Korean Journal of Air-Conditioning and Refrigeration Engineering (설비공학논문집)

The Society of Air-Conditioning and Refrigerating Engineers of Korea (대한설비공학회)
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Performance Evaluation of a Dynamic Inverse Model with EnergyPlus Model Simulation for Building Cooling Loads

건물냉방부하에 대한 동적 인버스 모델링기법의 EnergyPlus 건물모델 적용을 통한 성능평가

  • 이경호 (한국전력공사 전력연구원) ;
  • Published : 2008.03.10
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Abstract

This paper describes the application of an inverse building model to a calibrated forward building model using EnergyPlus program. Typically, inverse models are trained using measured data. However, in this study, an inverse building model was trained using data generated by an EnergyPlus model for an actual office building. The EnergyPlus model was calibrated using field data for the building. A training data set for a month of July was generated from the EnergyPlus model to train the inverse model. Cooling load prediction of the trained inverse model was tested using another data set from the EnergyPlus model for a month of August. Predicted cooling loads showed good agreement with cooling loads from the EnergyPlus model with root-mean square errors of 4.11%. In addition, different control strategies with dynamic cooling setpoint variation were simulated using the inverse model. Peak cooling loads and daily cooling loads were compared for the dynamic simulation.

Keywords

References

  1. Chaturvedi, N. and Braun, J. E., 2002, An inverse grey-box model for transient building load prediction, HVAC&R Research, Vol. 8, No. 1, pp. 73-100
  2. Gouda, M. M., Danaher, S. and Underwood, C. P., 2002, Building thermal model reduction using nonlinear constrained optimization, Building and Environment, Vol. 37, pp. 1255-1265 https://doi.org/10.1016/S0360-1323(01)00121-4
  3. Lee, K. H. and Braun, J. E., 2004, Development and application of an inverse building model for demand response in small commercial buildings, Proceeding of the IBPSAUSA SimBuild 2004
  4. EnergyPlus, Energy Simulation Software, DOE, USA, http://www.eere.energy.gov
  5. Xu, P., Haves, P., Zagreus, L., and Piette, M., 2006, Peak shifting with thermal mass in large commercial buildings (Field tests, simulation and results), LBNL
  6. TRNSYS, Transient system simulation program, Solar Energy Laboratory, University of Wisconsin-Madison
  7. Seem, J. E., Klein, S. A., Beckman, W. A. and Mitchell, J. W., 1989, Transfer functions for efficient calculations of multi dimensional heat transfer, Journal of Heat Transfer-Transactions of the ASME, Vol. 111, No. 1, pp. 5-12 https://doi.org/10.1115/1.3250659
  8. Compaq Visual Fortran Math Library, Compaq