• Title/Summary/Keyword: heating degree day of design

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Comparative Analysis of Accumulated Temperature for Seasonal Heating Load Calculation in Greenhouses (온실의 기간난방부하 산정을 위한 난방적산온도 비교분석)

  • Nam, Sang-Woon;Shin, Hyun-Ho;Seo, Dong-Uk
    • Journal of Bio-Environment Control
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    • v.23 no.3
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    • pp.192-198
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    • 2014
  • To establish the design criteria for seasonal heating load calculation in greenhouses, standard weather data are required. However, they are being provided only at seven regions in Korea. So, instead of using standard weather data, in order to find the method to build design weather data for seasonal heating load calculation, heating degree-hour and heating degree-day were analyzed and compared by methods of fundamental equation, Mihara's equation and modified Mihara's equation using normal and thirty years from 1981 to 2010 hourly weather data provided by KMA and standard weather data provided by KSES. Average heating degree-hours calculated by fundamental equation using thirty years hourly weather data showed a good agreement with them using standard weather data. The 24 times of heating degree-day showed relatively big differences with heating degree-hour at the low setting temperature. Therefore, the heating degree-hour was considered more appropriate method to estimate the seasonal heating load. And to conclude, in regions which are not available standard weather data, we suggest that design weather data should be analyzed using thirty years hourly weather data. Average of heating degree-hours derived from every year hourly weather data during the whole period can be established as environmental design standards, and also minimum and maximum of them can be used as reference data for energy estimation.

Study on the Revision of HDD for 15 Main Cities of Korea (국내 15개 주요지역의 난방도일 재산정에 관한 연구)

  • Cho, Sung-Hwan;Kim, Seong-Su;Choi, Chang-Yong
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.22 no.7
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    • pp.436-441
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    • 2010
  • The purpose of this study is to revise the HDD(Heating Degree-Days) of main cities of Korea because the outside temperature rise have been accelerated by global warming recently. Now our HDD(Heating Degree-Days) for the utility design of district heating system had been `established in 20 years ago. Therefore new heating degree days for main cities of korea had been required and determined using long-term measured outside weather temperature data during 30 years. For the analysis of HDD, five different base temperatures ranging from 24 to $16^{\circ}C$ were chosen in the calculation of heating degree days. And new yearly heating degree days of 15 cities of korea were given in the tabular form.

The expectation of future cooling and heating degree day of the Seoul and Ulsan using HadCM3 (HadCM3를 이용한 서울 및 울산지역의 미래 냉.난방도일 예측)

  • Lee, Kwan-Ho;Yoo, Ho-Chun;Noh, Kyoung-Hwan
    • 한국태양에너지학회:학술대회논문집
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    • 2008.04a
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    • pp.160-165
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    • 2008
  • The concern in energy reduction in the field of architecture which takes up a big weight in domestic energy consumption is gradually increasing. For this reason, a lot of research work on this matter is being carried out. Particularly, it is generally required that currently used system in a structure for energy reduction should be maximized in its efficiency. In addition, research on several energy reduction typed systems is underway. Such a research work should not only include the one in time of the present but also keep up with the trend for future-oriented research. This research paper forecasted and analyzed the trend for global warming and demand of a structure for energy in the future by applying climate scenarios to cooling degree-day and heating degree-day. Also, this research found out the decrease in heating degree-days and increase in cooling degree-days until this moment due to the progress of global warming. In addition, as for heating degree-days in the future forecasted on the basis of HadCM3, it is estimated that the range of decrease could be ever bigger starting 2040 in case of Seoul and also starting 2010 in case of Ulsan ever after respectively. In case of cooling degree-days, it is estimated that its increase range could be bigger abruptly starting 2050, and after 2080, its increase range would be much bigger.

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Improvement Method of Regional Insulation Standard through the Regional Heating Energy Demand Analysis (권역별 난방에너지 요구량 분석을 통한 단열기준 개선방안)

  • Kim, Jeong-Gook;Ahn, Byung-Lip;Jang, Cheol-Yong;Jeong, Hak-Geun;Haan, Chan-Hoon
    • KIEAE Journal
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    • v.13 no.4
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    • pp.43-48
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    • 2013
  • The effect of climate change has influenced humanity and ecosystem with tremendous changes in temperature. For the past 150 years, the national annual average temperature is 0.6 degree increased and the heating degree day reduced from April to November. However, December to January, the climate change was generated and the heating degree day increased. The blackout occured in 2011 and 2012 by increasing electricity consumption of heating and cooling equipment to the effects of climate change. That is because heating load accounted for 20% of building electric use. In this study, strengthening measures to reduce heating energy consumption is presented due to climate change in winter since 1980 to prevent blackout and reliable power supply for the building energy-saving design standards by Meteorological data provided by the National Weather Service were calculated using the heating degree days in order to present eighteen cities from 1980 to 2012. Insulation standards are presented to prevent black-out by the heating degree days. the heating energy demand was reduced almost 6% including 10% in Central, 5% in South and Jeju area based on strengthening of the insulation. It is applied to the entire country an annual economic effect of 250 billion won, and black-out can be prevented.

A Study on Prediction of Power Consumption Rate for Heating and Cooling load of School Building in Changwon City (창원시 학교 건축물의 냉난방부하에 대한 전력 소비량 추정에 관한 연구)

  • Park, Hyo-Seok;Choi, Jeong-Min;Cho, Sung-Woo
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.11 no.2
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    • pp.19-27
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    • 2012
  • This study was carried out in order to establish the estimation equation for school power consumption using regression analysis based on collected power consumption for two years of weather data and schools are located in Central Changwon and Masan district in Changwon city. (1) The power consumption estimation equation for Heating and cooling is calculated using power consumption per unit volume, the difference between actual power consumption and results of estimation equations is 4.1%. (2) The power consumption estimation equation for heating load is showed 2.6% difference compared to actual power consumption in Central Changwon and is expressed 2.9% difference compared to that in Masan district. Therefore, the power consumption prediction for each school using the power consumption estimation equation is possible. (3) The power consumption estimation equation for cooling load is showed 8.0% difference compared to actual power consumption in Central Changwon and is expressed 2.9% compared to that in Masan district. As the power consumption estimation equation for cooling load is expressed difference compared to heating load, it needs to investigate influence for cooling load.

A Case Study for Energy Consumption Characteristics of High School Facilities in Seoul (서울지역 고등학교 건물의 에너지소비특성에 관한 사례분석)

  • Kim, Sung-Bum;Oh, Byung-Chil;Shin, U-Cheul
    • Journal of the Korean Solar Energy Society
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    • v.36 no.6
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    • pp.61-69
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    • 2016
  • In this study, we analyzed five-year(2011~2015) data for D high school in Seoul area to analyze energy consumption characteristics in high school. The results are summarized as follows. (1) In the result of comparison analysis about 2015 energy consumption by usage, based on primary energy, 18% of energy was consumed in cafeteria, and 82% was consumed in main building. In the case of main building, base and constant load excepting hot water supply in restroom took 40%, heating including freeze protection took 20%, hot water supply in restroom took 14%, and cooling took 8% in order. (2) In the 2015 total energy consumption in D high school based on primary energy, heating energy takes 28%. The range and limit of energy savings coming from the reinforcement of insulation and window performance could be estimated. (3) To introduce new & renewable energy system in high school, electricity-based system is suitable than heat-based system because usage of electric energy is larger than that of heat energy in high school. (4) Five-year energy consumption unit according to heating degree-day showed a linearly increasing trend, and the coefficient of determination(R2) was 0.9763, which means high correlation.

Study on Heating Load Characteristics and Thermal Curtain Effects for Simple Silkworm Rearing Houses(I) -Heating Load Coefficient and Maximum Heating Load- (간이잠실(簡易蠶室)의 난방(暖房) 부하특성(負荷特性) 및 보온(保溫)커튼 설치효과(設置効果)에 관(關)한 연구(硏究)(I) -간이잠실(簡易蠶室)의 난방(暖房) 부하계수(負荷係數) 및 최대(最大) 난방부하(暖房負荷)-)

  • Choe, K.J.;Lee, D.H.;Park, K.K.
    • Journal of Biosystems Engineering
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    • v.15 no.4
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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.

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Analysis of Greenhouse Thermal Environment by Model Simulation (시뮬레이션 모형에 의한 온실의 열환경 분석)

  • 서원명;윤용철
    • Journal of Bio-Environment Control
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    • v.5 no.2
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    • pp.215-235
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    • 1996
  • The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad & fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH+7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad & fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).

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