Calibration of simplified building energy models for parameter estimation and forecasting: Stochastic versus deterministic modelling

摘要

Due to the ill-posedness of many inverse problems, parameter estimates are often prone to a possibly large uncertainty, caused by a series of errors and approximations in the experimental and modelling work. Stochastic state-space models for time series modelling incorporate a term of process noise that represents system error; most studies on building thermal model calibration however employ deterministic models that overlook this error.