Thermal Modelling of Existing Residential Buildings in North Western Europe

A study by the Building Performance Institute Europe(BPIE) stated that upgrading old housing stock to higher energy efficiency through renovations and smart interventions would be a significant step towards meeting Europe’s Greenhouse Gas (GHG) reduction goals. Since 2011 Shell Global Solutions is investigating deep decarbonisation strategies for the residential sector through the EcoGenie project. The EcoGenie project constitutes an extreme learning position in order to determine cost-effective, socially beneficial and renewable options for residential heating systems for the immediate future. The Shell EcoGenie house has been under operation for the last 4 years where it is being used to test out new energy technologies available in the market and collect data about the energy use, occupancy and indoor climate. Based on the work of Bacher and Madsen, 2011, this research investigates the complexity and accuracy of dynamic thermal modelling with the objectives to predict the future heating demand and to identify sources of heat loss in the house. Using indoor/outdoor climate data, energy consumption data and prior knowledge about the heat transfer mechanisms, an initial thermal model is developed and its parameters are estimated by applying statistical solution algorithms based on the maximumlikelihood method. The estimated parameters represent physical properties of the building such as window area, heat capacities and thermal resistances. A hierarchy of models with increasing levels of complexity is investigated and suitable models are identified based on maximum likelihood values, statistical tests, data size and physical interpretation of the properties. The estimated parameters are discussed to understand the heat dynamics of the house. It is concluded that the heat capacity of the building envelope and its interaction with its adjacent components (indoor and outdoor air) significantly influences the heat dynamics of the house. In addition, a thermal resistance mechanism to model the effect of air leakage in existing houses, i.e. unwanted exchange of warm indoor air, is proposed and successfully applied. Future research is required to differentiate and to quantify conductive and convective heat transfer mechanism of air leakages. This research proposes a thermal model that forecasts the thermal behaviour of a residential building - the EcoGenie house - to predict its heating requirements for up to 48 hours. Additional sub-models are investigated to account for meaningful physical model boundaries and model improvements that simulate the heating system’s control mechanisms are tested with the objective to improve prediction accuracies. Further research should be considered into simulating controllers that can capture effects of rapid temperature changes, both indoor and ambient temperatures. Finally, and with an outlook to future management of smart grids and smart cities infrastructures, future research is needed to investigate and to build a library of thermal models which includes a large cross-section of existing building archetypes to account for diverging structural and physical properties of the building stock. The aggregated heating energy demands of buildings will be instrumental to ensure integration of and safe and secure supply of renewable energy sources.

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