Journal of the Architectural Institute of Korea Planning & Design (대한건축학회논문집:계획계)

Architectural Institute of Korea (대한건축학회)
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Whole Building Energy Simulation using Bayesian Stochastic Calibration

베이지언 확률적 보정을 이용한 에너지 시뮬레이션

  • 이동현 (성균관대학교 u-City 공학과) ;
  • 김영진 (성균관대학교 건축공학과) ;
  • 박철수 (성균관대학교 건축공학과) ;
  • 김인한 (경희대학교 건축학과)
  • Published : 2013.02.28
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Abstract

Building simulation has become increasingly important in assessing potential energy savings in buildings. It has been widely acknowledged that many inputs are under strong uncertainty and this causes significant differences between the simulation prediction and the reality. For calibrating the model, there are generally three approaches: manual (trial and error), deterministic, stochastic. This paper reports the last approach so called Bayesian calibration technique. The technique has been widely accepted in other domains as a powerful tool to estimate the posterior distribution of uncertain inputs based on the measured outputs. In this study, an building was selected and unknown parameters were identified. The Bayesian calibration was conducted in four steps: (1) determination of prior probability distributions for uncertain parameters. (2) Markov Chain Monte Carlo method for estimating posterior distributions, (3) validation of the model. It is concluded that the Bayesian calibration can be successfully used to improve accuracy of simulation prediction and reduce uncertainty of the model.

Keywords

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