• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.243-246
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• 2009

To evaluate the building energy performance, many building simulation programs are used and its capabilities are developed. Despite of its increased capabilities the weather data used In the Building Energy performance evaluation, are still using the same limited set of data. This often forces users to find or calculate weather data such as illuminance, solar radiation, and ground temperature from other sources to calculate it. Also, proper selection of a right weather data set has been considered as one of important factors for a successful building energy simulation. In this paper, we describe TMY2 data, a generalized weather data format developed for use, and applied to Seoul region and examine the differences comparing to existing weather data. A set of 23 years raw weather data base has been developed to provide the weather data file for building energy analysis in Seoul.

• New & Renewable Energy
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• v.8 no.2
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• pp.14-23
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• 2012

The TMY (Typical Meteorological Year) for the solar energy study is generated using observation data with 22 solar sites from KMA (Korea Meteorological Administration) during 11 years (2000-2010). The meteorological data for calculation the TMY are used solar radiation, temperature, dew point temperature, wind speed and humidity data. And the TMY is calculated to apply the FS (Finkelstein and Schafer) statistics and RMSE (Root Mean Squared Error) methods. FS statistics performed with each point and each variable and then selected top five candidate TMM months with statistical analysis and normalization. Finally TMY is generated to select the highest TMM score with evaluation the average errors for the 22 whole points. The TMY data is represented average state and long time variations with 22 sites and meteorological data. When TMY validated with the 11-year daily solar radiation data, the correlation coefficient was about 0.40 and the highest value is 0.57 in April and the lowest value is 0.23 in May. Mean monthly solar radiation of TMY is 411.72 MJ which is 4 MJ higher than original data. Average correlation coefficient is 0.71, the lowest correlation is 0.43 in May and the highest correlation is 0.90 in January. Accumulated annual solar radiation by TMY have higher value in south coast and southwestern region and have relatively low in middle regions. And also, differences between TMY and 11-year mean of is distributed lower 100 MJ in Kyeongbuk, higher 200 MJ in Jeju and higher 125 MJ in Jeonbuk and Jeonnam, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.8
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• pp.1119-1126
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• 2013

The objective of this study was to compare the goodness of fit of four lactation curve models: Wood's Gamma model (WD), Wilmink (WL), and Pollott's multiplicative two (POL2) and three parameters (POL3) and to determine the environmental factors affecting the complete lactation curve of F1 dairy sheep under organic management. A total of 5,382 weekly milk yields records from 150 ewes, under organic management were used. Residual mean square (RMS), determination coefficients ($R^2$), and correlation (r) analysis were used as an indicator of goodness of fit for each model. WL model best fitted the lactation curves as indicated by the lower RMS values (0.019), followed by WD (0.023), POL2 (0.025) and POL3 (0.029). The four models provided total milk yield (TMY) estimations that were highly correlated (0.93 to 0.97) with observed TMY (89.9 kg). The four models under estimated peak yield (PY), whereas POL2 and POL3 gave nearer peak time lactation estimations. Ewes lambing in autumn had higher TMY and showed a typical curve shape. Higher TMY were recorded in second and third lambing. Season of lambing, number of lambing and type of lambing had a great influenced over TMY shaping the complete lactation curve of F1 dairy sheep. In general terms WL model showed the best fit to the F1 dairy sheep lactation curve under organic management.

• Journal of Oriental Neuropsychiatry
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• v.25 no.2
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• pp.123-132
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• 2014

Objectives: The purpose of this study was to investigate the levels of Yangseng (Traditional Health Behavior), depression, anxiety, cognitive function between the elderly women living alone and the aged in the living with family. Methods: The subjects of this study were 137 elderly women aged between 65 and 80. They were evaluated with the Tool in Measuring Yangseng (TMY), Korean Geriatric Depression Scale (KGDS), State-Trait Anxiety Inntory (STAI) and Korean of the Mini-Mental State Examination (MMES-K). Depending on whether or not they lived alone, they were divided into two groups; group living alone (L.A.) and group living with family (L.F.). Results: In TMY score, there were statistically significant differences in characteristics of Mind, Diet, Sleep and total score between L.A. (63 persons) and L.F. (74 persons). Group living alone (L.A.) had significantly higher score in KGDS and STAI compared with other group (L.F.). The values of KGDS and STAI comparing to the values of Mind, Diet, Sleep, Exercise and total score in this study resulted in negative correlations which showed statistically significant. Conclusions: Above results suggest that between L.A. and L.F, there are significant difference in physical and mental health. TMY is enough to estimate health of the aged. These results can be used for Yangseng health promoting program based on Korean traditional medicine.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1157-1167
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• 2010

This paper details a method for establishing a wind energy map having($1Km{\times}1Km$) resolution. The map is essential for measurement and efficiency-testing of wind energy resources and wind site analysis. To this end, a statistical wind field model is estimated that covers 345,682 regions obtained by $1Km{\times}1Km$ lattices made over South Korea. The paper derives various characteristics of a regional wind energy resource under the statistical wind field model and estimates them to construct the wind energy map. Kolmogorov-Smirnov test, based on TMY(typical meteorological year) wind data of 76 weather station areas, shows that a Log-normal model is adequate for the statistical wind field model. The model is estimated by using the wind speed data of 345,682 regions provided by the National Institute of Meteorological Research(NIMR). Various wind energy statistics are studied under the Log-normal wind field model. As an application, the wind energy density(W$/m^2$) map of South Korea is constructed with a resolution of $1Km{\times}1Km$ and its utility for the wind site analysis is discussed.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.3
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• pp.315-320
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• 2002

Test-day records (n=13677) sampled from 896 ewes in 5-9 (${\mu}$=7.5) monthly test-days were used to estimate genetic and phenotypic parameters of test-day yields, lactation milk yield (TMY), length of the milking period (DAYS) and three measures of persistency of milk yield in Boutsico dairy sheep. Τhe measures of persistency were the slope of the regression line (${\beta}$), the coefficient of variation (CV) of the test-day milk yields and the maximum to average daily milk yield ratio (MA). The estimates of variance components were obtained under a linear mixed model by restricted maximum likelihood. The heritability of test-day yields ranged from 0.15 to 0.24. DAYS were found to be heritable ($h^2$=0.11). Heritability estimates of ${\beta}$, CV and MA were 0.15, 0.13, 0.10, respectively. Selection for maximum lactation yields is expected to result in prolonged milking periods, high rates of decline of yields after peak production, variable test-day yields and higher litter sizes. Selection for flatter lactation curves would reduce lactation yields, increase slightly the length of the milking period and decrease yield variation as well as litter size. The most accurate prediction of TMY was obtained with a linear regression model with the first five test-day records.

• Journal of the Korean Solar Energy Society
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• v.32 no.2
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• pp.64-73
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• 2012

The angle of solar panels is calculated using solar radiation model for the efficient solar power generation. In ideal state, the time of maximum solar radiation is represented from 12:08 to 12:40 during a year at Gangneung and it save rage time is12:23. The maximum solar radiation is 1012$W/m^2$ and 708$W/m^2$ inc lear sky and cloudy sky, respectively. Solar radiation is more sensitive to North-South (N-S) slope angle than East-West (E-W) azimuth angle. Daily solar radiation on optimum angle of solar panel is higher than that on horizontal surface except for 90 days during summer. In order to apply to the real atmosphere, the TMY (typical meteorological Year) data which obtained from the 22 solar sites operated by KMA(Korea Meteorological Administration) during 11 years(2000 to 2010) is used as the input data of solar radiation model. The distribution of calculated solar radiation is similar to the observation, except in Andong, where it is overestimated, and in Mokpo and Heuksando, where it is underestimated. Statistical analysis is performed on calculated and observed monthly solar radiation on horizontal surface, and the calculation is overestimated from the observation. Correlationis 0.95 and RMSE (Root Mean Square Error) is10.81 MJ. The result shows that optimum N-S slope angles of solar panel are about $2^{\circ}$ lower than station latitude, but E-W slope angles are lower than ${\pm}1^{\circ}$. There are three types of solar panels: horizontal, fixed with optimum slope angle, and panels with tracker system. The energy efficiencies are on average 20% higher on fixed solar panel and 60% higher on tracker solar panel than compared to the horizontal solar panel, respectively.

• Journal of the Korean Solar Energy Society
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• v.39 no.3
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• pp.91-102
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• 2019

Decomposition models are essential in TMY development and solar energy system design. Up until recently, only a few decomposition model related researches are implemented in Korea due to lack of measured direct normal solar irradiance. In contrast, numerous researches have been conducted in various countries, and some quasi-universal composition models have been recommended by several papers. In this research, three decomposition models - Watanabe model, Reindl-2 model and Engerer1 model - are selected and their site-fitted coefficients are developed using measured direct normal solar irradiance in Seoul. R-squared, RMSE, MBE of the site-fitted models are compared with the case of original coefficients and then each other. The comparison result shows that the Reindl-2 model with site-fitted coefficients is best suitable for Seoul. Further researches will be conducted to find the best model using more various measured data of Korean cities and site-fitting methods.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.83-92
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• 2011

This study is about an analysis of surplus solar energy by important greenhouse type using Typical Meteorological Year (TMY) data which was secured in order to provide basic data for designing an optimum thermal storage system to accumulate surplus solar energy generated in greenhouses during the daytime. The 07-auto-1 and 08-auto-1 types showed similar heat budget tendencies regardless of greenhouse types. In other words, the ratios of surplus solar energy were about 20.0~29.0% regardless of greenhouse type. About 54.0~225.0% and 53.0~218.0% of required heating energy will be able to be supplemented respectively according to the greenhouse types. The 07-mono-1 and 07-mono-3 types also showed similar heat budget tendencies regardless of greenhouse types. In other words, the ratios of surplus solar energy were about 20.0~26.0% and 21.0~27.0% respectively by greenhouse type. About 57.0~211.0% and 62.0~228.0% of required heating energy will be able to be supplemented by greenhouse type. Except for Daegwallyeong and Suwon area, other regions can cover heating energy only by surplus solar energy, according to the study.

• KIEAE Journal
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• v.11 no.6
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• pp.101-108
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• 2011

The weather data has important role for performative building design. If the data location is close to building site, the result of performative design can be accurate. The data which have used nowadays in Korea are from U.S. Department of Energy (DOE) and Korea Solar Energy Society (KSES) but they cover only several locations in Korea which are 4 in DOE and 11 in KSES and there are opinions which it could be served building design efficiently even if the data are not enough. However the weather data for micro-climate are exist which are Green Building Studio Virtual Weather Station (GBS VWS) and Meteonorm weather data. Each weather data has different generation methods which are TMY2, TRY, MM5, and extrapolation. In this research, the weather date for climate are compared with DOE and KSES to check correlation. The result shows the value of correlation in Dry Bulb Temp. and Dew Point Temp. is around 0.9 so they have high correlation in both but in Wind Speed case the correlation(around 0.2) is not exist. In overall result, the data has correlation with DOE and KSES as the value of correlation 0.648 of GBS VW and 0.656 of Meteonorm. Even if the correlation value is not high enough, the patterns of difference in each weather element are similar in scatter plot.