A novel monitoring and modelling technique for energy-related occupant behaviour

Abstract

The present work focuses on the development of a novel application that aims to better understand energy-related indoor occupant behaviour (OB). The thesis briefly introduces the key features of OB, presents the current state of the art and highlights the present challenges related to this field. The goal of the thesis is to present how potential challenges can be addressed with the use of a novel monitoring technique for in-situ occupant tracking. It is a depth registration technique that has practical implementations in various applications focusing on surface scanning. The main goal of the use of this technique in OB studies is to increase the quality of the measurement resolution to better understand the reasons for occupant activities regarding indoor energy use. It is expected that with an increase in the measurement resolution, it will be possible to observe and collect new information about occupants and their energy utilization. Therefore, it will be possible to detect avoidable waste of energy. The proposed monitoring technique has not previously been commercially implemented in this research domain. Thus, there were no guidelines allowing for quick implementation. The methodology presented in the thesis describes step-by-step all the basic information required to understand the ideas and proposals for device utilization. Extended explanations are included in the appendices, and each subchapter refers to relevant appendices. Beyond the direct monitoring of occupants, the thesis explains the use of the collected data and shows how the data can be implemented in an agent-based model (ABM). The proposed model focuses on direct simulation of an occupant’s activities by recreating these activities through the portrayal of the occupant as an agent. The main functionalities that are provided by the model enable simulation of occupant movement, sensation of the thermal environment, interaction with indoor appliances and decision-making processes. The results obtained from the simulation show that a novel approach for the simulation of occupants is achievable. The OB represented by the ABM can be implemented as a calculation engine, which considers the occupant’s actions as activity triggers. The model is designed to connect various scientific specialities that focus on OB aspects, and combines each of the aspects into one common platform. The communication between scientific specialities that can be initialised by the proposed platform will bring a greater understanding of energy-related OB. Consequently, it may lead to a greater reduction in the use of energy resources without compromising occupants’ indoor comfort.