DOI QR코드

DOI QR Code

Modeling of Stochastic Properties of Internal Heat Generation of an Office Building for Slab Cooling Storage

사무소건물의 슬래브축냉을 위한 내부발열부하의 확률적 성상 모델화

  • Jung, Jae-Hoon (Department of Architectural Engineering, Hoseo University)
  • Received : 2011.06.30
  • Published : 2011.12.10

Abstract

It has been shown that the air-conditioning system with slab cooling storage is effective in cutting peak load and utilizing nighttime electric power. The stochastic properties of internal heat generation which has great influence on the cooling load are examined in this paper. Based on the measured cooling load and electric power consumption in an office building with slab cooling storage, stochastic time series models to simulate these random processes are investigated. Furthermore, a calculated result by an optimal control method of thermal analysis taking into account the internal heat is compared with the measured cooling load.

Keywords

References

  1. Shinkai, K. I., Kasuya, A., and Kato, M. H., 2000, Performance Evaluation of Floor Thermal Storage System, ASHRAE Transactions, Vol. 106, No. 1, pp. 311-316.
  2. Jung, J. H. and Shin, Y. G., 2005, An Experimental Study on Thermal Storage Performance of an Air-Conditioning System with Slab Thermal Storage, Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 17, No. 5, pp. 427-435.
  3. Ishino, H., 2003, A Simulation Study on the Response of Charged and Discharged Thermal Energy in Building Thermal Mass Storage Systems, Proceedings of Eighth International IBPSA Conference, pp. 547-555.
  4. Jung, J. H., Hokoi, S. and Urabe, W., 1999, Fundamental study into optimized control for air-conditioning system with floor thermal storage based on optimal control theory, Journal of Architecture, planning and environmental engineering(Transactions of AIJ), Vol. 520, pp. 33-39.
  5. Jung, J. H., 2008, An Analysis of the Optimal Thermal Storage Time of Air-Conditioning System with Slab Thermal Storage:An Analysis by the Gradient Method Algorithm, Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 20, No. 10, pp. 702- 709.
  6. Yoshida, H. and Terai, T., 1992, Modeling of weather data by time series analysis for airconditioning load calculations, ASHRAE Trans., 98 Pt.1 pp. 328-345
  7. Kim, J. Y., Yook, I. S., Nam, H. J., Lee, J. S., Kim, J. M. and Cho, S., 2008, The Impact of Internal Heat Gain on Heating and Cooling Load in Curtain Wall Office Buildings, Proceedings of the SAREK 2008 Summer Annual Conference, pp. 925-930.
  8. Hirata, T. Y., Kawase, T. H., Nagai, T. O. and Nagata A. H., 2010, Field Survey on Internal Heat Generation in Office Buildings, Summaries of Technical Papers of Annual Meeting Architectural Institute of Japan, pp. 1157-1158.
  9. Yoo, S. Y. and Kim, J. Y., Analysis of Internal Heat Gain and System Operation Patterns in Residential Buildings, Proceedings of the SAREK 2011 Summer Annual Conference, pp. 683-686.
  10. Box, G. E. P. and Jenkins, G. M., 1976, Time Series Analysis-Forecasting and Control, Holden-Day.
  11. Peter, J. B. and Richard, A. D., 1996, Introduction To Time Series and Forecasting, Springer-Verlag New York, Inc.
  12. Korea Electric Power Corporations; www.kepco.co.kr.

Cited by

  1. A Study on Optimal Control of Slab Cooling Storage Considering Stochastic Properties of Internal Heat Generation vol.27, pp.6, 2015, https://doi.org/10.6110/KJACR.2015.27.6.313