Influence of occupant's behaviour on indoor environmental quality and energy consumptions

Buildings are dynamic, and the interactions of operators, occupants, and designers all influence the way in which buildings will perform. At the core of this research is the belief that technical solutions alone are not sufficient to face great challenges of saving energy while still maintaining or even improving current comfort levels. Buildings are engineered using tested components and generally reliable systems whereas people can be unreliable, variable, and perhaps even irrational. The studies in literature also reveal the gap between how designers expect occupants to use a building, and how they will actually operate it. Actually, there is often a significant discrepancy between the designed and the real total energy use in buildings. The reasons of this gap are generally poorly understood and largely have more to do with the role of human behaviour than the building design. Knowledge of user’s interactions within building is crucial to better understanding and a more valid predictions of building performance (energy use, indoor climate) and effective operation of building systems. The present work undertakes a theoretical and empirical study of the uncertainty of energy consumption assessment related to occupants’ behaviour in residential buildings. The main purpose of this research is to propose a methodology to model the user behaviour in the context of real energy use and applied it to a case study. The methodology, based on a medium/long-term monitoring, is aimed at shifting towards a probabilistic modelling the occupant behaviour related to the control of indoor environment with respect to the energy-related issues. The goal is to determine users’ behavioural patterns describing user’s interaction with the building controls. The procedure is applied first at modelling occupants’ interactions with windows (opening and closing behaviour) and then at modelling the heating set-point preferences. This research is based on the assumption that only switching from a deterministic approach in building energy simulation to a probabilistic one it will be feasible to obtain energy consumption prediction closer to reality. This probability is related to variability and unpredictability during the whole building operation. In this way, it become crucial to take into account the occupants’ presence and interactions with the building and systems. Actually, building energy simulation tools often reproduce building dynamics using numerical approximations of equations modelling only deterministic (fully predictable and repeatable) behaviours. In such a way, “occupant behaviour simulation” could refer to a computer simulation generating “fixed occupant schedules”, representing a fictional behaviour of a building occupant over the course of a single day. This is an important limitation of energy simulation tools for modelling occupant’s interactions with buildings, and highlights that the results are essentially unrealistic. The whole dissertation consists of four parts. In the first part the development of a theoretical model of the occupant behaviour is described based on a comprehensive literature review. With respect to the complexity of this issue, a specific literature survey is addressed to derive the most dominating driving forces useful for a more accurate description of occupant behaviour related to the habits of opening and closing the windows. Existing studies on the topic of window opening behaviour are highlighted and a theoretical framework to deal with occupants’ interactions with building controls, aimed at improving or maintaining the preferred indoor environmental conditions, is elaborated. The analysis of the literature highlights how a shared approach on identifying the driving forces for occupants’ window opening and closing behaviour has not yet been reached. In the second part of this dissertation, a method for defining occupant behaviour in simulation programs based on measurements is proposed. The proposed approach is based on measurements of both indoor and outdoor environmental parameters and the behavioural actions of the building occupants (window opening, TRV’s set point adjustments, occupancy sensors, etc..). From the collected data, different suitable user behavioural patterns (models) were defined by means of statistical analysis (logistic regression, Markov chain, etc..) and implemented in a building energy simulation tool. Moreover, a probabilistic distribution instead that a single value is preferred as a representation of energy consumptions. The proposed procedure was applied for modelling the human behaviour related to the window opening and closing and the change in thermostatic radiator valves (TRVs), and its implementation in the simulation tool IDA ICE so that the results obtained are probabilistic in nature. The third part of the dissertation deals with the validation of the obtained models to ensure the effectiveness of the models. In this section, the validation procedure is carried out using other data coming from an analogue dataset of dwellings where the same indoor and outdoor parameters are measured. These data will be used to validate the models of window opening behaviour. The validation is performed by comparing the probabilities of window opening and closing with the actual measured state of the windows in the dwellings. In literature, a variety of logistic models expressing the probability with which actions will be performed on windows, as a function of indoor temperature, outdoor temperature or both. Previously published models are then also compared using this validation procedure. The fourth part of the thesis represents a sightseeing of the future application of this field of research, focusing on the understanding of how technology and building design can improve energy efficiency exploiting the goal of making users more aware and hence careful on energy consumption. Overall, this dissertation highlights the importance of researching the individual’s behaviour in order to understand the differences in real building energy usage. Besides being limited to the cases of window opening and closing for most of the analyses, the methodology presented can also be applied to other types of behaviours.