• 설비공학논문집
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• 제28권12호
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• pp.467-476
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• 2016

As the energy saving issues become one of the important global agenda, the building simulation method is generally used to predict the inside energy usage to establish the power-saving strategies. To foretell an accurate energy usage of a building, proper and typical weather data are needed. For this reason, typical weather data are fundamental in building energy simulations and among the meteorological factors, the solar irradiation is the most important element. Therefore, preparing solar irradiation is a basic factor. However, there are few places where the horizontal solar radiation in domestic weather stations can be measured, so the prediction of the solar radiation is needed to arrive at typical weather data. In this paper, four solar radiation prediction models were analyzed in terms of their applicability for domestic weather conditions. A total of 12 regions were analyzed to compare the differences of solar irradiation between measurements and the prediction results. The applicability of the solar irradiation prediction model for a certain region was determined by the comparisons. The results were that the Zhang and Huang model showed the highest accuracy (Rad 0.87~0.80) in most of the analyzed regions. The Kasten model which utilizes a simple regression equation exhibited the second-highest accuracy. The Angstrom-Prescott model is easily used, also by employing a plain regression equation Lastly, the Winslow model which is known for predicting global horizontal solar irradiation at any climate regions uses a daily integration equation and showed a low accuracy regarding the domestic climate conditions in Korea.

• 설비공학논문집
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• 제14권12호
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• pp.1084-1091
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• 2002

In general, flat-plate solar collectors are generally fixed in place at some angles. The most common method is to orient solar collectors toward the true south, where variations up to 15 degrees east or west are acceptable and the tiIt angle of the collectors is calculated from latitude and different heating applications. However, the best angle of flat-plate collectors depends upon whether the dominant load occurs in the winter, summer, or evenly all year. Moreover, this setting angle must consider the average insolation characteristics of the region exactly. In this study, the setting angle of flat-plate solar collectors is presented for Busan area by using domestic typical meteorological year weather data, so that the fixed flat-plate solar collectors must be set as quantitatively as possible.

• 한국태양에너지학회 논문집
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• 제37권6호
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• pp.79-91
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• 2017

The meteorological data of 1 hour interval are required to write a typical weather data for building energy simulation. However, many meterological data are missing and the interpolation method to recover the missing data is required. Especially, lots of meterological data are replicated by linear interpolation method because the changes are not significant. While, the wind velocity fluctuates with the time or locations, so linear interpolation method is not appropriate in interpolation of the wind velocity data. In this study, three interpolation methods, using surrounding wind velocity data, Inverse Distance Weighting (IDW), Revised Inverse Distance Weighting (IDW-r), were analyzed considering the characteristics of wind velocity. The Revised Inverse Distance Weighting method, proposed in this study, showed the highest reliability in restoration of the wind velocity data among the analyzed methods.

• 한국통신학회논문지
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• 제25권6B호
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• pp.1120-1126
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• 2000

Recently, in order to analyze the time series problems that occur in the nature word, and analyzing method using a neural electric network is being studied more than a typical statistical analysis method. A neural electric network has a generalization performance that is possible to estimate and analyze about non-learning data through the learning of a population. In this paper, after collecting weather datum that was collected from 1987 to 1996 and learning a population established, it suggests the weather forecasting system for an estimation and analysis the future weather. The suggested weather forecasting system uses 28*30*1 neural network structure, raises the total learning numbers and accuracy letting the selecting concentration learning about the pattern, that is not collected, using the descending epsilon learning method. Also, the weather forecasting system, that is suggested through a comparative experiment of the typical time series analysis method shows more superior than the existing statistical analysis method in the part of future estimation capacity.

• 한국태양에너지학회 논문집
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• 제32권3호
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• pp.123-128
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• 2012

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design. The purpose of our work is to predict the surface temperature on inclined surfaces based on ISO-TRY typical weather data. To reach this goal, three studies were performed. They consisted of quantifying the accuracy of various well-known three models. The first type of models calculated diffuse horizontal irradiations from global ones and the second type models computed global irradiations on inclined planes from diffuse and global components on a horizontal surface. The third type of model calculated long-wave radiation and surface temperature from ISO-TRY typical weather data. The proposed model can provide an alternative to building designers in estimating the surface temperature and solar irradiation on inclined surfaces where only the typical meteorological data are available.

• 대한설비공학회지:설비저널
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• 제14권2호
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• pp.125-137
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• 1985

Standard weather data for Seoul has been developed for use in computer calculations for energy requirements, and the 8760 sequential hourly values for seven weather elements have been placed in magnetic tape and cards. Applying the method determining average month, developed by Japanese Society of Heating, Air-Conditioning and Sanitary Engineers, the standard year data have been selected from the monthly average values for three weather elements during the 10year period of 1971 through 1980. The followings are obtained. 1. The Test Reference Year, consisting of 12 months chosen from different calendar years, has been determined, and TRY tape which contains seven weather elements has been prepared. 2. The Typical Weather Year, which means a year close to the average value, is the year of 1978 during the above 10 year period. 3. During the period, Winter Season needs the maximum heating load is from Dec. 1976 to Mar. 1977 and Summer Season needs the maximum cool ins load is from Jun. to Sep, 1978.

• 한국태양에너지학회 논문집
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• 제29권3호
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• pp.66-72
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• 2009

As 'Low Carbon Green Building' is highly required, programs to evaluate building performance are actively and commonly used. For most of these programs, dynamic responses of buildings against external weather changes are very important. In order to simulate the programs, weather data of each region must be properly entered to estimate accurate amount of building energy consumption. To this end, the existing weather data and weather data of KSES were compared and analyzed to find out how weather changes. Energy load of Korea's standard houses was also analyzed based on this data. As a result, data corresponding to June ${\sim}$ September when cooling is supplied shows 23% of average increase with 30% of peak increase(June). On the other hand, data corresponding to November ${\sim}$ February when heating is supplied shows 29% of average decrease with 34% of peak decrease(November). Increase in cooling load and decrease in heating load in the above data comparison/analysis show that KSES 2009 data reflects increase in average temperature caused by global warming unlike the existing data. Increase in dry-bulb temperature depending on weather change of standard houses increases cooling load by 17% and decreases heating load by 36%

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2008년도 추계학술발표대회 논문집
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• pp.202-207
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• 2008

Measures for coping with energy shortage are being sought all over the world. Following such a phenomenon, effort to use less energy in the design of buildings and equipment are being conducted. In particular, a program to evaluate the performance of a building comes into the spotlight. However. indispensable standard wether data to estimate the exact energy consumption of a building is currently unprepared. Thus, after appling standard weather data for four weather factors which were used in previous researches to Visual DOE 4.0, we compared it with the result of the existing data and evaluated them. For the monthly cooling and heating load of our target building, we used revised data for June, July, August, and September during which cooling load is applied. When not the existing data but the revised data was used, the research shows that an average of 14.9% increased in June, August, and September except for July. Also, in a case of heating load, the result by the revised data shows a reduction of an average of 11.9% from October to April during which heating load is applied. In particular, the heating loads of all months for which the revised data was used were more low than those of the existing data. In the maximum cooling and heating load according to load factors, the loads by residents and illumination for which the revised data was used were the same as those of the existing data, but the maximum cooling loads used by the two data have a difference in structures such as walls and roofs. Through the above results, the research cannot clearly grasp which weather data influences the cooling and heating load of a building. However, in the maximum loads by the change of weather data in four factors (dry-bulb temperature, web-bulb temperature, cloud amount, and wind speed) among 14 weather factors, the research shows that 5.95% in cooling load and 27.56% in heating load increased, and these results cannot be ignored. In order to make weather data for Performing energy performance evaluation for future buildings, the flow of weather data for the Present and past should be obviously grasped.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2009년도 추계학술발표대회 논문집
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• pp.330-335
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• 2009

kDomestic studies on meteorologicaldata have been carried out, however they were mostly not constant but limited to fragment compilation. The studies on solar energy, among others, have been relatively active but the measurement of solar irradiance is also limited to some extent. This study, in an effort to identify the difference in data between solar radiance and cloud cover, was intended to compare and analyze the typical meteorological data developed by Korean Solar Energy Society with the solar irradiance calculated using the typical meteorological data and cloud cover data provided by current simulation program. Monthly average solar irradiance from the meteorological data (ISO TRY) of Korea's typical meteorological data which was actuallymeasured appeared to be far below the monthly solar irradiance from the American Department of Energy. The solar irradiance calculated based on cloud cover indicates very limited difference between the two data, so the solar irradiance measured by Korean typical metrologicaldata (ISO TRY) indicated the similar value, which demonstrates the solar irradiance data from Korean Meteorological Administration is more accurate than those US National Weather Center.

• Current Photovoltaic Research
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• 제5권1호
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• pp.38-42
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• 2017

PV system output is determined according to the weather conditions, the azimuth and tilt angle. Weather conditions are changing every moment and it seems to vary according to the daily, monthly, and annual basis. The azimuth and tilt angle is decided along the site conditions for the PV system installation. This paper analyzed the PV system output through the changing the weather conditions, the azimuth, and tilt angle. We compared the TMY data and analysis of the two major weather institutes which are KMA and METEONORM. PV system output trend were analyzed by changing the azimuth and tilt angle. We used simulation tool, which is named PVsyst for the entire PV system analysis.