Calibration of building dynamic thermal model using a unique whole house facility
Thermal modelling tools have been widely used in building industry at design stage,either for new build,or retrofitting existing,providing informed data for decision making.The accuracy of thermal models has been subject of much research in recent decades due to the potential large differences between predicted and ‘in-use’ performance-the so called ‘performance gap’.A number of studies suggested that better representing building physics and operation details in thermal models can improve the accuracy of predictions.However,full scale model calibration has always been challenging as it is difficult to measure all necessary boundary conditions in an open environment.The Energy House facility at University of Salford-a full sized end Terrance house sitting in an environmental chamber,presents a unique opportunity to conduct a full scale model calibration.The aim of this research is to calibrate the Energy House thermal models using various full scale measurements.The measurements used in this research include the co-heating tests for a whole house retrofit case study,thermal resistance from window covering and heating controls with thermostatic radiator valves(TRVs).Thermal models were created using IESVE-Integrated Environment Solutions Virtual Environment.IESVE is a well-established dynamic thermal simulation tool widely used in analysing the dynamic response of a building based on the hourly input of weather data.The evidence from this study suggests that thermal models using measured U-values and infiltration rates do perform better than the models using calculated thermal properties and assumed infiltration rates.The research suggests that better representations of building physics help thermal models reduce the performance gap.However,discrepancies still exist due to various other reasons which need to be considered individually with each case.In relative terms,i.e.variations in percentage,the predictions from thermal models tend to be more reliable than predicting the absolute numbers.
Model calibration Dynamic thermal modelling Co-heating Retrofit
Yingchun JI Will SWAN Richard FITTON Alex MARSHALL
SoBE,University of Salford,The Crescent,Salford,Great Manchester M5 4WT,UK
国际会议
武汉
英文
160-170
2018-08-21（万方平台首次上网日期，不代表论文的发表时间）