• Journal of the Korean Solar Energy Society
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• 제29권5호
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• pp.81-87
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• 2009

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design.. Building designers often now predict the performance of buildings simulation programmes that require hourly weather data. However, not all weather stations provide hourly data. Climate prediction models such as HadCM3 also provide the daily average dry bulb temperature as well as the maximum and minimum. Hourly temperature values are available for building thermal simulations that accounts for future changes to climate. In order to make full use of these predicted future weather data in building simulation programmes, algorithms for downscaling daily values to hourly values are required. This paper describes a more accurate method for generating hourly temperature values in the South Korea that uses all three temperature parameters from climate model. All methods were evaluated for accuracy and stability in terms of coefficient of determination and cumulative error. They were compared with hourly data collected in Seoul and Ulsan, South Korea.

• Journal of The Korean Society of Agricultural Engineers
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• 제58권5호
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• pp.59-69
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• 2016

This study aims to evaluate the Soil and Water Assessment Tool (SWAT) hourly hydrological modeling performance and compare it with daily SWAT modeling parameters. For the Byeolmicheon catchment ($1.17km^2$) located in the upstream of Gyeongancheon watershed and total 18 storm events measured during 3 years (2011-2013), the hourly SWAT was calibrated and validated using the Green and Ampt (G&A) infiltration equation. The determination coefficient ($R^2$) and Nash-Sutcliffe model efficiency (NSE) of hourly SWAT discharge were 0.81 and 0.73 respectively, and the most sensitive parameter was soil saturated hydraulic conductivity (SOL_K) and calibrated with the average value of 0.075 mm/hr. In addition, the hourly SWAT simulation by G&A was compared with the daily SWAT simulation by SCS-CN (Soil Conservation Service-Curve Number) method for the whole 3 years period. The houlrly G&A results showed $R^2$ and NSE of 0.71 and 0.50, and the daily SCS-CN results were 0.71 and 0.66, respectively. The SOL_K by daily SCS_CN method was calibrated at 75.5 mm/hr, 1,000 times greater than the hourly G&A method. The next sensitive parameters for the hourly simulation were lag time of lateral flow (LAT_TIME) and lag time of surface runoff (SURLAG).

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.501-504
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• 2008

A non-homogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrological variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1548-1555
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• 2016

This paper presents an application of time series analysis in hourly wind speed simulation and forecast in Jeju Island, Korea. Autoregressive - moving average (ARMA) model, which is well in description of random data characteristics, is used to analyze historical wind speed data (from year of 2010 to 2012). The ARMA model requires stationary variables of data is satisfied by power law transformation and standardization. In this study, the autocorrelation analysis, Bayesian information criterion and general least squares algorithm is implemented to identify and estimate parameters of wind speed model. The ARMA (2,1) models, fitted to the wind speed data, simulate reference year and forecast hourly wind speed in Jeju Island.

• Proceedings of the KIEE Conference
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.495-497
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• 1992

Hourly load forecasting has become indispensable for practical simulation of electric power system as the system become larger and more complicated. To forecast the future hourly load the cyclic behavior of electric load which follows seasonal weather, day or week and office hours is to be analyzed so that the trend of the recent behavioral change can be extrapolated for the short term. For the long term, on the other hand, the changes in the infra-structure of each electricity consumer groups should be assessed. In this paper the concept and process of hourly load forecasting for hourly load is introduced.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2015년도 학술발표회
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• pp.247-247
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• 2015

Global Climate Model (GCM) is too coarse to apply at a basin scale. The spatial downcsaling is needed to used to permit the assessment of the hydrological changes of a basin. Furthermore, temporal downscaling is required to obtain hourly precipitation to analyze a small or medium basin because only few or several hours are used to determine the peak flows after it rains. In the current study, the spariotemporal distribution of downscaled hourly precipitation for RCP4.5 and RCP8.5 scenarios over South Korea is presented as well as its implications over hydrologica responses. Mean hourly precipitation significantly increases over the southern part of South Korea, especially during the morning time, and its increase becomes lower at later times of day in the RCP8.5 scenario. However, this increase cannot be propagated to the mainland due to the mountainous areas in the southern part of the country. Furthermore, the hydrological responses employing a distributed rainfall-runoff model show that there is a significant increase in the peak flow for the RCP8.5 scenario with a slight decrease for the RCP4.5 scenario. The current study concludes that the employed temporal downscaling method is suitable for obtaining the hourly precipitation data from daily GCM scenarios. In addition, the rainfall runoff simulation through the downscaled hourly precipitation is useful for investigating variations in the hydrological responses as related to future scenarios.

• Journal of Korea Water Resources Association
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• 제35권6호
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• pp.763-777
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• 2002

The objective of this study is to develop computer simulation model that produces precipitation patterns from stochastic model. The hourly precipitation process consists of the precipitation occurrence and precipitation amounts. In this study, an event cluster model developed by Lee and Lee(2002) is used to describe the occurrence process of events, and the hourly precipitation amounts within each event is described by a nonstationary form of a first-order autoregressive process. The complete stochastic model for hourly precipitation is fitted to historical precipitation data by estimating the model parameters. An analysis of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many of the features of historical precipitation. The autocorrelation coefficients of the historical and simulated data are nearly identical except for lags more than about 3 hours. The precipitation intensity, duration, marginal distributions, and conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.

• Journal of The Korean Society of Agricultural Engineers
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• 제66권4호
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• pp.51-57
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• 2024

This study was conducted on how to simulate runoff, which was done using existing physical models, using an LSTM (Long Short-Term Memory) model based on deep learning. Tancheon, the first tributary of the Han River, was selected as the target area for the model application. To apply the model, one water level observatory and four rainfall observatories were selected, and hourly data from 2020 to 2023 were collected to apply the model. River water level of the outlet of the Tancheon basin was simulated by inputting precipitation data from four rainfall observation stations in the basin and average preceding 72-hour precipitation data for each hour. As a result of water level simulation using 2021 to 2023 data for learning and testing with 2020 data, it was confirmed that reliable simulation results were produced through appropriate learning steps, reaching a certain mean absolute error in a short period time. Despite the short data period, it was found that the mean absolute percentage error was 0.5544~0.6226%, showing an accuracy of over 99.4%. As a result of comparing the simulated and observed values of the rapidly changing river water level during a specific heavy rain period, the coefficient of determination was found to be 0.9754 and 0.9884. It was determined that the performance of LSTM, which aims to simulate river water levels, could be improved by including preceding precipitation in the input data and using precipitation data from various rainfall observation stations within the basin.

• Solar Energy
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• 제12권1호
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• pp.15-24
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• 1992

An hourly simulation model of a solar LiBr-water absorption cooling and heating system (for brevity, solar absorption system) is presented, based on SuperCalc spreadsheet computational procedures. This paper demonstrates the value of using spreadsheet simulation techniques by examining the thermal performances of a solar absorption system. The hourly heating and cooling coil loads for a typical office building in Tucson, Arizona are modeled and calculated using ASHRAE methods. The details of the algorithms for the components and control schemes are presented. Two case studies are also presented using real system parameters.

• KIEAE Journal
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• 제14권2호
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• pp.3-10
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• 2014

Impact by estimation error of hourly horizontal global solar radiation in a weather file on building energy performance was investigated in this study. There are a number of weather parameters in a given weather file, such as dry-bulb, wet-bulb, dew-point temperatures; wind speed and direction; station pressure; and solar radiation. Most of them except for solar radiation can be easily obtained from weather stations located on the sites worldwide. However, most weather stations, also including the ones in South Korea, do not measure solar radiation because the measuring equipment for solar radiation is expensive and difficult to maintain. For this reason, many researchers have studied solar radiation estimation models and suggested to apply them to predict solar radiation for different weather stations in South Korea, where the solar radiation is not measured. However, only a few studies have been conducted to identify the impact caused by estimation errors of various solar radiation models on building energy performance analysis. Therefore, four different weather files using different horizontal global solar radiation data, one using measured global solar radiation, and the other three using estimated global solar radiation models, which are Cloud-cover Radiation Model (CRM), Zhang and Huang Model (ZHM), and Meteorological Radiation Model (MRM) were packed into TRY formatted weather files in this study. These were then used for office building energy simulations to compare their energy consumptions, and the results showed that there were differences in the energy consumptions due to these four different solar radiation data. Additionally, it was found that using hourly solar radiation from the estimation models, which had a similar hourly tendency with the hourly measured solar radiation, was the most important key for precise building energy simulation analysis rather than using the solar models that had the best of the monthly or yearly statistical indices.