• Journal of the Korean Solar Energy Society
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• v.32 no.5
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• pp.1-10
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• 2012

This paper proposes a modeling and controller design approach for a wind-diesel hybrid system including dump load. Wind turbine depends on nature such as wind speed. It causes power fluctuations of wind turbine. Excessive power fluctuation at stand-alone power grid is even worse than large-scale power grid. The proposed control scheme for power quality is fuzzy PI controller. This controller has advantages of PI and fuzzy controller. The proposed model is carried out by using Matlab/Simulink simulation program. In the simulation study, the proposed controller is compared with a conventional PI controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-diesel hybrid power system.

• Journal of Advanced Navigation Technology
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• v.22 no.4
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• pp.271-278
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• 2018

For ionospheric correction of low earth orbiter (LEO) satellites using single frequency global navigation satellite system (GNSS) receiver, ionospheric scale factor should be applied to the ground-based ionosphere model. The ionospheric scale factor can be calculated by using a NeQuick model, which provides a three-dimensional ionospheric distribution. In this study, the ionospheric scale factor is calculated by using NeQuick G model during 2015, and it is compared with the scale factor computed from the combination of LEO satellite measurements and international GNSS service (IGS) global ionosphere map (GIM). The accuracy of the ionospheric delay calculated by the NeQuick G model and IGS GIM with NeQuick G scale factor is analyzed. In addition, ionospheric delay errors calculated by the NeQuick G model and IGS GIM with the NeQuick G scale factor are compared. The ionospheric delay error variations along to latitude and solar activity are also analyzed. The mean ionospheric scale factor from the NeQuick G model is 0.269 in 2015. The ionospheric delay error of IGS GIM with NeQuick G scale factor is 23.7% less than that of NeQuick G model.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.147-154
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• 2008

A simulation program is developed for the optimal design of small scale district heating and cooling system. Main features for the simulation program are the reliability and the easiness for the optimal design of the DHC(District Heating and Cooling) systems. In order for implementing those features, the operational characteristics according to the prime movers is modeled based on the materials of efficiency as a function of operational load. The unit energy load model is also developed extensively for several building types, of which the corresponding district consist, such as apartment complex, hotel, hospital, buildings for business and commercial use respectively. The specific features and the overall procedure of the simulation are described in brief in this paper. The results of the simulation for several test cases will be presented in subsequent study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1777-1783
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• 2021

The use of drones is gradually increasing for the efficient maintenance of large-scale renewable energy power generation complexes. For a long time, photovoltaic panels have been photographed with drones to manage panel loss and contamination. Various approaches using artificial intelligence are being tried for efficient maintenance of large-scale photovoltaic complexes. Recently, semantic segmentation-based application techniques have been developed to solve the image classification problem. In this paper, we propose a classification model using semantic segmentation to determine the presence or absence of failures such as arcs, disconnections, and cracks in solar panel images obtained using a drone equipped with a thermal imaging camera. In addition, an efficient classification model was implemented by tuning several factors such as data size and type and loss function customization in U-Net, which shows robust classification performance even with a small dataset.

• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.256-262
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• 2009

Purpose of this study is embody the environmental-friendly military facility model that applied renewable energy, passive design method and high efficiency equipment. In the introduction of this study, defined problem of existing military facility and classification of military facility are performed. Also, environmental friendly military facility is defined through classified by scale and building equipment method. In the renewable energy chapter, photovoltaic system and wind turbine system are considered And then, LED light, photovoltaic panel, motor, inverter are analyzed in the high efficiency equipment chapter.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.47.3-48
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• 2021

We studied the large scale dynamo process in a system forced by helical magnetic field. The dynamo process is basically nonlinear, but can be linearized with 𝛼&𝛽 coefficients and large scale magnetic field $\bar{B}$. This is very useful to the investigation of solar (stellar) dynamo. A coupled semi-analytic equations based on statistical mechanics are used to investigate the exact evolution of 𝛼&𝛽. This equation set needs only magnetic helicity ${\bar{H}}_M({\equiv}{\langle}{\bar{A}}{\cdot}{\bar{B}}{\rangle},\;{\bar{B}}={\nabla}{\times}{\bar{A}})$ and magnetic energy ${\bar{E}}_M({\equiv}{\langle}{\bar{B}}^2{\rangle}/2)$. They are fundamental physics quantities that can be obtained from the dynamo simulation or observation without any artificial modification or assumption. 𝛼 effect is thought to be related to magnetic field amplification. However, in reality the averaged 𝛼 effect decreases very quickly without a significant contribution to ${\bar{B}}$ field amplification. Conversely, 𝛽 effect contributing to the magnetic diffusion maintains a negative value, which plays a key role in the amplification with Laplacian ∇²(= - k²) for the large scale regime. In addition, negative magnetic diffusion accounts for the attenuation of plasma kinetic energy E_V(= 〈 U² 〉/2) (U: plasma velocity) when the system is saturated. The negative magnetic diffusion is from the interaction of advective term - U • ∇ B from magnetic induction equation and the helical velocity field. In more detail, when 'U' is divided into the poloidal component U_pol and toroidal one U_tor in the absence of reflection symmetry, they interact with - B • ∇ U and - U • ∇ B from ∇ × 〈 U × B 〉 leading to 𝛼 effect and (negative) 𝛽 effect, respectively. We discussed this process using the theoretical method and intuitive field structure model supported by the simulation result.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.37-43
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• 2001

Crop status monitoring and yield prediction at higher spatial resolution is a valuable tool in various decision making processes including agricultural policy making by the national and local governments. A prototype crop forecasting system was developed to project the size of rice crop across geographic areas nationwide, based on daily weather pattern. The system consists of crop models and the input data for 1,455 cultivation zone units (the smallest administrative unit of local government in South Korea called "Myun") making up the coterminous South Korea. CERES-rice, a rice crop growth simulation model, was tuned to have genetic characteristics pertinent to domestic cultivars. Daily maximum/minimum temperature, solar radiation, and precipitation surface on 1km by 1km grid spacing were prepared by a spatial interpolation of 63 point observations from the Korea Meteorological Administration network. Spatial mean weather data were derived for each Myun and transformed to the model input format. Soil characteristics and management information at each Myun were available from the Rural Development Administration. The system was applied to the forecasting of national rice production for the recent 3 years (1997 to 1999). The model was run with the past weather data as of September 15 each year, which is about a month earlier than the actual harvest date. Simulated yields of 1,455 Myuns were grouped into 162 counties by acreage-weighted summation to enable the validation, since the official production statistics from the Ministry of Agriculture and Forestry is on the county basis. Forecast yields were less sensitive to the changes in annual climate than the reported yields and there was a relatively weak correlation between the forecast and the reported yields. However, the projected size of rice crop at each county, which was obtained by multiplication of the mean yield with the acreage, was close to the reported production with the $r^2$ values higher than 0.97 in all three years.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.11
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• pp.788-797
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• 2010

This study examines the influence of fluctuating daylight illuminance on daylight dimming control systems. Field measurements were performed for a full-scale mocked-up model under various daylight conditions in winter. Fluctuating ranges for a partially-shielded photosensor were great when the variation of sky ratio was great. When solar altitude was lower the illuminance and fluctuating range of illuminance were great due to the influence of direct components of daylight and the interrefelction between surfaces in rear area of space. It implies that daylight dimming system would not function effectively, unless the desktop illuminance by daylight is enough. Fluctuation ranges of photosensor illuminance were lower than 50 lx under clear sky conditions, but they were greater than 100 lx under partly-cloudy sky conditions. It means that the fluctuation range of electric light output of lighting fixture would greater under the partly-cloudy conditions and cause potential visual annoyance to occupants. Outdoor vertical illuminance reaching the windows would be an effective factor that can be used to predict the fluctuation of photosensor signals for effective controls of daylight dimming system.

• The Journal of the Petrological Society of Korea
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• v.23 no.3
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• pp.273-277
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• 2014

This paper presents a brief historical review of various attempts to estimate the age of the Earth, and reappraises the study of Patterson (1956) which revealed for the first time that the age of the Earth is $4550{\pm}70Ma$ by measuring Pb isotope ratios of several meteorites and a marine sediment. The standard model for the planetary formation of early solar system is: formation of solid particles condensed from the cooling of hot nebular gas -> formation of planet-sized bodies by accretion of those solid particles. The Moon is supposed to have formed from the accretion of the relicts produced by the collision of proto-Earth with Mars-sized body. It is not easy to pinpoint the age of the Earth, considering the series of events related to the formation of the Earth. So, I propose that the collision age as that of the Earth, since the present status of the Earth is thought to be the direct product of the collision. According to the previous studies, the collision age can be broadly constrained between the age ($4567.30{\pm}0.16Ma$) of the earliest condensates (CAI, calcium-aluminum rich inclusion) of the nebula gas, i.e., the age of the solar system, and the oldest age ($4,456{\pm}40Ma$) among rocks and minerals of the Earth and the Moon. We need more precise estimation of the collision age, since it is important in estimating time scale for the formation of planet-size body and in revealing thermal evolution of magma oceans of the Earth and the Moon presumably developed right after the collision.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.107-114
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• 1999

The large-scale distribution of crops Is usually determined by climate. We present the results of a climate-crop prediction based on spatial bio-physical process model approach, implemented in a GIS (Geographic Information System) environment using several regional and global agriculture-environmental databases. The model utilizes daily climate data like temperature, rainfall, solar radiation being generated stocastically by in-built model weather generator to determine the daily biomass and finally the crop yield. Crops are characterized by their specific growing period requirements, photosynthesis, respiration properties and harvesting index properties. Temperature and radiation during the growing period controls the development of each crop. The model simulates geographic/spatial distribution of climate by which a crop-growing belt can also be determined. The model takes both irrigated and non-irrigated area crop productivity into account and the potential increase in productivity by the technical means like mechanization is not considered. All the management input given at the base year 1995 was kept same for the next twenty-year changes until 2015. The simulated distributions of crops under current climatic conditions coincide largely with the current agricultural or specific crop growing regions. Simulation with assumed weather generated derived climate change scenario illustrate changes in the agricultural potential. There are large regional differences in the response across the country. The north-south and east-west regions responded differently with projected climate changes with increased and decreased productivity depending upon the crops and scenarios separately. When water was limiting or facilitating as non-irrigated and irrigated area crop-production effects of temperature rise and higher $CO_2$ levels were different depending on the crops and accordingly their production. Rise in temperature led to yield reduction in case of maize and rice whereas a gain was observed for wheat crop, doubled $CO_2$ concentration enhanced yield for all crops and their several combinations behaved differently with increase or decrease in yields. Finally, with this spatial modeling approach we succeeded in quantifying the crop productivity which may bring regional disparities under the different climatic scenarios where one region may become better off and the other may go worse off.