• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.12
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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.

• New & Renewable Energy
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• v.20 no.1
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• pp.102-109
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• 2024

The Typical Meteorological Year (TMY) dataset compiles 12 months of data that best represent long-term climate patterns, focusing on global horizontal irradiance and other weather-related variables. However, the irradiance measured on the plane of the array (POA) shows certain distinct distribution characteristics compared with the irradiance in the TMY dataset, and this may introduce some biases. Our research recalculated POA irradiance using both the Isotropic and DIRINT models, generating an updated dataset that was tailored to POA characteristics. Our analysis showed a 28% change in the selection of typical meteorological months, an 8% increase in average irradiance, and a 40% reduction in the range of irradiance values, thus indicating a significant shift in irradiance distribution patterns. This research aims to inform stakeholders about accurate use of TMY datasets in potential decision-making. These findings underscore the necessity of creating a typical dataset by using the time series of POA irradiance, which represents the orientation in which PV panels will be deployed.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.943-960
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• 2009

This study suggests an algorithm for generating TMY(typical meteorological year) for the Korean peninsula, and generates the TMY based on the algorithm using 11 years(1998~2008) wind data observed at 77 sites of Regional Meteorological Offices(RMO). The algorithm consists of computing TMM scores based on the various statistics defined by the Fikenstein-Shafer statistical model and, in turn, generating TMY based on the TMM scores. Also the algorithm has two stages designed to yield the best representation of the regional wind characteristics appeared during the 11 years(1998~2008). The first stage is designed for the representation of each of 77 regions of RMO and the second is for the Korean peninsula. Various comparison studies are provided to demonstrate the properties of the TMY like its utility and typicality.

• New & Renewable Energy
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• v.20 no.1
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• pp.95-101
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• 2024

Since 1990, the Renewable Big Data Research Lab at the Korea Institute of Energy Technology has been observing solar radiation at 16 sites across South Korea. Serving as the National Reference Standard Data Center for Renewable Energy since 2012, it produces essential data for the sector. By 2020, it standardized meteorological year data from 22 sites. Despite user demand for data from approximately 260 sites, equivalent to South Korea's municipalities, this need exceeds the capability of measurement-based data. In response, our team developed a method to derive solar radiation data from satellite images, covering South Korea in 400,000 grids of 500 m × 500 m each. Utilizing satellite-derived data and ERA5-Land reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), we produced standard meteorological year data for 1,000 sites. Our research also focused on data measurement traceability and uncertainty estimation, ensuring the reliability of our model data and the traceability of existing measurement-based data.

• Journal of Institute of Convergence Technology
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• v.9 no.1
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• pp.31-36
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• 2019

After 30 years of KKP model analysis and extended 30 years of accuracy analysis, the unique correlation and various problems between measured horizontal surface insolation and measured weather data are found in this paper. The KKP model's 10yrs daily total horizontal surface insolation forecasting was averaged about 97.7% on average, and the forecasting accuracy at peak times per day was about 92.1%, which is highly applicable regardless of location and weather conditions nationwide. The daily total solar radiation forecasting accuracy of the modified KKP cloud model was 98.9%, similar to the KKP model, and 93.0% of the forecasting accuracy at the peak time per day. And the results of evaluating the accuracy of calculation for 30 years of KKP model were cloud model 107.6% and cloud model 95.1%. During the accuracy analysis evaluation, this study found that inaccuracies in measurement data of cloud cover should be clearly assessed by the Meteorological Administration.

• Current Photovoltaic Research
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• v.5 no.1
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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.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.3
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• pp.177-190
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• 1998

The concentrations of air pollutants In large cities such as Pusan area have been increased every year due to the increasing of fuels consumption at factories and by vehicles as well as the gravitation of the population. In addition to the pollution sources, time and spatial variation of air pollutants concentration and meteorological factors have a great influence on the air pollution problem. Especially , its concentration is governed by wind direction, wind speed, precipitation, solar radiation, temperature, humidity and cloud amounts, etc. In this study, we have analyzed various data of meteorological factors using typical patterns of the air pressure to investigate how the concentration of air pollutants is varied with meteorological condition. Using the relationship between meteorological factors (air temperature, relative humidity, wind speed and solar radiation) and the concentration of air pollutants (SO2, O3) , experimental prediction formulas for their concentration were obtained. Therefore, these prediction formulas at each meteorological factor in a pressure pattern may be roughly used to predict the air pollutants concentration and contributed to estimate the variation of its value according to the weather condition in Pusan city.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.1
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• pp.70-81
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• 2010

A mathematical model is formulated to study the effect of wall mass on the thermal performance of four different houses of different construction. This analytical study was motivated by the experimental work of Burch et al. An analytical solution of one -dimensional, linear, partial differential equation for wall temperature profiles and room air temperatures is obtained using the Laplace transform method. Typical Meteorological Year data are processed to yield hourly average monthly values. These discrete data are then converted to a continuous, time dependent form using a Fast Fourier Transform method. This study is conducted using weather data from four different locations in the United States: Albuquerque, New mexico; Miami, Florida; Santa Maria, California; and Washington D.C. for both winter and summer conditions. A computer code is developed to calculate the wall temperature profile, room air temperature, and energy consumption loads. Three sets of results are calculated one for no auxiliary energy and two for different control mechanism -- an on-off controller and a proportional controller. Comparisons are made for the cases of two controllers. Heavy weight houses with insulation in mild weather areas (such as August in Santa Maria, California) show a high comfort level. Houses using proportional control experience a higher comfort level in comparison to houses using on-off control. The result shows that there is an effect of mass on the thermal performance of a heavily constructed house in mild weather conditions.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.48 no.1
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• pp.82-90
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• 2012

Four different buildings having various wall construction are analyzed for the effect of wall mass on the thermal performance and inside building air and wall temperature transient and also for calculating the energy consumption load. This analytical study was motivated by the experimental work of Burch et al. An analytical solution of one-dimensional, linear, partial differential equations is obtained using the Laplace transform method, Bromwich and modified Bromwich contour method. A simple dynamic model using steady state analysis as simplified methods is developed and results of energy consumption loads are compared with results obtained using the analytical solution. Typical Meteorological Year data are processed to yield hourly average monthly values. This study is conducted using weather data from two different locations in Korea: Daegu having severe weather in summer and winter and Jeju having mild weather almost all year round. There is a significant wall mass effect on the thermal performance of a building in mild weather condition. Buildings of heavyweight construction with insulation show the highest comfort level in mild weather condition. A proportional controller provides the higher comfort level in comparison with buildings using on-off controller. The steady state analysis gives an accurate estimate of energy load for all types of construction. Finally, it appears that both mass and wall insulation are important factors in the thermal performance of buildings, but their relative merits should be decided in each building by a strict analysis of the building layout, weather conditions and site condition.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.47 no.1
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• pp.46-58
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• 2011

A steady-state analysis and a simple dynamic model as simplified methods are developed, and results of energy consumption loads are compared with results obtained using computer to evaluate the analytical solution. Before obtaining simplified model a mathematical model is formulated for the effect of wall mass on the thermal performance of four different houses having various wall construction. This analytical study was motivated by the experimental work of Burch et al. An analytical solution of one-dimensional, linear, partial differential equation for wall temperature profiles and room air temperatures is obtained using the Laplace transform method. Typical Meteorological Year data are processed to yield hourly average monthly values. This study is conducted using weather data from four different locations in the United States: Albuquerque, New mexico; Miami, Florida; Santa Maria, California; and Washington D.C. for both winter and summer conditions. The steady state analysis that does not include the effect of thermal mass can provide an accurate estimate of energy consumption in most cases except for houses #2 and #4 in mild weather areas. This result shows that there is an effect of mass on the thermal performance of heavily constructed house in mild weather conditions. The simple dynamic model is applicable for high cycling rates and accurate values of inside wall temperature and ambient air temperature.