복하기 위해 본 연구에서는 평활된 계절별 평균 온도를 일반화선형모형의 공변수로 추가하였다. 그리고 제안된 모형을 1961년부터 2011년까지 51년 동안의 서울지역 일일 평균 기온자료에 적용하였다.

• 한국농공학회지
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• 제40권1호
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• pp.57-67
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• 1998

A stochastic weather generator which simulate daily precipitation, maximum and minimum daily temperature, relative humidity was developed. The model parameters were estimated using stochastic characteristics analysis of historical data of 71 weather stations. Spatial variations of the parameters for the country were also analyzed. Model parameters of ungauged Sites were determined from parameters of adjacent weather stations using inverse distance method. The model was verified on Suwon and Ulsan weather stations and showed good agreement between simulated and observed data.

• Journal of Mechanical Science and Technology
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• 제16권7호
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• pp.942-949
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• 2002

The use of a combined starter/generator integrated into the drive train of an automobile offers several possibilities for improvement of fuel economy The use of such a starter/generator system is made feasible by a switch from a 14 volts electrical system to a 42 volts system, however, the sizing of the components is not a trivial problem. This study combines a dynamic electromechanical model of the starter, battery and power electronics with the nonlinear mechanics of the piston/crankshaft system and a thermofluid model of the compression and expansion processes to investigate the cold start problem. The example involves the start of an eight cylinder engine at -25 degrees Celsius. This paper shows how the mechatronic V8 engine of an automotive starter/generator system for the startability works well.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.2000-2001
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• 2007

Wind power generation system based on the PSCAD/EMTD is proposed in this paper for the simulations under the real weather conditions. Real field data of weather condition is interfaced to PSCAD/EMTDC using Fortran program interfaced method. And a new turbine component is developed using characteristic equation of a wind turbine and pitch angle control algorism. The generator output and current supplied into utility can be obtained by the transient analysis using PSCAD/EMTDC.

• 한국수자원학회논문집
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• 제36권3호
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• pp.345-363
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• 2003

대기순환모형(GCM)에 의하면 온실가스농도의 증가는 전구와 국지규모의 기후변화에 중요한 관련이 있음이 알려져 있다. GCM은 단일지점의 기상학적 순환과정을 분석하는데는 불확실성을 지니고 있기 때문에 현재로서는 축소기법이 대기순환모형(GCM)의 개발자들이 제공할 수 있는 것과 모형을 이용하여 기후영향을 평가하는 연구자들이 요구하는 것 사이의 차이점을 연계하기 위해 이용되고 있다. 본 논문에서는 통계학적 축소기법을 이용하여 국지 규모의 기후변화의 영향을 평가할 수 있는 방법을 제시하고자 하였다. 본 방법을 이용한다면 현재와 미래의 국지적 규모의 기후강제력 하에서의 지표 기상변수의 시나리오를 저 비용으로 신속하게 작성할 수 있다. 기후변화시나리오의 작성은 통계학적 회귀방법인 전이함수와 추계학적 일기발생모형을 이용하였다. 전이함수는 저해상도의 GCM 격자 변수들을 고해상도의 단일 지점의 변수들로 변환시키며, 이 변수들은 단일 지점의 특정 일 지표 기상 변수를 모의하기 위해 추계학적 일기발생 모형의 매개변수를 수정하는데 이용되었다. 본 연구에서는 YONU GCM을 이용하여 제어실험과 점증실험을 실시하여 전구규모의 기후변화시나리오를 작성하였다.

• 전기학회논문지P
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• 제59권1호
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• pp.129-133
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• 2010

A hybrid system which is combined several complementary new and renewable power sources, such as photovoltaic, fuel-cell, and wind generator, etc., has been presented in various approaches. For instance, a photovoltaic cannot always generate stable output power with ever-changing weather condition, so it might be co-generated with a wind generator, diesel generator, and some other sources. In this paper, a residential PV-FC hybrid system is suggested as a distribution power source, and its operation is optimized by HOMER$^{(R)}$. As a result, it is the most economic that 5[kW] PV, 1[kW] FC, 4 batteries, 2[kW] electrolyzer, 0.5[kg] $H_2$ tank, 3[kW] converter are applied to the hybrid system.

• 한국농공학회논문집
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• 제52권5호
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• pp.1-9
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• 2010

Evapotranspiration (ET) is one of the basic components of the hydrologic cycle and is essential for estimating irrigation water requirements. In this study, artificial neural network (ANN) models for reference crop evapotranspiration ($ET_0$) estimation were developed on a monthly basis (May~October). The models were trained and tested for Suwon, Korea. Four climate factors, daily maximum temperature ($T_{max}$), daily minimum temperature ($T_{min}$), rainfall (R), and solar radiation (S) were used as the input parameters of the models. The target values of the models were calculated using Food and Agriculture Organization (FAO) Penman-Monteith equation. Future climate data were generated using LARS-WG (Long Ashton Research Station-Weather Generator), stochastic weather generator, based on HadCM3 (Hadley Centre Coupled Model, ver.3) A1B scenario. The evapotranspirations were 549.7 mm/yr in baseline period (1973-2008), 558.1 mm/yr in 2011-2030, 593.0 mm/yr in 2046-2065, and 641.1 mm/yr in 2080-2099. The results showed that the ANN models achieved good performances in estimating future reference crop evapotranspiration.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회 논문집
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• pp.143-148
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• 2005

The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.