• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.8
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• pp.803-809
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• 2012

It is necessary to predict the heating load in order to determine the optimal scheduling control of district heating systems. Heating loads are affected by many complex parameters, and therefore, it is necessary to develop an efficient, flexible, and easy to use prediction method for the heating load. In this study, simple specifications included in a building design document and the estimated temperature and humidity are used to predict the heating load on the next day. To validate the performance of the proposed method, heating load data measured from a benchmark district heating system are compared with the predicted results. The predicted outdoor temperature and humidity show a variation trend that agrees with the measured data. The predicted heating loads show good agreement with the measured hourly, daily, and monthly loads. During the heating period, the monthly load error was estimated to be 4.68%.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.12
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• pp.1105-1112
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• 2013

In this study, a method for predicting heating loads using building characteristic coefficients is proposed for heating system control, and a method for predicting hourly temperature and solar insolation, which mainly affect building heating loads, is also proposed. The temperature and solar insolation are predicted by using a fuzzy theory from forecast information at the meteorological agency, and the building characteristic coefficients for the prediction of heating loads are derived from EnergyPlus. The simulated heating loads of the present study show good agreement with those of EnergyPlus. and the variations of the predicted heating loads using the predicted temperature and solar insolation are similar to those using the actual weather data.

• Journal of Navigation and Port Research
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• v.35 no.3
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• pp.265-270
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• 2011

The purpose of this study is to compare and analyze the differences of a building's heating and cooling loads depending on the weather variation. Followings are the results. The temperature, humidity and wind speeds of standard year are bigger than those of 2006~2009. The 2006~2009's total horizontal solar irradiance is greater than that of standard year, and the direct solar irradiance of standard year is bigger in winter and vice versa in summer. As results of simulation on heating and cooling loads, it is difficult to find out the bilateral influences between maximum thermal loads and annual's. The equivalent-time operating ratio(EOR) is defined on this study to estimate the differences between year and year, and the EOR of standard year shows low value comparing to 2006~2009 years'.

• JOURNAL OF ELECTRICAL WORLD
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• s.315
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• pp.24-29
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• 2003

• Proceedings of the KAIS Fall Conference
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• 2012.05b
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• pp.575-578
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• 2012

단일창호를 적용한 KNU 식물공장 모델의 냉난방 에너지 부하를 DesignBuilder를 이용하여 해석하였다. 상추의 적정생육온도인 $20^{\circ}C$를 기준으로 이중창호를 적용한 경우와 에너지 소모량을 비교 분석하였다. 단일창호가 이중창호에 비해 연간 냉방부하는 약 128 MWh 감소하고 난방부하는 약 26 MWh 증가하여 단일창호가 냉방부하저감에 유리하다고 판단된다. KNU 식물공장의 중앙에 위치한 공간의 상부를 지붕구조물로 닫거나 계절별로 개폐하면서 냉난방부하에 미치는 영향을 계산하였다. 지붕구조물을 설치하게 되면 단위유닛이 취득하는 태양열이 감소하여 냉방부하가 감소하게 된다. 또한 지붕구조물을 상시 닫아두는 것이 계절별로 여닫는 것보다 냉방부하 저감에 유리하다. 식물공장 측면벽에 overhang과 sidefin을 설치하면 차양효과로 냉방부하가 감소하지만 감소비율은 크지 않았다. 에너지 부하의 대부분을 차지하는 냉방부하를 낮추기 위해 구조물이나 차양을 설치할 수 있으나 절감효과에 비해 설치비가 증가할 수 있기 때문에 추가 경제성 연구가 필요하다.

• Horticultural Science & Technology
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• v.33 no.5
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• pp.647-657
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• 2015

To investigate a method for calculation of the heating load for environmental designs of horticultural facilities, measurements of total heating load, infiltration rate, and floor heat flux in a large-scale plastic greenhouse were analyzed comparatively with the calculation results. Effects of ground heat exchange and infiltration loss on the greenhouse heating load were examined. The ranges of the indoor and outdoor temperatures were $13.3{\pm}1.2^{\circ}C$ and $-9.4{\sim}+7.2^{\circ}C$ respectively during the experimental period. It was confirmed that the outdoor temperatures were valid in the range of the design temperatures for the greenhouse heating design in Korea. Average infiltration rate of the experimental greenhouse measured by a gas tracer method was $0.245h^{-1}$. Applying a constant ventilation heat transfer coefficient to the covering area of the greenhouse was found to have a methodological problem in the case of various sizes of greenhouses. Thus, it was considered that the method of using the volume and the infiltration rate of greenhouses was reasonable for the infiltration loss. Floor heat flux measured in the center of the greenhouse tended to increase toward negative slightly according to the differences between indoor and outdoor temperature. By contrast, floor heat flux measured at the side of the greenhouse tended to increase greatly into plus according to the temperature differences. Based on the measured results, a new calculation method for ground heat exchange was developed by adopting the concept of heat loss through the perimeter of greenhouses. The developed method coincided closely with the experimental result. Average transmission heat loss was shown to be directly proportional to the differences between indoor and outdoor temperature, but the average overall heat transfer coefficient tended to decrease. Thus, in calculating the transmission heat loss, the overall heat transfer coefficient must be selected based on design conditions. The overall heat transfer coefficient of the experimental greenhouse averaged $2.73W{\cdot}m^{-2}{\cdot}C^{-1}$, which represents a 60% heat savings rate compared with plastic greenhouses with a single covering. The total heating load included, transmission heat loss of 84.7~95.4%, infiltration loss of 4.4~9.5%, and ground heat exchange of -0.2~+6.3%. The transmission heat loss accounted for larger proportions in groups with low differences between indoor and outdoor temperature, whereas infiltration heat loss played the larger role in groups with high temperature differences. Ground heat exchange could either heighten or lessen the heating load, depending on the difference between indoor and outdoor temperature. Therefore, the selection of a reference temperature difference is important. Since infiltration loss takes on greater importance than ground heat exchange, measures for lessening the infiltration loss are required to conserve energy.

• 보일러설비
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• s.76
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• pp.100-106
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• 2000

• 보일러설비
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• s.75
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• pp.104-111
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• 2000

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1419-1426
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• 2012

The heating and cooling energy load of the KNU plant factory was analyzed using the DesignBuilder. Indoor temperature set-point, LED supplemental lighting schedule, LED heat gain, and type of double skin window were selected as simulation parameters. For the cases without LED supplemental lighting, the proper growth temperature of lettuce $20^{\circ}C$ was selected as indoor temperature set-point together with $15^{\circ}C$ and $25^{\circ}C$. The annual heating and cooling loads which are required to maintain a constant indoor temperature were calculated for all the given temperatures. The cooling load was highest for $15^{\circ}C$ and heating load was highest for $25^{\circ}C$. For the cases with LED supplemental lighting, the heating load was decreased and the cooling load was 6 times higher than the case without LED. In addition, night time lighting schedule gave better result as compared to day time lighting schedule. To investigate the effect of window type on annual energy load, 5 different double skin window types were selected. As the U-value of double skin window decreases, the heating load decreases and the cooling load increases. To optimize the total energy consumption in the plant factory, it is required to set a proper indoor temperature for the selected plantation crop, to select a suitable window type depending on LED heat gain, and to apply passive and active energy saving technology.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.803-832
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• 2007

Electricity and heat load profiles by use types on an hourly basis at the least are essential for assessing economic viability of new cogeneration and CES projects and for optimally operating existing cogeneration and CES facilities. We adopt a multilevel model to specify heat load profiles so as to utilize in a flexible manner the panel nature of our data on weather and heating/cooling use. Converting the multilevel model to the linear mixed-effects model, we estimate the model by panel FGLS. The estimated load profile model for each distinct use type accounts for the effects of temperature, humidity, each hour over the year, each day of the week, each type of legal holidays, and heating/cooling area on energy use. To save space, we feature in detail the heating profile of the household.