CONICET | Buscador de Institutos y Recursos Humanos

The effects of occupancy and user behaviour have been recently recognized as one of the leading influences of energy consumption in buildings: They are either random, or purpose-driven (e.g. entering/leaving a room, consuming domestic hot water, using an appliance) or comfort-related (e.g. adjusting a thermostat, opening a window for ventilation, closing blinds). They change the indoor environment in terms of temperature, humidity, illuminance levels, air quality etc. which influences total energy consumption of a building. These are important factors in the study of uncertainties between building performance simulation at a project stage and the real response of the built dwelling. There is a strong need for more accurate approaches of modelling occupant behaviour to support planners and building managers during the design phase and building operation. The aim of this research is to find predictable parameters to obtain occupancy and user behaviour profiles that could be taken into account for building simulation in dynamic prediction software such as ?Energy Plus?. For that purpose, temperatures of a real-life building operation were monitored in the city of Mendoza, Argentina (32º 40´ S; 68º 51´ W y 750 masl) assessing the thermal impact of opening a window for ventilation in summer. At the same time, every user action of opening / closing a window was registered. Data obtained was statistically analyzed with ?R? software. Logistic regression was used to infer probabilities of opening or closing windows. Typical occupancy and user profiles were developed. Compared variables established a statistical relationship between environmental factors and occupant actions. Analyzed variables allow predictable outcomes that are the first step to emulate stochastic human behaviour and therefore reduce the gap between real and simulated building performance.