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Prediction of Greenhouse Energy Loads using Building Energy Simulation (BES)

BES 프로그램을 이용한 국내 대표적 대형온실의 에너지 부하 예측

  • 이성복 (서울대학교 농업생명과학대학 지역시스템공학과 & 농업생명과학연구원) ;
  • 이인복 (서울대학교 농업생명과학대학 지역시스템공학과 & 농업생명과학연구원) ;
  • 홍세운 (서울대학교 농업생명과학대학 지역시스템공학과 & 농업생명과학연구원) ;
  • 서일환 (서울대학교 농업생명과학대학 지역시스템공학과 & 농업생명과학연구원) ;
  • ;
  • 권경석 (서울대학교 농업생명과학대학 지역시스템공학과 & 농업생명과학연구원) ;
  • 하태환 (서울대학교 농업생명과학대학 지역시스템공학과 & 농업생명과학연구원) ;
  • 한창평 (상지영서대학교 자동차과)
  • Received : 2012.03.06
  • Accepted : 2012.05.16
  • Published : 2012.05.31

Abstract

Reliable estimation of energy load inside the greenhouse and the selection of cooling and heating facilities are very important preceding factors to save energy as well as initial and maintenance costs of operating a greenhouse. Recently, building energy simulation (BES) technique to simulate a model similar to the actual conditions through a variety of dynamic simulation methods, and predict and analyze the flow of energy is being actively introduced and developed. As a fundamental research to apply the BES technique which is mainly used for analysis of general buildings, to greenhouse, this research designed four types of naturally-ventilated greenhouses using one of commercial programs, TRNSYS, and then compared and analyzed their energy load properties, by applying meteorological data collected from six regions in Korea. When comparing the greenhouse load of each region depending on latitude and topographical characteristics through simulation, Chuncheon had nearly 9~49 % higher heating load per year than other regions, but its annual cooling load was the reverse to it. Except for Jeju, 1-2W type greenhouses in five regions showed about 17 % higher heating load than a widespan type greenhouse, and 1-2W type greenhouses in Chuncheon, Suwon, Cheongju, Daegu, Cheonju and Jeju had 23 %, 20 %, 17 %, 16 %, 18 % and 20 % higher cooling load respectively than a wide span-type one. Glasshouse and vinyl greenhouse showed 8~11 % and 10~12 % differences respectively in heating load, while 2~10 % and 7~10 % differences in cooling load respectively.

Keywords

References

  1. Hong, S. W., 2008. Analytical comparison on ventilation efficiencies of naturally-ventilated multi-span greenhouse and development of crop model using CFD technology. M.S. : Seoul National University (in Korean).
  2. Hong, S. W., Lee, I. B., Hong, H. K., Seo, I. W., Hwang, H. S., Bitog, J. P., Yoo, J. I., Kwon, K. S., Ha, T. H., and Kim, K. S., 2008. Analysis of heating load of a naturally ventilated broiler house using BES simulation. Journal of the Korean Society of Agricultural Engineers 50(1): 39-47 (in Korean). https://doi.org/10.5389/KSAE.2008.50.1.039
  3. Hyun, S. K., Hong, H. K., and Yoo, H. S., 2002. Verification experiment and calculation of cooling load for a test space. Korean Journal of Air-Conditioning and Refrigeration Engineering 14(2): 153-160 (in Korean).
  4. Jang, J. C., Kang, E. C., and Lee, E. J., 2009. Peak cooling and heating load and energy simulation study for a special greenhouse facility. Journal of the Korean Solar Energy Society 29(1): 72-76 (in Korean).
  5. Kim, D. H., Hong, H. K., Yoo, H. S., and Kim, O. J., 2006. Simulation and verification of cooling and heating load for test space with forced ventilation. Korean Journal of Air-Conditioning and Refrigeration Engineering 18(12): 947-954 (in Korean).
  6. Korea Energy Economics Institute (KEEI), 2010. Yearbook of energy statistics. Eui-wang, Korea. (in Korean).
  7. Lee, J. H., Yu, K. H., and Cho, D. W., 2009. An analysis of comparison between the evaluation tool for building energy efficiency rating system and detailed analysis programs. SAREK 2009 Summer Annual Conference, 2009(6): 3-8 (in Korean).
  8. Rural Development Administration (RDA), 2006. Guide book of energy cost down protected horticulture for overcome of high oil price. Suwon: National Institute of Agricultural Engineering of RDA. (in Korean).
  9. Solar Energy Laboratory (SEL), 2007, TRNSYS 16 reference manual, Madison: University of Wisconsin.

Cited by

  1. Comparative Analysis of Accumulated Temperature for Seasonal Heating Load Calculation in Greenhouses vol.23, pp.3, 2014, https://doi.org/10.12791/KSBEC.2014.23.3.192
  2. Development and Optimization of a Building Energy Simulation Model to Study the Effect of Greenhouse Design Parameters vol.11, pp.8, 2018, https://doi.org/10.3390/en11082001