Revealing the hidden dynamics of the energy signature model

The energy signature (ES) model is a well-known method to measure the energy performance of a building. This method uses coarse data aggregation that omits valuable information about the dynamics of the thermal elements of a building. This work presents a method to reconstruct these hidden dynamics without increasing the measuring complexity. The proposed method uses a state space formulation of the ES, that is filtered using hourly measurements of outdoor temperature and heat consumption. It is shown that the reconstructed state variable works as a proxy of the indoor temperature, and reacts to the weather conditions. These results highlight the potential of this method for real-time heating performance evaluation, as well as anomaly detection.