• Energy Research

Abstract Occupant behavior is now widely recognized as a major contributing factor to uncertainty of building performance. While a surge of research on the topic has occurred over the past four decades, and particularly the past few years, there are many gaps in knowledge and limitations to current methodologies. This paper outlines the state-of-the-art research, current obstacles and future needs and directions for the following four-step iterative process: (1) occupant monitoring and data collection, (2) model development, (3) model evaluation, and (4) model implementation into building simulation tools. Major themes include the need for greater rigor in experimental methodologies; detailed, honest, and candid reporting of methods and results; and development of an efficient means to implement occupant behavior models and integrate them into building energy modeling programs.

Abstract Occupant behavior is now widely recognized as a major contributing factor to uncertainty of building performance. While a surge of research on the topic has occurred over the past four decades, and particularly the past few years, there are many gaps in knowledge and limitations to current methodologies. This paper outlines the state-of-the-art research, current obstacles and future needs and directions for the following four-step iterative process: (1) occupant monitoring and data collection, (2) model development, (3) model evaluation, and (4) model implementation into building simulation tools. Major themes include the need for greater rigor in experimental methodologies; detailed, honest, and candid reporting of methods and results; and development of an efficient means to implement occupant behavior models and integrate them into building energy modeling programs.

Phase change materials (PCMs) can store and release thermal energy. The energy is stored when the material goes through a solid-to-liquid phase change, and released in the reverse process. Such materials can contribute to the mitigation of overheating in buildings, if their melting and solidification temperatures are in a suitable range. The present contribution entails a computational examination of this potential as relevant to overheating mitigation in typical residential units in the Central European context of Vienna, Austria. Thereby, multiple variations of PCM application (size, thickness, location, and application thickness) under different contextual settings (fenestration and insulation, boundary conditions in terms of weather) were simulated and comparatively evaluated. Results indicate that certain PCM application configurations can significantly influence indoor thermal condition. For instance, PCM elements with larger surface areas displayed a more pronounced effect as compared to bulkier elements with smaller surface areas. Likewise, ceiling-integrated PCM application was found to be more effective that those involving other room surfaces. The results also highlight the importance of rooms ventilation regime if the PCM application potential toward overheating mitigation is to be effectively harvested.

Phase change materials (PCMs) can store and release thermal energy. The energy is stored when the material goes through a solid-to-liquid phase change, and released in the reverse process. Such materials can contribute to the mitigation of overheating in buildings, if their melting and solidification temperatures are in a suitable range. The present contribution entails a computational examination of this potential as relevant to overheating mitigation in typical residential units in the Central European context of Vienna, Austria. Thereby, multiple variations of PCM application (size, thickness, location, and application thickness) under different contextual settings (fenestration and insulation, boundary conditions in terms of weather) were simulated and comparatively evaluated. Results indicate that certain PCM application configurations can significantly influence indoor thermal condition. For instance, PCM elements with larger surface areas displayed a more pronounced effect as compared to bulkier elements with smaller surface areas. Likewise, ceiling-integrated PCM application was found to be more effective that those involving other room surfaces. The results also highlight the importance of rooms ventilation regime if the PCM application potential toward overheating mitigation is to be effectively harvested.

AbstractOccupancy patterns in building performance simulation are typically represented via fixed diversity profiles. More recently, stochastic models have been developed to generate random non-repeating occupancy profiles. In this context, an important question concerns the implications of occupancy modelling approaches for simulation results. The present contribution involves a virtual office building for which annual and peak heating and cooling demands are simulated. Thereby, both conventional and random profiles are deployed and different levels of occupants’ interaction with building systems are modelled. For the specific case considered here, the results do not show a noticeable difference between conventional and stochastic occupancy models.

AbstractOccupancy patterns in building performance simulation are typically represented via fixed diversity profiles. More recently, stochastic models have been developed to generate random non-repeating occupancy profiles. In this context, an important question concerns the implications of occupancy modelling approaches for simulation results. The present contribution involves a virtual office building for which annual and peak heating and cooling demands are simulated. Thereby, both conventional and random profiles are deployed and different levels of occupants’ interaction with building systems are modelled. For the specific case considered here, the results do not show a noticeable difference between conventional and stochastic occupancy models.

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.