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The present paper suggests a procedure for identification of suitable models for the heat dynamics of a building. Such a procedure for model identification is essential for better usage of readings from smart meters, which is expected to be installed in almost all buildings in the coming years. The models can be used for different purposes, e.g. control of the indoor climate, forecasting of energy consumption, and for accurate description of energy performance of the building. Grey-box models based on prior physical knowledge and data-driven modelling are applied. This facilitates insight into otherwise hidden information about the physical properties of the building. A hierarchy of models of increasing complexity is formulated based on prior physical knowledge and a forward selection strategy is suggested enabling the modeller to iteratively select suitable models of increasing complexity. The performance of the models is compared using likelihood ratio tests, and they are validated using a combination of appropriate statistics and physical interpretation of the results. A case study is described in which a suitable model is sought after for a single storey 120 m2 building. The result is a set of different models of increasing complexity, with which building characteristics, such as: thermal conductivity, heat capacity of different parts, and window area, are estimated.

openalex: W2040640105