In the last four decades several methods have been used to model occupants' presence and actions (OPA) in buildings according to different purposes, available computational power, and technical solutions. This study reviews approaches, methods and key findings related to OPA modeling in buildings. An extensive database of related research documents is systematically constructed, and, using bibliometric analysis techniques, the scientific production and landscape are described. The initial literature screening identified more than 750 studies, out of which 278 publications were selected. They provide an overarching view of the development of OPA modeling methods. The research field has evolved from longitudinal collaborative efforts since the late 1970s and, so far, covers diverse building typologies mostly concentrated in a few climate zones. The modeling approaches in the selected literature are grouped into three categories (rule-based models, stochastic OPA modeling, and data-driven methods) for modeling occupancy-related target functions and a set of occupants' actions (window, solar shading, electric lighting, thermostat adjustment, clothing adjustment and appliance use). The explanatory modeling is conventionally based on the model-based paradigm where occupant behavior is assumed to be stochastic, while the Revised Manuscript with No Changes MarkedClick here to view linked References data-driven paradigm has found wide applications for the predictive modeling of OPA, applicable to control systems. The lack of established standard evaluation protocols was identified as a scientifically important yet rarely addressed research question. In addition, machine learning and deep learning are emerging in recent years as promising methods to address OPA modeling in real-world applications.

In recent years, research has emerged to quantitatively and qualitatively understand occupants' interactions with buildings. However, there has been surprisingly little research on building interfaces and how their design, context (e.g., location), and underlying logic impact their usability and occupants' perceived control, as well as the resulting comfort and energy performance. Research is needed to better understand how occupants interact with building interfaces in both commercial and residential applications; both applications are important to address as there are many differences in interface types, level of control and understanding, and even expectations of engagement. This paper provides a cursory review and discussion of select common building interfaces: windows, window shades/blinds, thermostats, and lighting controls. The goal of this paper is to review literature related to these human-building interfaces to explore interface characteristics, current design and use challenges, and relationships between building interfaces and occupants. Human-building interface interactions are complex, more research is needed to understand design, use, and characteristics. Common themes emerged throughout the literature review to explain occupant interactions (or lack of interactions) with building interfaces, which included thermal and visual comfort, ease and access of control, interface/control placement, poor interface/control design, lack of understanding, and social-behavioral dynamics.

Buildings’ expected (projected, simulated) energy use frequently does not match actual observations. This is commonly referred to as the energy performance gap. As such, many factors can contribute to the disagreement between expectations and observations. These include, for instance, uncertainty about buildings’ geometry, construction, systems, and weather conditions. However, the role of occupants in the energy performance gap has recently attracted much attention. It has even been suggested that occupants are the main cause of the energy performance gap. This, in turn, has led to suggestions that better models of occupant behavior can reduce the energy performance gap. The present effort aims at the review and evaluation of the evidence for such claims. To this end, a systematic literature search was conducted and relevant publications were identified and reviewed in detail. The review entailed the categorization of the studies according to the scope and strength of the evidence for occupants’ role in the energy performance gap. Moreover, deployed calculation and monitoring methods, normalization procedures, and reported causes and magnitudes of the energy performance gap were documented and evaluated. The results suggest that the role of occupants as significant or exclusive contributors to the energy performance gap is not sufficiently substantiated by evidence.

Differences in building operator strategies can significantly affect building energy use and occupant comfort. However, it seems that the daily work of building operators and facility managers is still largely based on heuristics and individual experiences. In this work, we have investigated the current data collection methods during the operation and its daily use in buildings as well as the handling of occupant behavior, comfort, and user complaints based on interviews with ten building operators in Germany. These interviews were conducted as part of an international study of building operator OCC (Occupant-Centric Control) strategies, under the auspices of the IEA EBC Annex 79. The results of the interviews clearly reflect, that until now, communication between building operators and building occupants plays a more important role in optimizing or adjusting building operations to meet occupant needs than the data collected by BAS, which is mainly used to detect faults and check the system status of key HVAC components when faults occur. In some cases, the real-time data are applied for the adjustment of set points and schedules depending on measured conditions; however, customization of set points considering the user’s preferred temperature or ventilation rate or building operation based on occupancy detection has not yet been implemented in the considered buildings. The overall objective of this contribution to building operation research is to highlight best practices and identify white spaces that fulfill occupant requirements and achieve a high level of energy-efficiency. The presented findings identify current gaps between science and practice in the field of sustainable optimization of building operation, but also point out real-world starting points for future research and development.

For the transition of the energy system from the status quo to a point where the political targets are achieved, the largest potentials for energy and CO2 savings are in the building sector, especially due to older unrenovated buildings. For the state of Bavaria, preliminary investigations have shown that approximately 27 % of the total final energy demand is provided for space heating and domestic hot water preparation of the residential building stock. Extensive measures must be taken in this sector for a successful energy transition. To make the best use of available resources, investigations with realistic reference building models are essential. Previous studies have shown that a significant classification of the building stock can performed and large parts of it can be represented with a limited number of reference buildings models. In this study, it is shown that the representativity can be further increased by selective grouping of the categories while keeping the number of necessary models as small as possible. In addition, a method is presented to model reference buildings using statistical data. The methods of grouping and modelling as well as possible applications and outputs of the generated models are shown for a realistic example.