• Title/Summary/Keyword: ground source heat pump

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Model to Predict Non-Homogeneous Soil Temperature Variation Influenced by Solar Irradiation (일사영향권내 비균질 토양의 열적거동 예측 모델)

  • Kim, Yong-Hwan;Hyun, Myung-Taek;Kang, Eun-Chul;Park, Yong-Jung;Lee, Euy-Joon
    • Journal of the Korean Solar Energy Society
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    • v.26 no.4
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    • pp.1-7
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    • 2006
  • This study is to develop a model to predict the soil temperature variation in Korea Institute of Energy Research using its thermal properties, such as thermal conductivity and diffusivity. Soil depth temperature variation is very important in the design of a proper Ground Source Heat Pump (GSHP) system. This is because the size of the borehole depends on the soil temperature distribution, and this can decrease GSHP system cost. If the thermal diffusivity and thermal conductivity are known, the soil temperature can be predicted by either the Krarti equation or the Spitler equation. Then a comparison with the Krarti equation and Spitler equation data with the real measured data can be performed. Also, the thermal properties can be reasonably approximated by performing a fit of the Krarti and Spitler equations with measured temperature data. This was done and, as a result, the Krarti equation and Spitler equation predicted values very close to the measured data. Although there is about a $0.5^{\circ}C$ difference between the deep subsurface prediction (16m - 60m), with this equation, were expected to have model this Non-Homogeneous Soil Temperature phenomenon properly. So, it has been shown that a prediction of non-homogeneous soil temperature variation influenced by solar radiation can be achieved with a model.

Evaluation on Heating Effects of Geothermal Heat Pump System in Farrowing House (지열 난방시스템을 이용한 분만돈사의 난방효과 분석)

  • Choi, H.C.;Park, Jae-Hong;Song, J.I.;Na, J.C.;Kim, M.J.;Bang, H.T.;Kang, H.G.;Park, S.B.;Chae, H.S.;Suh, O.S.;Yoo, Y.S.;Kim, T.W.
    • Journal of Animal Environmental Science
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    • v.16 no.3
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    • pp.205-215
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    • 2010
  • Geothermal heat pump system (GHPS) is an energy-efficient technology that use the relatively constant and renewable energy stored in the earth to provide heating and cooling. With the aim of using GHPS as a heating source, it's possibilities of application in farrowing house were examined by measuring environmental assessment and sow's performance. A total of 96 sows were assigned to 2 pig housings (GHPS and conventional housing) with 48 for four weeks in winter season. During the experimental period, indoor maximum temperature in GHPS-housing was measured up to $26.7^{\circ}C$, average temperature could maintain $21.2^{\circ}C$. The mean value of dust levels and $CO_2$, $NH_3$ and $H_2S$ gas emissions were decreased in GHPS-housing compare with those of conventional housing. Litter size, birth weight, parity and weaning weight did not differ between housings. However, feed intake of sow in GHPS-housing was lower than that of conventional housing. In energy consumption for heating, electric power consumption increased in GHPS-housing than the conventional housing, a 2,250 kwh increase, whereas there is no fuel usage for heater in GHPS-housing. Amount of ground water circulated for heating in cold weather for earth heat exchanger was 8.4-12.9 ton per day. In conclusion, GHPS may have environmental benefits and effectiveness of heating in farrowing housing and affect the performance in sows.

International Case Studies on the Eco-friendly Energy Towns with Hybrid Thermal Energy Supply System and Borehole Thermal Energy Storage (BTES) (친환경에너지타운에서 보어홀지중열 저장(BTES) 활용 융복합 열에너지 공급 시스템 사례 연구)

  • Shim, Byoung Ohan
    • Economic and Environmental Geology
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    • v.51 no.1
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    • pp.67-76
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    • 2018
  • This study reviews three eco-friendly energy towns with hybrid thermal energy supply systems and borehole thermal energy storage (BTES) in Canada and Denmark. The district heating and cooling systems were designed by using multi-source energy for the higher efficiency and reliability as well as environment. ADEU (Alexandra District Energy Utility) located at the developing area in the city of Richmond, Canada was designed to supply district energy with the installation of 726 borehole heat exchangers (BHEs) and a backup boiler using natural gas. DLSC (Drake Landing Solar Community) located in the town of Okotoks, Canada is a district system to store solar thermal energy underground during the summer season by seasonal BTES with 144 BHEs. Brædstrup Solpark district heating system located in Denmark has been conducted energy supply from multiple energy sources of solar thermal, heat pump, boiler plants and seasonal BTES with 48 BHEs. These systems are designed based on social and economic benefits as well as nature-friendly living space according to the city based energy perspective. Each system has the energy center which distribute the stored thermal energy to each house for heating during the winter season. The BHE depth and ground thermal storage volume are designed by the heating and cooling load as well as the condition of ground water flow and thermophysical properties of the ground. These systems have been proved the reliance and economic benefits by providing consistent energy supply with competitive energy price for many years. In addition, the several expansions of the service area in ADEU and Brædstrup Solpark have been processed based on energy supply master plan. In order to implement this kind of project in our country, the regulation and policy support of government or related federal organization are required. As well as the government have to make a energy management agency associated with long-term supply energy plan.

Energy Performance Evaluation of Low Energy Houses using Metering Data (실측데이터를 이용한 저에너지주택의 에너지성능평가)

  • Baek, Namchoon;Kim, Sungbum;Oh, Byungchil;Yoon, Jongho;Shin, Ucheul
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.27 no.7
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    • pp.369-374
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    • 2015
  • This study analyzed analyzes the energy performance of six houses in Daejeon completed which were built in 2011. Observed The observed houses, which were all designed and constructed inof the same size and structure, are were highly insulated with triple Low-E coating windows; the insulation level of the walls is was $0.13W/m^2K$ and that of the roof is was $0.10W/m^2K$. As electric houses, all of the energy supplied to the houses, including for cooking, is was supplied by electricity. A and 3~4 kWp of photovoltaic system and a 3~5 kW of ground source heat pump (GSHP) were installed in each house tofor providing provide space heating/and cooling and hot water are installed. We constructed a Web-based remote monitoring system in order to understand energy consumption and the dynamic behavior of the energy system. T, and the results of our metering data analysis of 2013 are as follows. First, the annual residential energy consumption is was 4,400 kWh (${\sigma}=1,209$) and GSHP energy consumption is was 5,182 kWh (${\sigma}=1,164$). Second, residential energy consumption ranked highest in average energy usage, with at 45% of the total, followed by heating with at 30%, hot water supply with at 17% and cooling with at 6%. Third, the average energy independence rate is was 51.8%, the GFA (Gross gross floor area) criteria average energy consumption unit is was $48.7kWh/m^2yr$ (${\sigma}=10.1$), and the net energy consumption unit (except the energy yield of the PV systems) is was $24.7kWh/m^2yr$ (${\sigma}=8.8$).

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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