Assessing the performance gap of two dynamic thermal modelling software tools when comparing with real-time data in relation to thermal loss

Abstract

Managing thermal loss is a key topic that needs further investigation as it has a direct link to reducing the energy load in buildings. One of these thermal loss management methods can be the use of shading devices. Dynamic thermal models normally used at the early stages of the building design can play an important role in the decision-making process regarding the use of shading devices. This paper presents the results of a real-world study assessing the potential of using a sealed cellular blind as a passive energy conservation method, where the real-world results are compared with the simulated results generated with environmental design solutions limited thermal analysis software (EDSL Tas) and integrated environmental solutions virtual environment (IES VE). During the real-world study, a positive impact of having blinds was seen whereby the window surface temperature increased and office heating energy consumption was lowered. Both software tools were able to predict a similar trend of results for the window surface temperature in with and without blind scenarios whereas for energy consumption although in the presence of a blind a consistent correlation is seen between measured and calculated values but not without a blind. This can be attributed to the inability of the software tools in demonstrating the effect of infiltration in the absence of a blind or shading device i.e., a clear window scenario. The performance gap analysis regarding thermal loss between dynamic thermal models and real-world settings within buildings can enhance the predictability of the building energy software tools used by designers. Early design inputs within buildings can prevent costly building re-work to improve the building’s energy performance. This can also improve the understanding within the building industry of the importance of reducing thermal loss through the use of shading devices and ensuring the software tools used to model these devices are as close to real-world settings as possible.