Influence of occupant's heating set-point preferences on indoor environmental quality and heating demand in residential buildings

Abstract

The aim of this study was to switch from a deterministic approach of building energy simulation toward a probabilistic one that takes into account the occupants’ interactions with the building controls. A probabilistic approach is proposed and applied to simulate occupant behavior realistically. The methodology was based on probabilistic evaluation of both input and output variables of building energy simulations. The developed methodology can be applied in all aspects of occupant's interactions with building controls, such as window openings, shading devices, etc., to achieve more realistic predictions of energy consumption. The aim was to compare the obtained results with a traditional deterministic use of the simulation program. Based on heating set-point behavior of 13 Danish dwellings, logistic regression was used to infer the probability of adjusting the set-point of thermostatic radiator valves. Three different models of occupant's interactions with heating controls were obtained and implemented in a building simulation tool. The models of occupant's behavior patterns were used to investigate how different behavior patterns influence indoor climate quality and energy consumption. Simulation results were given as probability distributions of energy consumption and indoor environmental quality depending on occupant's behavior.