The Impact of the Thermal Comfort Models on the Prediction of Building Energy Consumption

Abstract

Building energy assessment software/programs use various assumptions and types of thermal comfort models to forecast energy consumption. This paper compares the results of using two major thermal comfort models (adaptive thermal comfort and the predicted mean vote (PMV) adjusted by the expectancy factor) to examine their influence on the prediction of the energy consumption for several full-scale housing experimental modules constructed on the campus of the University of Newcastle, Australia. Four test modules integrating a variety of walling types (insulated cavity brick (InsCB), cavity brick (CB), insulated reverse brick veneer (InsRBV), and insulated brick veneer (InsBV)) were used for comparing the time necessary for cooling and heating to maintain internal thermal comfort for both models. This research paper exhibits the benefits of adopting the adaptive thermal model for building structures. It shows the effectiveness of this model in helping to reduce energy consumption, increasing the thermal comfort level for the buildings, and therefore reducing greenhouse emissions.