System identification for building thermal systems under the presence of unmeasured disturbances in closed loop operation: Lumped disturbance modeling approach

Identification approaches applied to semi-physical thermal network structures, so called gray-box modeling approaches, are popular in building science for energy audits, retrofit analysis and advanced building controls, e.g. model predictive control. However conventional identification approaches applied to thermal networks fail when there are significant unmeasured heat gains that influence building responses. This paper presents a method to obtain improved gray-box building models from closed loop data having significant unmeasured disturbances. The method estimates both physical parameters of a building thermal network model and also a disturbance model that characterizes the unmeasured inputs. The performance of the algorithm is demonstrated using numerical and experimental results.