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The “human dimensions” of energy use in buildings refer to the energy-related behaviors of key stakeholders that affect energy use over the building life cycle. Stakeholders include building designers, operators, managers, engineers, occupants, industry, vendors, and policymakers, who directly or indirectly influence the acts of designing, constructing, living, operating, managing, and regulating the built environments, from individual building up to the urban scale. Among factors driving high-performance buildings, human dimensions play a role that is as significant as that of technological advances. However, this factor is not well understood, and, as a result, human dimensions are often ignored or simplified by stakeholders. This paper presents a review of the literature on human dimensions of building energy use to assess the state-of-the-art in this topic area. The paper highlights research needs for fully integrating human dimensions into the building design and operation processes with the goal of reducing energy use in buildings while enhancing occupant comfort and productivity. This research focuses on identifying key needs for each stakeholder involved in a building’s life cycle and takes an interdisciplinary focus that spans the fields of architecture and engineering design, sociology, data science, energy policy, codes, and standards to provide targeted insights. Greater understanding of the human dimensions of energy use has several potential benefits including reductions in operating cost for building owners; enhanced comfort conditions and productivity for building occupants; more effective building energy management and automation systems for building operators and energy managers; and the integration of more accurate control logic into the next generation of human-in-the-loop technologies. The review concludes by summarizing recommendations for policy makers and industry stakeholders for developing codes, standards, and technologies that can leverage the human dimensions of energy use to reliably predict and achieve energy use reductions in the residential and commercial buildings sectors. [ABSTRACT FROM AUTHOR]

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10 min interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. The identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings. [ABSTRACT FROM AUTHOR]

• We reviewed methods used in social sciences that suit energy research. • Eight methods were found adequate to different purposes and life-cycle phases. • Different actors of the building sector can apply qualitative methods in their work. • Our findings support that both policies and buildings can be human-centred. Different stakeholders are involved in the energy consumption in buildings: occupants, designers, managers, operators, policymakers, technology developers and vendors. Therefore, it is necessary to understand their opinions and needs to optimise the energy consumption in buildings during their lifespan. Questionnaires and interviews have been applied; however, the literature still supports that energy research lacks social science approaches to improve their outcomes. Although limitations are inherent in qualitative methods (e.g., social desirability bias), much information such as human needs, preferences and opinions cannot be obtained through quantitative methods like building monitoring. Therefore, to have a deeper understanding of human-related aspects regarding the energy consumption in buildings, this literature review synthesises opportunities and main challenges of applying methods commonly used in social sciences. We reviewed papers published over the last five years (from 2014 to 2019) and presented information about questionnaires, interviews, brainstorming, post-occupancy evaluation, personal diaries, elicitation studies, ethnographic studies, and cultural probe. Increasing use of qualitative methods is expected to support the spread of human-centric policies and design/control of buildings, with a consequent overall optimisation of energy performance of buildings as well as the comfort of occupants. [ABSTRACT FROM AUTHOR]

• We conducted a review of technological innovations related to the human dimension of building performance. • We focused on recently documented technologies (from 2015 to 2019). • Our findings highlight that buildings are emerging as complex Cyber-Physical-Social Systems. • Proper use of technologies may reduce energy consumption and enhance indoor quality levels in buildings. The human dimension plays an essential role in the energy performance of buildings and is considered as significant as technological advances. Several studies highlighted the negative influence of occupant behaviour in underperforming buildings, while some support that technological innovations may reduce human-related uncertainties. Thus, one may consider that fully automated smart buildings are essential to achieve energy efficiency. However, if technology excludes people from decision-making processes, low acceptance and comfort/welfare levels may be reported from users. Therefore, the right combination of humans and technologies are expected to solve these problems. Buildings are emerging as complex Cyber-Physical Systems, including the Social dimension, and this provides an excellent opportunity to achieve high-performance outcomes, considering both technical and social aspects. Thus, the right choice among available up-to-date behavioural sensing – comprising active and passive sensors, as well as Kinect technology – are important in the Internet-of-Things (IoT) era. IoT-driven buildings can use real-time monitoring data to inform users and drive behavioural-based consumption change, which is an important aspect to achieve high-performance buildings and deliver user-centred services. An essential feature in this regard is to allow for human-in-the-loop approaches enabled by human-centric computing and smart devices, which has grown fast in the last few years. This literature review summarises applications and main challenges related to the combination of the human dimension and technological innovations in the building sector. This combination is expected to increase user welfare and reduce the energy consumption in buildings, as human and machine components of intelligence may complement each other regarding building performance. [ABSTRACT FROM AUTHOR]

Occupant behavior is one of the major factors influencing building energy consumption and contributing to uncertainty in building energy use prediction and simulation. Currently the understanding of occupant behavior is insufficient both in building design, operation and retrofit, leading to incorrect simplifications in modeling and analysis. This paper introduced the most recent advances and current obstacles in modeling occupant behavior and quantifying its impact on building energy use. The major themes include advancements in data collection techniques, analytical and modeling methods, and simulation applications which provide insights into behavior energy savings potential and impact. There has been growing research and applications in this field, but significant challenges and opportunities still lie ahead. [ABSTRACT FROM AUTHOR]

More than 30% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupant behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle. [ABSTRACT FROM AUTHOR]