Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Developing a dynamic method to assess the thermal performance of occupied dwellings
The domestic sector accounted for around 28% of the UK's end-use energy consumption in 2015; in order to meet the commitment of the Paris Agreement to limit the global average temperature increase to a maximum of 2degC carbon emissions from this sector must be reduced. The performance gap, the difference between the predicted and actual reduction in consumption achieved by an intervention, can significantly reduce the impact of efforts to improve the energy efficiency of houses, including new technology, retrofits, and designs for new-builds. Key contributors to this gap are methods used for energy consumption prediction which often include untested assumptions and exclude important effects. Construction companies can also be reluctant to allow post-intervention testing as most methods require an unoccupied building or significant experiment length which can be expensive or intrusive. To effectively reduce consumption in the domestic sector it is vital to have accurate knowledge of the performances of dwellings; this thesis aims to develop a new method of characterising thermal performance which is applicable to occupied buildings, requires minimal inputs and has known uncertainty. To this end, a new method combining Bayesian inference and lumped capacitance models has been developed, adapting one applied to individual elements. This method is advantageous as it allows a variety of representations of the house, shorter monitoring periods than most traditional, static methods, and produces distributions of the estimated parameters which are more informative than a value alone, particularly concerning the associated uncertainty. The influence of different model formations on the performance estimates for four case study buildings is investigated, and a model selection method is applied which penalises unnecessary parameters to identify the most appropriate physical representation of each period of data analysed; this varies dependent on both dwelling and time of year.
Developing a dynamic method to assess the thermal performance of occupied dwellings
The domestic sector accounted for around 28% of the UK's end-use energy consumption in 2015; in order to meet the commitment of the Paris Agreement to limit the global average temperature increase to a maximum of 2degC carbon emissions from this sector must be reduced. The performance gap, the difference between the predicted and actual reduction in consumption achieved by an intervention, can significantly reduce the impact of efforts to improve the energy efficiency of houses, including new technology, retrofits, and designs for new-builds. Key contributors to this gap are methods used for energy consumption prediction which often include untested assumptions and exclude important effects. Construction companies can also be reluctant to allow post-intervention testing as most methods require an unoccupied building or significant experiment length which can be expensive or intrusive. To effectively reduce consumption in the domestic sector it is vital to have accurate knowledge of the performances of dwellings; this thesis aims to develop a new method of characterising thermal performance which is applicable to occupied buildings, requires minimal inputs and has known uncertainty. To this end, a new method combining Bayesian inference and lumped capacitance models has been developed, adapting one applied to individual elements. This method is advantageous as it allows a variety of representations of the house, shorter monitoring periods than most traditional, static methods, and produces distributions of the estimated parameters which are more informative than a value alone, particularly concerning the associated uncertainty. The influence of different model formations on the performance estimates for four case study buildings is investigated, and a model selection method is applied which penalises unnecessary parameters to identify the most appropriate physical representation of each period of data analysed; this varies dependent on both dwelling and time of year.
Developing a dynamic method to assess the thermal performance of occupied dwellings
Hollick, Frances P. (Autor:in) / Elwell, C
28.07.2020
Doctoral thesis, UCL (University College London).
Hochschulschrift
Elektronische Ressource
Englisch
DDC:
690
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