Modelling residential heat demand supplied by a local smart electric thermal storage system

Abstract

This paper presents an inverse modelling approach for deriving equivalent thermal parameters of buildings. A simplified thermal network based on electrical analogy was developed to replicate building thermal dynamics and model residential heat demand. The study employs data driven blackbox modelling based on the measured indoor and outdoor temperature. To validate the proposed method, virtual and physical experiments were conducted and performance of the simplified thermal network model was compared to two more complex RC models and measurements in an existing building. The simplified model was able to replicate the thermal dynamics of the complex models and the building with a high accuracy at the same conditions under which model parameters were estimated implying that for accurate modelling a large amount of experimental data obtained under various conditions is required. Such data will be gathered in the upcoming studies from 50 buildings in Latvia. The obtained data will then be used to model the aggregate heating demand at a national scale for assessment of the impact of smart electric thermal storage appliances on the overall power system.