Revealing the hidden dynamics of the energy signature model

Abstract

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. Key innovations• Implementing a dynamical version of the energy signature method using high frequency measurements.• Reconstructing a dynamic variable that is a proxy of the indoor temperature, i.e., measurements of the indoor air temperature are not needed. Practical implicationsHigh frequency data such as hourly resolution is required for the proposed method. Special attention should be put on the reliability of the estimated hidden proxy of the indoor temperature state for new case studies.