William O’Brien

A preliminary study of representing the inter-occupant diversity in occupant modelling

Significant diversity between occupants and their presence and actions results in major uncertainty with regard to predicting building performance. However, many current occupant modelling approaches – even stochastic ones – suppress occupant diversity by focusing on developing representative occupants. Accordingly, existing approaches tend to limit the ability of stochastic occupant models to provide probabilistic building performance distributions. Using occupancy data from 16 private offices, this paper evaluated three hypotheses: (1) occupant parameters have a continuous distribution rather than discrete; (2) modelling occupants from aggregated data suppresses diversity; and (3) randomly selecting occupant traits exaggerates synthetic population diversity. The paper indicates that samples sizes for the studied occupants would have more appropriately been an order of magnitude higher: hundreds. This introductory paper shows that there are many future research needs with regard to modelling occupants.

Field study of thermal comfort and occupant satisfaction in Canadian condominiums

ABSTRACT In Canada and much of the world, high-rise residential buildings with large glazing areas are increasing in popularity. These buildings are associated with lower thermal resistance envelopes and higher solar gains than more traditional construction with smaller windows. This study explores the comfort implications and usability in condominiums by performing a field study of 20 units: 10 with large window areas (LW) and 10 with medium-sized window areas. Occupant comfort was assessed in summer and winter, through two open-ended surveys, infrared thermography, and recorded interior temperature and humidity. LW occupants more often report uneven interior temperature distributions and windows as a source of discomfort in winter. One quarter of condo units experience condensation on windows, indicating window and frame improvements may benefit both groups. This exploratory study identifies key issues and occupant preferences within condominiums to guide future research on this building type.

Control-oriented inverse modeling of the thermal characteristics in an office

This article puts forward 12 graybox models at varying sensory model inputs and parameters. The parameters of each model were recursively estimated using the extended Kalman and the particle filtering methods. A systematic way to evaluate the predictive performance and the appropriateness of the models was introduced by using the data gathered in three perimeter offices. The simplest feasible models that can capture the timing and magnitude of local extrema were the models with five parameters and six inputs collected with low-cost sensors. They could robustly predict the indoor temperature at less than ±0.6°C mean absolute error over a 2-day horizon.

Sensing and Data Acquisition

Occupant sensing and data acquisition are essential elements for occupant behavior research. A wide range of different types of sensors has been implemented to collect rich information on occupants and their interactions with the built environment, such as presence, actions, power consumption, etc. This information establishes a foundation to study the physiological, psychological, and social aspects of occupant behavior. This chapter summarizes existing occupancy and occupant behavior sensing and data acquisition technologies in terms of field applications, and develops nine performance metrics for their evaluation. The reviewed technologies focus on both occupants’ presence and interactions with the built environment, and are grouped into six major categories: image-based, threshold and mechanical, motion sensing, radio-based, human-in-the-loop, and consumption sensing. This chapter provides an overview and discussion of different current state-of-the-art and future sensing technologies for researchers.

In Situ Approaches to Studying Occupants

This chapter provides an overview of in situ methods to study occupant behavior and presence. The aim of the chapter is to provide new and established researchers with a systematic approach to in situ occupant monitoring studies, while also providing illustrative examples to demonstrate the complexities and solutions for navigating this method. The chapter begins with a recommended systematic procedure for designing, conducting, and publishing in situ occupant studies. Following that, in situ-specific sensor technologies and sensing strategies are discussed in detail, with numerous real examples. This chapter devotes considerable discussion on nuances and practical issues that are frequently encountered during in situ studies, including: sensor placement, validation, access to studied spaces, monitoring spaces with multiple occupants, biases such as the Hawthorne effect, participant recruitment, and ethical considerations. Next, recommendations are provided for the level of documentation that should be provided when publishing in situ studies, with particular attention to the contextual factors that could influence the results. Finally, the use of surveys to complement in situ sensor-based methods is discussed.

Development of an office tenant electricity use model and its application for right-sizing HVAC equipment

As a consequence of considerable uncertainty about occupancy, occupant behaviour, and the corresponding effect on thermal loads in buildings, it is difficult to correctly size heating, ventilation, and air-conditioning (HVAC) equipment. Mechanical engineers avoid liability of potential under-capacity and corresponding thermal discomfort by making conservative assumptions about occupants. Meanwhile, there has been a surge in research on characterizing occupants through increasingly advanced modelling approaches to support building performance simulation, but these have focused on agent-based models representing individual occupants, which may be impractical for building-level HVAC equipment sizing. This paper describes the development of a data-driven stochastic tenant model using 15 months of data from 17 independent commercial tenants. The model is implemented in EnergyPlus to examine its potential for an improved HVAC equipment-sizing procedure. The results show: the standard schedules are reasonable though conservative; oversizing equipment does not greatly improve comfort; and the tremendous importance of modelling inter-tenant diversity.

Occupancy and Occupants’ Actions

Occupants’ presence and actions within the built environment are crucial aspects related to understanding variations in energy use. Within this chapter, first, a nomenclature for the field of research dealing with occupants in buildings is defined. This nomenclature distinguishes between occupants’ presence and behavior, states and actions, adaptive triggers, non-adaptive triggers, and contextual factors. Second, an extensive list of occupant behaviors is provided and categorizations of occupants’ actions are introduced. The list includes most of the possible phenomena that researchers may wish to study, measure, and ultimately model. The categories are physiological, individual, environmental, and spatial adjustments. Third, a list of adaptive and non-adaptive triggers together with contextual factors that could influence occupant behavior is presented. Individual elements are further grouped into physical environmental, physiological, psychological, and social aspects. Finally, a comprehensive table of studies related to occupant behavior and the corresponding significant and non-significant predictors, based on an extensive literature review, is shown. This table highlights areas of research where numerous studies have been conducted, as well as areas where hardly any research has been published. The conclusion highlights the importance of publishing future occupant monitoring campaigns with sufficient detail to inform future researchers and save redundant effort. Such detail is especially necessary in relation to the methodology, including, for example, a clear description of the type of variables monitored, and in relation to the results, where both the influencing factors that were found to be significant and insignificant should be documented.

Concluding Remarks and Future Outlook

This book has defined relevant terms in the field of building occupant research and provided a comprehensive overview of the steps required to study occupants’ behavior in buildings, whether in situ or through laboratory experiments or surveys. It has offered both broad and specific guidance about research design and methodological approaches, including data collection, storage, and processing, and presented relevant discussions of ground truth and ethics. At the time of this book’s publication, the field of occupant research is relatively new, but with rapidly increasing activity. Therefore, the motivation was to significantly improve the state of the art of occupant behavior research methodologies, considering the multidisciplinarity of the field by including authors from the broad backgrounds of engineering, architecture, interior design, information technology, and social sciences. Readers of this book will realize that the field of occupant behavior research still holds a large number of unanswered fundamental questions to be tackled. Thus, this concluding chapter provides the editors’ perspectives on research needs future outlook for the field of occupant behavior.

Introduction to Occupant Research Approaches

There are numerous methods of collecting occupant-related data for the purpose of researching building occupants, each with its own strengths and weaknesses. The objective of this chapter is to guide the decision-making process for researchers who are about to embark on a new occupant data collection campaign. This chapter introduces Chaps. 6– 8 by overviewing four methods for occupant research: in situ, laboratory, survey, and virtual reality. For each method, the advantages and disadvantages are laid out based on findings in the literature and the authors’ experiences. Next, a comprehensive list of occupant-related phenomena of interest is provided, along with a qualitative discussion of the merits of each data collection method for studying them. Finally, mixed methods research approaches—whereby multiple, complementary approaches are adopted in a single study—are briefly discussed. Following this chapter, the reader is presented with three chapters that provide recommended best practice for each of in situ (Chap. 6), laboratory (Chap. 7), and survey (Chap. 8) methods to researching occupants in occupants.

Building energy model reduction using model-cluster-reduce pipeline

This paper introduces a novel building energy model reduction pipeline called ‘model-cluster-reduce’. It is centred around using clustering techniques to identify archetypes and eliminate redundant zones. An experiment was conducted in this paper using a detailed EnergyPlus model generated from building information modelling directly. A total number of four reduced models were generated and compared against the original model, random select models and an expert model. The reduced models estimated annual energy simulation and parametric simulation results within 5% error margin, while reducing the overall simulation time by 95%. The proposed method – which is aimed at large models where inter-zone heat transfer is not significant – can be used to approximate parametric simulations or optimizations with greatly reduced runtime.