Bayesian Calibration: Calibrating Energy Models with Uncertainty

Bayesian calibration is one of many methods that can be used for calibrating building energy models.   In Bayesian calibration, modelers start from an assumption that parameters to be calibrated are uncertain through assignment of probability distribution functions. The Bayesian calibration algorithm adjusts the parameter probability distribution functions by comparison of model predictions to measured data.  The posterior parameter distributions parameters are statistically more consistent with the measured data than the prior distributions with the probability distributions representing the confidence of the values of the input parameters given both the model of the buildings and the observed values from the building.