• Journal of Mechanical Science and Technology
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• v.14 no.12
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• pp.1403-1411
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• 2000

Heat losses from the receivers for a dish-type solar energy collecting system constructed at Korea Institute of Energy Research are analyzed. The Stine and McDonald's model is used to estimate the convection loss. The Net Radiation method and the Monte-Carlo method are used to calculate the radiation heat transfer rate from the inside surface of the receiver to the surroundings. Two different receivers are suggested here and the performances of the receivers are estimated and compared with each other based on the prediction of the amount of heat losses from the receivers. The effects of the receiver shape and the radiation properties of the surface on the thermal performance are investigated. The performance of Receiver I is better than that of Receiver II, and the amount of solar irradiation that is not captured by the captured by the receiver after being reflected by the concentrator becomes significant if the temperature of the working fluid is low.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.569-575
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• 2021

Deep learning shows differences in prediction performance depending on data quality and model. This study uses various input data and multiple deep learning models to build an optimal deep learning model for predicting solar radiation, which has the most influence on power generation prediction. did. As the input data, the weather data of the Korea Meteorological Administration and the clairvoyant meteorological image were used by segmenting the image of the Korea Meteorological Agency. , comparative evaluation, and predicting solar radiation by constructing multiple deep learning models connecting the models with the best error rate in each model. As an experimental result, the RMSE of model A, which is a multiple deep learning model, was 0.0637, the RMSE of model B was 0.07062, and the RMSE of model C was 0.06052, so the error rate of model A and model C was better than that of a single model. In this study, the model that connected two or more models through experiments showed improved prediction rates and stable learning results.

• Journal of the Korean Solar Energy Society
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• v.30 no.2
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• pp.72-80
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• 2010

The main thrust of this paper is to investigate a practical way of generating the monthly averaged daily horizontal solar radiation in Korea. For estimating the horizontal solar radiation, the clearness index($K_T$) and the clearness number($C_N$) which are required for the use of Liu and Jordan's model and ASHRAE Clear Sky model were derived based on the measured weather data. Third-order polynomials returning $K_T$ and��$C_N$ for a given location were derived as a function of cloud amount, month, date, latitude and longitude. The predicted monthly averaged daily horizontal solar radiation values were compared with those acquired from the established design weather data. The MBE(Mean Bias Error) and RMSE (Root Mean Squares for Error) between the predicted values and the measured data were near zero. It means that the suggested third-order polynomials for $K_T$ and $C_N$ have good applicability to Liu and Jordan's model and ASHRAE Clear Sky model.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.565-572
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• 2009

Deterioration of the outdoor thermal environment in urban areas such as heat island has become worse due to urbanization and overpopulation, etc. In this study, a new method which is coupled simulation of convection and radiation to evaluate outdoor thermal environment in urban area will be proposed. Because the solar radiation affects on outdoor thermal environment massively, therefore the radiation calculation is very important in outdoor thermal environment prediction. The coupled simulation proposed in this study can assess the outdoor thermal environment with accurate.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.32.1-32.1
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• 2010

KASI's Solar and Space Weather Research Group (SSWRG) is actively involved in solar and space weather research. Since its inception, the SSWRG has been utilizing ground-based assets for its research, such as the Solar Flare Telescope, Solar Imaging Spectrograph, and Sunspot Telescope. In 2007 SSWRG initiated the Korean Space Weather Prediction Center (KSWPC). The goal of KSWPC is to extend the current ground observation capabilities, construct space weather database and networking, develop prediction models, and expand space weather research. Beginning in 2010, SSWRG plans to expand its research activities by collaborating with new international partners, continuing the development of space weather prediction models and forecast system, and phasing into developing and launching space-based assets. In this talk, we will report on KASI's recent activities of international collaborations with NASA for STEREO (Solar Terrestrial Relations Observatory), SDO (Solar Dynamic Observatory), and Radiation Belt Storm Probe (RBSP).

• Journal of the Korean Solar Energy Society
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• v.32 no.5
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• pp.11-17
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• 2012

In this study, a simulation program was developed with heat transfer model in the thermal storage tank for a solar collector and burner combined heating and hot water supply system. Analysis was conducted with variation of operating condition and schedule to analyze performance of a hot water supply and panel heating system with a solar collector and burner combined thermal storage tank. The simulation program is divided two sections. One part is calculation of temperature variation of water which flows through the panel in the floor for heating of the residential house during 24 hours, and the other part is heat transfer calculation for the reaction time to get desired water temperature in the thermal storage tank. As results, light oil consumption and system performance during operation period were analyzed with variation of climate condition and with or without solar collector. Most of the case, oil could be saved about from 24 to 41% with installing the solar collector. The performance of the system is more dependent on radiation time of the solar collector rather than the intensity of the solar radiation which was adopted for the climate 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 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.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.989-996
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• 2012

The purpose of this paper is to analyze GPS (Global Positioning System) satellite orbital mechanics, and then to propose a novel long-term GPS satellite orbit prediction scheme including virtual planet perturbation. The GPS orbital information is a necessary prerequisite to pinpointing the location of a GPS receiver. When a GPS receiver has been shut down for a long time, however, the time needed to fix it before its reuse is too long due to the long-standing GPS orbital information. To overcome this problem, the GPS orbital mechanics was studied, such as Newton's equation of motion for the GPS satellite, including the non-spherical Earth effect, the luni-solar attraction, and residual perturbations. The residual perturbations are modeled as a virtual planet using the least-square algorithm for a moment. Through the modeling of the virtual planet with the aforementioned orbital mechanics, a novel GPS orbit prediction scheme is proposed. The numerical results showed that the prediction error was dramatically reduced after the inclusion of virtual planet perturbation.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.1 s.151
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• pp.40-47
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• 2007

This study is focused on developing a software that predicts the temperature distribution and infrared Emission from 30 objects considering the solar radiation through the atmosphere. The solar radiation through the atmosphere is modeled by using the well-known LOWTRAN7 code. Surface temperature information is essential for generating the infrared scene of the object. Predictions of the transient surface temperature and the infrared emission from a naval ship by using the software developed here show fairly good results by representing the typical temperature and emitted radiance distributions expected for the naval ship considered in mid latitude. Emissivity of each material is appeared to be an important parameter for recognizing the target in Infrared band region. The numerical results also show that the low emissivity surface on the heat source can be helpful in reducing the IR image contrast as compared to the background sea.