• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.4
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• pp.505-514
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• 2015

This paper proposes a probabilistic generation assessment model of renewable energy generators(REGs) considering uncertainty of resources, mainly focused on Wind Turbine Generator(WTG) and Solar Cell Generator(SCG) which are dispersed widely in South Korea The proposed numerical analysis method assesses the one day-ahead generation by combining equivalent generation characteristics function and probabilistic distribution function of wind speed(WS) and solar radiation(SR) resources. The equivalent generation functions(EGFs) of the wind and solar farms are established by grouping a lot of the farms appropriately centered on Weather Measurement Station(WMS). First, the EGFs are assessed by using regression analysis method based on typical least square method from the recorded actual generation data and historical resources(WS and SR). Second, the generation of the REGs is assessed by adding the one day-ahead resources forecast, announced by WMS, to the EGFs which are formulated as third order degree polynomials using the regression analysis. Third, a Renewable Energy Generation Assessment System(REGAS) including D/B of recorded actual generation data and historical resources is developed using the model and algorithm predicting one day-ahead power output of renewable energy generators.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.229-229
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• 2016

현재 국내외에서 제공되고 있는 기후변화 시나리오 자료의 경우 일단위로 제공되고 있다. 그러나 수자원 설계 및 계획 시 중요한 입력자료 중 하나는 시간단위 강우 자료이다. 이러한 시간단위 자료는 강우-유추 분석, 댐 설계 및 위험도 분석에 있어 중요한 입력 변수중 하나이므로 기후변화 시나리오에 따른 영향을 평가하기 위해선 신뢰성 있는 상세화 기법이 필요하다. 국내외에서는 일단위에서 일단위로 상세화 하는 기법, 또는 공간상세화 기법 연구는 상당히 진행된바 있는 반면, 시간단위 상세화 기법 연구는 일단위 연구에 비해 상대적으로 미진한 실정이다. 즉 일단위 상세화 기법의 경우 Weather generator, Weather typing 등 다양한 기법이 존재하고 이를 활용한 연구사례가 많지만, 시간단위 상세화 기법의 Poisson 기법을 활용한 사례가 다수 존재하였다. 이러한 이유로 본 연구에서는 기후변화 시나리오에 따른 영향을 평가하기 위해 Bayesian 기법을 도입하여 신뢰성 있는 시간단위 강우량을 생성할 수 있는 모형을 개발하였으며, 연대별로 산정된 결과는 빈도해석을 통해 미래 확률강우량을 제시하였다. 본 연구에서 제안하고자 하는 Bayesian Copula 모형은 기존 주변확률분포(marginal distribution) 매개변수와 Copula 매개변수 추정시 각각 다른 기법을 활용하여 추정하며, 각각 모형에서 발생하는 불확실성은 추정하지 못하는 반면, Bayesian Copula 모형의 경우 매개변수의 사후분포를 정량적으로 제시할 수 있으며, 추정되는 확률강우량 역시 불확실성을 정량적으로 산정할 수 있는 장점을 확인할 수 있었다.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.185-193
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• 2004

The main purpose of this study is to investigate and evaluate the impact of climate change on the runoff and water resources of Yongdam basin. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONV 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.

• Current Research on Agriculture and Life Sciences
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• v.30 no.2
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• pp.97-104
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• 2012

Over the last century, drainage systems have become an integral component of agriculture. Climate observations and experiments using General circulation models suggest an intensification of the hydrologic cycle due to climate change. This study presents hydrologic simulations assessing the potential impact of climate change on subsurface drainage in Daegu, Republic of Korea. Historical and Long Ashton Research Station weather generator perturbed future climate data from 15 general circulation models for a field in Daegu were ran into a water management simulation model, DRAINMOD. The trends and variability in rainfall and Soil Excess Water ($SEW_{30}$) were assessed from 1960 to 2100. Rainfall amount and intensity were predicted to increase in the future. The predicted annual subsurface drainage flow varied from -35 to 40 % of the baseline value while the $SEW_{30}$ varied from -50 to 100%. The expected increases in subsurface drainage outflow require that more attention be given to soil and water conservation practices.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.1
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• pp.47-54
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• 2012

Agriculture is dependable to weather condition and its change so that it is necessary to understand the impacts of climatic change. The aim of this study is to analyze the change of consumptive use of water and rice yield due to climate change using CERES-Rice. In this study, the weather data of three emission scenario of A1B, A2 and B1 created from CGCM (Coupled General Circulation Model) were used from 2011 to 2100, and downscaled daily weather data were simulated using LARS-WG (Long Ashton Research Station Weather Generator). The input data for cultivated condition for simulating CERSE (Crop-Environment Resource Synthesis)-Rice were created referring to standard cultivation method of paddy rice in Korea. The results showed that consumptive uses of water for paddy rice were projected decreasing to 4.8 % (2025s), 9.1 % (2055s), 12.6 % (2085s) comparing to the baseline value of 403.5 mm in A2 scenario. The rice yield of baseline was 450.7 kg/10a and projected increasing to -0.4 % (2025s), 3.9 % (2055s), 17.5 % (2085s) in A1B scenario. The results demonstrated relationships between consumptive use of water and rice yields due to climate change and can be used for the agricultural water resources development planning and cultivation method of paddy rice for the future.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.107-114
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• 1999

The large-scale distribution of crops Is usually determined by climate. We present the results of a climate-crop prediction based on spatial bio-physical process model approach, implemented in a GIS (Geographic Information System) environment using several regional and global agriculture-environmental databases. The model utilizes daily climate data like temperature, rainfall, solar radiation being generated stocastically by in-built model weather generator to determine the daily biomass and finally the crop yield. Crops are characterized by their specific growing period requirements, photosynthesis, respiration properties and harvesting index properties. Temperature and radiation during the growing period controls the development of each crop. The model simulates geographic/spatial distribution of climate by which a crop-growing belt can also be determined. The model takes both irrigated and non-irrigated area crop productivity into account and the potential increase in productivity by the technical means like mechanization is not considered. All the management input given at the base year 1995 was kept same for the next twenty-year changes until 2015. The simulated distributions of crops under current climatic conditions coincide largely with the current agricultural or specific crop growing regions. Simulation with assumed weather generated derived climate change scenario illustrate changes in the agricultural potential. There are large regional differences in the response across the country. The north-south and east-west regions responded differently with projected climate changes with increased and decreased productivity depending upon the crops and scenarios separately. When water was limiting or facilitating as non-irrigated and irrigated area crop-production effects of temperature rise and higher $CO_2$ levels were different depending on the crops and accordingly their production. Rise in temperature led to yield reduction in case of maize and rice whereas a gain was observed for wheat crop, doubled $CO_2$ concentration enhanced yield for all crops and their several combinations behaved differently with increase or decrease in yields. Finally, with this spatial modeling approach we succeeded in quantifying the crop productivity which may bring regional disparities under the different climatic scenarios where one region may become better off and the other may go worse off.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.120-124
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• 2009

기후변화로 인한 사회, 경제, 자원, 환경, 수자원 등에 영향분석은 세계적인 연구 트렌드로 자리 잡고 있다. 다양한 모형들이 기후변화 영향을 효과적으로 평가하기 위해서 개발되고 있으나 주로 강우-유출 모형을 통한 유출의 변화 특성을 모의하는데 대부분의 연구가 초점을 맞추고 있다. 그러나 기본적으로 사용되는 강수량자료의 정확한 추정이 기후변화 연구에서 가장 중요하다고 해도 과언이 아니다. 이러한 관점에서 GCM 기후모형으로부터 유도된 기후변화 시나리오로부터 여러 단계로 가공하여 모형의 입력 자료로 사용하기 위한 강수량 자료를 생산하게 된다. 이러한 과정을 총칭해서 Downscaling이라고 한다. 본 연구에서는 기후모형으로 얻은 정보를 유역단위의 수문시나리오로 변환하기 위한 통계학적 Downscaling의 연구이론 변천 상황을 종합적으로 검토하고 각 모형이 갖는 장단점을 분석하고자 한다. 즉, Weather Generator, Single-site Nonstationary Markov Chain, Multi-site Nonstationary Markov Chain, Multi-site Weather State Based Markov Model 등 다양한 모델의 변화 및 진보 과정을 살펴보고 실제 국내 유역에 적용하여 모형의 타당성을 평가해보고자 한다. 이를 위해 IPCC 기후변화 시나리오를 활용하였으며 일강수량자료계열의 특성치, 극치수문량 변동특성 등 기후변화에 따른 영향분석을 일부 실시하여 분석하였다.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1178-1179
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• 2008

This paper describes a modeling of fixed speed wind power generation system which comprise of wind turbine, generator and grid. The wind turbine is based on MOD-2, which is IEEE standard wind turbine, and includes a component using wind turbine characteristic equation. Fixed speed induction generator is directly connected to grid, so the variation of wind speed has effects on the electrical torque and electrical output power. Therefore the power control mode pitch control system is necessary for aerodynamic control of the blades. But the power control mode does not operate at the fault condition. So it is required some methods to control the rotor speed at transient state for stabilization of wind power system. In this paper, simulation model of a fixed speed wind power generation system based on the PSCAD/EMTDC is presented and implemented under the real weather conditions. Also, a new pitch control system is proposed to stabilize the wind power system at the fault condition. The validity of the stabilization method is demonstrated with the results produced through sets of simulation.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.243-248
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• 2014

Recently, solar energy is expanding to combination of computing in real time by tracking the position of the sun to estimate the angle of inclination and make up freshly correcting a part of the solar radiation. Solar power is need that reliably linked technology to power generation system renewable energy in order to efficient power production that is difficult to output predict based on the position of the sun rise. In this paper, we analysis of prediction model for solar power generation to estimate the predictive value of solar power generation in the development of real-time weather data. Photovoltaic power generation input the correction factor such as temperature, module characteristics by the solar generator module and the location of the local angle of inclination to analyze the predictive power generation algorithm for the prediction calculation to predict the final generation. In addition, the proposed model in real-time national weather service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.279-283
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• 2008

국외를 중심으로 기존 GCM보다 해상도가 높은 Regional Climate Model(RCM)을 이용한 분석이 일부 시행되고 있으나, 국내에서는 이를 이용한 연구가 아직 미비한 실정이다. 이러한 관점에서 본 연구에서는 27km의 해상도를 갖는 기상청 RegCM3 RCM에서 도출된 기후변화 SRES 시나리오 자료를 이용하고자 한다. 수자원의 장기 거동을 강우-유출 모형으로 모사하기 위해서는 입력 자료인 일 강수자료 계열을 모의발생이 필요하며 본 연구에서는 천이확률 및 강수 모의에 이용되는 Gamma 확률분포와 같은 분포형의 매개변수들이 외부 인자 즉 기후변화 시나리오에 따라 조건부로 변동할 수 있는 CWGEN(Cross-validated Canonical Correlation Analysis-Weather Generator) 강수 모의기법을 도입하여 이용하였다. RCM 자료 그 자체는 일반적으로 시 공간적으로 왜곡되어 있어 Quantile Mapping을 통하여 수정을 하였다. 최종적으로 모의된 결과를 바탕으로 기후변화에 따른 극치사상들에 대한 정량적인 거동을 추정하고 평가하였다.