• 한국농공학회논문집
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• 제57권5호
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• pp.37-42
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• 2015

In order to provide fundamental data for the creation of environmental design criteria for horticultural facilities, we developed a method to easily calculate the seasonal heating load applying heating degree-hour while taking into account heating load reductions due to solar radiation in the daytime, and reviewed through greenhouse heating experiments. Heating experiments and measuring meteorological environments were carried out in three greenhouses located at Buyeo, Cheonan, and Buan, and we derived reduction factors of seasonal heating load according to hours of sunshine. Daily mean hours of sunshine during the experiment period in each of the greenhouse was 4.0 to 8.3 hours, and the reduction factor of seasonal heating load was 0.64 to 0.85, has been shown to decrease linearly with the increase in hours of sunshine. A method to estimate the seasonal heating load for greenhouses was developed using the reduction factor of seasonal heating load derived from the greenhouse heating experiment, including the adjustment factor of seasonal heating load according to hours of sunshine. The developed method was validated through heating experiments in a greenhouse located at Cheonan. Greenhouse seasonal heating loads calculated by the method developed in this study were analyzed to show the estimate error of 1.2 to 5.0%. It showed that the accuracy increased 2.3 times more than when using the heating load reduction factor of 0.75 applied uniformly in previous studies. Thus, the calculation method of seasonal heating load for greenhouses considering hours of sunshine developed in this study could be utilized for energy estimation, management planning, and economic evaluation in greenhouse design.

• 한국태양에너지학회 논문집
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• 제32권6호
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• pp.60-67
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• 2012

Government Geothermal Cooling-Heating Projects has made efforts to reduce GHG(Greenhouse Gas) emissions and to manage cost of greenhouse farm households. This study evaluated the economic benefits of heating load rate of change by comparing Geothermal Cooling-Heating System with the existing system(greenhouse diesel heating) in the Government Geothermal Cooling-Heating Projects. Economic analysis results shows that, 1) When installing the Cooling-Heating system according to the ratio of 70% heating load in policy standards, the geothermal cooling-heating system has economic efficiency with greenhouse type or scale independent because the investment cost is recovered within 7 years. And It was more economic efficiency the ratio of 50% heating load than70% heating load. 2) When installing the Cooling-Heating system according to the glass greenhouse of the ratio of 90% heating load, pay period of investment cost is recovered within 5 years. Therefore it is necessary to apply flexible heating sharing according to greenhouse type or scale.

• KIEAE Journal
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• 제13권1호
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• pp.47-55
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• 2013

This study aims to evaluate the correlation between vertical solar radiation and the level of heating load according to the location and type of housing in multi-family apartments. This study shows that heating load is related with factors such as wall loss, window loss, ventilation loss and solar radiation gain. The heating load increases in the order of the middle floors, the highest floors and the lowest floors. The lowest and the highest floors are the most vulnerable floors, and it should be as emphasized as the middle floors. The heating load saving proposal contains 52 Alt. that shows heating load savings from min. 4% to max. 49%. The goal is to reduce the heating load of the highest and the lowest floors to the level of the middle floors. The result showed that there are 3 Alt. for the lowest floors and 16 Alt. for the highest floors as the heating load saving proposal. This study suggests integrated application to compose saving elements of heating load. so it could be utilized as a data for the construction of passive houses.

• 설비공학논문집
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• 제27권6호
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• pp.283-292
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• 2015

A model of apartment heating load in a district heating system could be useful in the management and utilization of energy resources, since it could predict energy usage and so could assist in the efficient use of energy resources. The heating load in a district heating system varies in a highly nonlinear manner and is subject to many different factors, such as heating area, number of people living in that complex, and ambient temperature. Thus there are few published papers with accurate models of heating load, especially in domestic literature. This work is concerned with the modeling of apartment heating load in a district heating system in winter, using the reduced least square support vector machine (LS-SVM), and with the purpose of using the model to predict heating energy usage in domestic city area. We collected 23,856 pieces of data on heating energy usage over a 12-week period in winter, from 12 heat exchangers in five apartments. Half of the collected data were used to construct the heating load model, and the other half were used to test the model's accuracy. The model was able to predict the heating energy usage pattern rather accurately. It could also estimate the usage of heating energy within of mean absolute percentage error. This implies that the model prediction accuracy needs to be improved further, but it still could be considered as an acceptable model if we consider the nonlinearity and uncertainty of apartment heating energy usage in a district heating system.

• 설비공학논문집
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• 제28권9호
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• pp.355-360
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• 2016

Continuing to the modeling of heating load, this paper, as the second part of consecutive works, presents LS-SVM (least square support vector machine) based model of winter time apartment hot water supply load in a district heating system, so as to be used in prediction of heating energy usage. Similar, but more severely, to heating load, hot water supply load varies in highly nonlinear manner. Such nonlinearity makes analytical model of it hardly exist in the literatures. LS-SVM is known as a good modeling tool for the system, especially for the nonlinear system depended by many independent factors. We collect 26,208 data of hot water supply load over a 13-week period in winter time, from 12 heat exchangers in seven different apartments. Then part of the collected data were used to construct LS-SVM based model and the rest of those were used to test the formed model accuracy. In modeling, we first constructed the model of district heating system's hot water supply load, using the unit heating area's hot water supply load of seven apartments. Such model will be used to estimate the total hot water supply load of which the district heating system needs to provide. Then the individual apartment hot water supply load model is also formed, which can be used to predict and to control the energy consumption of the individual apartment. The results obtained show that the total hot water supply load, which will be provided by the district heating system in winter time, can be predicted within 10% in MAPE (mean absolute percentage error). Also the individual apartment models can predict the individual apartment energy consumption for hot water supply load within 10% ~ 20% in MAPE.

• Journal of Biosystems Engineering
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• 제15권4호
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• pp.346-354
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• 1990

In order to provide basic references for the design of heating on simple silkworm rearing house, the actual change of heating load coefficient by progress of adult silkworm rearing day from the reared in silkworm rearing house, the heating load coefficient by types of silkworm rearing houses and the heating requirement and the maximum heating load by types of silkworm rearing houses were determined. The results obtained from the study were as follows : 1. The average heating load coefficients of NS, OS and CC type simple silkworm rearing houses were $24.1KJ/m^2-hr-^{\circ}C$, $19.8KJ/m^2-hr-^{\circ}C$, and $10.8KJ/m^2-hr-^{\circ}C$, respectively. 2. The change of heating load coefficient by progress of silkworm rearing day after reared into simple silkworm rearing house could be expressed as Fig. 4. 3. Heating degree-hour for adult silkworm rearing in Suweon district was calculated as $951.6^{\circ}C-hr$ for spring season and $610.5^{\circ}C-hr$ for autumn season. 4. Yearly heating requirement of the NS type was estimated twice more than that of the CC type. Thus, some kinds of reinforced thermal adiabatic facilities is desirable for NS type. 5. The time for maximum heating load was turned out at the 4th instar during the spring season and after the mounting during the autumn season. 6. This study was performed in Suweon district. However, the estimated and analyzed data could be adapted to the major silkworm rearing district if their meteorology data were adjusted.

• 한국농공학회논문집
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• 제48권5호
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• pp.51-60
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• 2006

In order to examine the heat transfer characteristic of a soil warming system and effects of soil warming on the greenhouse heating load, control experiments were performed in two greenhouses covered with double polyethylene film. One treated the soil warming with an electric heat wire and the other treated a control. Inside and outside air temperature, soil temperature and heat flux, and heating energy consumption were measured under the set point of heating temperature of $5,\;10,\;15,\;and\;20^{\circ}C$, respectively. Soil temperatures in a soil warming treatment were observed $4.1\;to\;4.9^{\circ}C$ higher than a control. Heating energy consumptions decreased by 14.6 to 30.8% in a soil warming treatment. As the set point of heating temperature became lower, the rate of decrease in the heating energy consumptions increased. The percentage of soil heat flux in total heating load was -49.4 to 24.4% and as the set point of heating temperature became higher, the percentage increased. When the set point of heating temperature was low in a soil warming treatment, the soil heat flux load was minus value and it had an effect on reducing the heating load. Soil heat flux loads showed in proportion to the air temperature difference between the inside and outside of greenhouse but they showed big difference according to the soil warming treatment. So new model for estimation of the soil heat flux load should be introduced. Convective heat transfer coefficients were in proportion to the 1/3 power of temperature difference between the soil surface and the inside air. They were $3.41\;to\;12.42\;W/m^{2}^{\circ}C$ in their temperature difference of $0\;to\;10^{\circ}C$. Radiative heat loss from soil surface in greenhouse was about 66 to 130% of total heating load. To cut the radiation loss by the use of thermal curtains must be able to contribute for the energy saving in greenhouse.

• 설비공학논문집
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• 제12권1호
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• pp.26-32
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• 2000

Design load calculations which depend on the thermal characteristics of the building structure such as the wall, roof, and fenestration provide the basic data for selecting an HVAC system and its equipment. Most of domestic multi-family houses include a high thermal storage layer like massive concrete structure and a floor heating structure. This study is to compare the results of the design heating load between steady state and unsteady state calculation in order to comprehend the thermal storage effect in multi-family houses. The design heating load under the steady state calculation is estimated from 5.4% to 7.8% larger than that under the unsteady state in the typical floor of a multi-family house model. The design heating load considered the safety factors like a orientation and location factor also is 21.4% to 26.5% larger than that by the unsteady state calculation. So, the safety factors for use of the practicing engineer are analyzed as the main factor of a heating plant oversizing.

• Journal of Biosystems Engineering
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• 제28권3호
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• pp.217-224
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• 2003

To find out heating load and to determine the power of heat pump compressor for the Ondol room heating the COP of heat pump, the variation of Ondol room air temperature, the variation of ambient temperature and power consumption of heat pump are analyzed. The results from this study were summarized as follows: 1. The COP of the heat pump in close loop decreased as the ambient air temperature. The COP was 2.26 when the temperature difference of condenser was $20\pm3^{\circ}C$. 2. The Ondol surface temperature was $25\pm3^{\circ}C$ when the hot water of $40^{\circ}C$ was supplied from hot water storage tank to the Ondol and the temperature difference between the Ondol surface and the room air temperature was $7~8^{\circ}C$. 3. The ratio of thermal conduction heating load to total heating load in Ondol heating space was found to be 83% and ratio of ventilation heating load was 17%. Therefore, the thermal conduction heating load was confirmod to be a major heating load in Ondol heating space. 4. In case of the ambient temperature of $3.2^{\circ}C$, the efficiency of heat exchange of Ondol heating system was 85%. 5. The heating load per Ondol heating surface area and volume of Ondol room space were theoretically analyzed. In case of the room temperature of $20^{\circ}C$ and the ambient temperature of $-3.2~3.8^{\circ}C$, the heating load per Ondol surface area was 115.8~167.6kJ/h ㆍ㎥ and per Ondol mom space volume was 50.2~72.7kJ/h ㆍ㎥. 6. The compressor power of heat pump fur the Ondol room heating could be determined with the heating load analyzed in this study In case of the Ondol room air temperature of 17~2$0^{\circ}C$ and the ambient temperature of -5~3.8$^{\circ}C$, the compressor power of heat pump per Ondol surface area was analyzed to be $2.3\times10^{-2}psm^2$, and per volume of Ondol room space $1.0\times10^{-2}1.4\times10^{-2}ps/m^2$ps.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2009년도 춘계학술대회 논문집
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• pp.255-258
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• 2009

Leading developed countries have studied energy self-sufficient houses such as zero or low energy buildings to reduce energy consumption for buildings since the early 1990s. Moreover, some developed countries have actually constructed self-sufficient houses and operated them for demonstration, expanding use of such houses. Korea has also established Zero Energy Solar House(ZeSH) and studied energy independence. Therefore, this study analyzed research result regarding ZeSH, self-sufficient energy house hold of Korea, found out technologies used for heating energy independence, used building interpretation program(ESP_r) to evaluate performance of each factors and analyzed energy reduction quantitatively. Results from the research are as follows: Reduction rate of actual detached house's heating load was also analyzed quantitatively depending on application of each technology. When each factor was applied step-by-step, annual reduction rate of heating load depending on increase in insulation thickness reached 6.6~22.2 %. Annual reduction rate of heating load depending on increase insulation thickness, and change in window heating performance and area ratio reached 31.5 %. Annual reduction rate of heating load through high-sealing and high-insulation depending on change in leakage rate reached 40.0~88.9 %. Annual reduction of heating load, when Mass Wall and attached sun space was applied were applied reached 28.5~39.2 %, respectively.