• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.161-171
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• 2019

Varied methods have been researched continuously because the past as the daily maximum electricity demand expectation has been a crucial task in the nation's electrical supply and demand. Forecasting the daily peak electricity demand accurately can prepare the daily operating program about the generating unit, and contribute the reduction of the consumption of the unnecessary energy source through efficient operating facilities. This method also has the advantage that can prepare anticipatively in the reserve margin reduced problem due to the power consumption superabundant by heating and air conditioning that can estimate the daily peak load. This paper researched a model that can forecast the next day's daily peak load when considering the influence of temperature and weekday, weekend, and holidays in the Seasonal ARIMA, TBATS, Seasonal Reg-ARIMA, and NNETAR model. The results of the forecasting performance test on the model of this paper for a Seasonal Reg-ARIMA model and NNETAR model that can consider the day of the week, and temperature showed better forecasting performance than a model that cannot consider these factors. The forecasting performance of the NNETAR model that utilized the artificial neural network was most outstanding.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.31-37
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• 2021

As the size of buildings increases due to urbanization due to the development of industry, the need to purify the air and maintain a comfortable indoor environment is also increasing. With the development of monitoring technology for refrigeration systems, it has become possible to manage the amount of electricity consumed in buildings. In particular, refrigeration systems account for about 40% of power consumption in commercial buildings. Therefore, in order to develop the refrigeration system failure diagnosis algorithm in this study, the purpose of this study was to understand the structure of the refrigeration system, collect and analyze data generated during the operation of the refrigeration system, and quickly detect and classify failure situations with various types and severity . In particular, in order to improve the classification accuracy of failure types that are difficult to classify, a three-step diagnosis and classification algorithm was developed and proposed. A model based on SVM and LGBM was presented as a classification model suitable for each stage after a number of experiments and hyper-parameter optimization process. In this study, the characteristics affecting failure were preserved as much as possible, and all failure types, including refrigerant-related failures, which had been difficult in previous studies, were derived with excellent results.

• Journal of the Society of Disaster Information
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• v.11 no.1
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• pp.135-147
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• 2015

Recent underground common utility tunnels are underground facilities for jointly accommodating more than 2 kinds of air-conditioning and heating facilities, vacuum dust collector, information processing cables as well as electricity, telecommunications, waterworks, city gas, sewerage system required when citizens live their daily lives and facilities responsible for the central function of the country but it is difficult to cope with fire accidents quickly and hard to enter into common utility tunnels to extinguish a fire due to toxic gases and smoke generated when various cables are burnt. Thus, in the event of a fire, not only the nerve center of the country is paralyzed such as significant property damage and loss of communication etc. but citizen inconveniences are caused. Therefore, noticing that most fires break out by a short circuit due to electrical works and degradation contact due to combustible cables as the main causes of fires in domestic and foreign common utility tunnels fire cases that have occurred so far, the purpose of this paper is to scientifically analyze the behavior of a fire by producing the model of actual common utility tunnels and reproducing the fire. A fire experiment was conducted in a state that line type fixed temperature detector, fire door, connection deluge set and ventilation equipment are installed in underground common utility tunnels and transmission power distribution cables are coated with fire proof paints in a certain section and heating pipes are fire proof covered. As a result, in the case of Type II, the maximum temperature was measured as $932^{\circ}C$ and line type fixed temperature detector displayed the fire location exactly in the receiver at a constant temperature. And transmission power distribution cables painted with fire proof paints in a certain section, the case of Type III, were found not to be fire resistant and fire proof covered heating pipes to be fire resistant for about 30 minutes. Also, fire simulation was carried out by entering fire load during a real fire test and as a result, the maximum temperature is $943^{\circ}C$, almost identical with $932^{\circ}C$ during a real fire test. Therefore, it is considered that fire behaviour can be predicted by conducting fire simulation only with common utility tunnels fire load and result values of heat release rate, height of the smoke layer, concentration of O2, CO, CO2 etc. obtained by simulation are determined to be applied as the values during a real fire experiment. In the future, it is expected that more reliable information on domestic underground common utility tunnels fire accidents can be provided and it will contribute to construction and maintenance repair effectively and systematically by analyzing and accumulating experimental data on domestic underground common utility tunnels fire accidents built in this study and fire cases continuously every year and complementing laws and regulations and administration manuals etc.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.288-296
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• 2019

Radiation cooling has used ceilings or floors as cooling surfaces. In such cases, to avoid moisture condensation on the surface, the surface temperature needs be higher than the dew point temperature or an additional dehumidifier is added. In this study, with a goal for residential application, intentional moisture condensation on the cooling surface was attempted, which increased the cooling capacity and improved the indoor comfortness. This method included two separate refrigeration cycles - convection-type dehumidifying cycle and the panel cooling cycle. Test results on the panel cooling cycle showed that, at the standard outdoor ($35^{\circ}C/24^{\circ}C$) and indoor ($27^{\circ}C/19.5^{\circ}C$) condition, the refrigerant flow rate was 8.8 kg/h, condensation temperature was $51^{\circ}C$, evaporation temperature was $8.8^{\circ}C$, cooling capacity was 376 W and COP was 1.75. Furthermore, the panel temperature was uniform within $1^{\circ}C$ (between $13^{\circ}C$ and $14^{\circ}C$). As the relative humidity decreased, the cooling capacity decreased. However, the power consumption remained approximately constant. In the convection-type dehumidification cycle, the refrigerant flow rate was 21.1 kg/h, condensation temperature was $61^{\circ}C$, evaporation temperature was $5.0^{\circ}C$, cooling capacity was 949 W and COP was 2.11 at the standard air condition. When both the radiation panel cooling and the dehumidification cycle operated simultaneously, the cooling capacity of the radiation panel cycle was 333 W and that of the dehumidification cycle was 894 W, and the COP was 1.89. As the fan flow rate decreased, both the cooling capacity of the radiation panel and the dehumidification cycle decreased, with that of the dehumidification cycle decreasing at a higher rate. Finally, a possible control logic depending on the change of the cooling load was proposed based on the results of the present study.