Farhang Tahmasebi

The sensitivity of building performance simulation results to the choice of occupants’ presence models: a case study

The considerable performance implications of occupants’ presence and behaviour in buildings render the inclusion of corresponding models in simulation applications both necessary and critical. In this context, an important question concerns the implications of different occupancy modelling approaches for simulation results. The present contribution addresses this issue by modelling an office building to obtain heating and cooling demands and peak loads. To represent occupants’ presence patterns in the model, standard-based and observed diversity profiles, stochastic realizations of these profiles, and the full-year observational occupancy data are deployed. Subsequently, a sequence of simulation runs – involving Monte-Carlo simulations of models with stochastic profiles – provides the distributions of results. The study suggests that the viability of simulation results regarding building-level annual heating and cooling demands and peak heating and cooling loads is primarily dependent on the availability of reliable estimations of actual occupancy, rather than stochastic or non-stochastic representation of presence patterns.

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.

On the quality evaluation of behavioural models for building performance applications

Building performance assessment applications require multiple categories of input information. These include, aside from building construction and systems and external conditions, representations of inhabitants. It has been suggested that the representation of people as passive and static entities is unlikely to yield reliable building performance assessment and building operation planning. Rather, adequate representations of building inhabitants should account for dynamics of inhabitants’ presence in buildings and their control-oriented actions (e.g. interactions with buildings indoor environmental control devices and systems). To address these requirements, many recent model development efforts have explored the potential of advanced mathematical formalisms. However, the resulting occupancy-related behavioural models have rarely gone through a rigorous evaluation process. The present contribution is indeed motivated primarily by the lack of explicit procedures and guidelines for the evaluation of proposed user-related behavioural models. Specifically, we formulate a number of conditions that are necessary for systematic and dependable quality assessment of buildings’ inhabitants. Towards this end, we discuss both general model evaluation requirements and specific circumstances pertaining to behavioural models of building inhabitants. By using specific instances of such models, we intend to identify the requirements of a rigorous quality assurance process with regard to behavioural models in building performance assessment applications.

Stochastic models of occupants’ presence in the context building systems control

Building performance is influenced by occupants’ presence and actions. Knowledge of occupants’ future presence and behaviour in buildings is of central importance to the implementation efforts concerning predictive building systems control strategies. Specifically, prediction of occupants’ presence in office buildings represents a necessary condition for predicting their interactions with building systems. In the present contribution, we focus on evaluation of probabilistic occupancy models to explore the potential of using past monitored data in predicting future presence of occupants. Towards this end, we selected a university campus office area, which is equipped with a monitoring infrastructure and includes a number of open and closed offices. For the purpose of this study, we use monitored occupancy data and a previously developed stochastic occupancy model to predict the occupancy profiles on a daily basis. The predictions are then evaluated via comparison with monitored daily occupancy profiles. To conduct the model evaluation in a rigorous manner, a number of specific evaluation statistics were deployed. In general, the obtained level of predictive accuracy of the studied model was found to be rather low, which reveals the necessity of considering other approaches in modelling occupants’ presence (including non-probabilistic methods) for incorporation in predictive building systems control.

Structured Building Data Management: Ontologies, Queries, and Platforms

Building data monitoring, in general, and occupancy-related data collection in particular have the potential to provide deep performance feedback for: (1) operational optimization of existing facilities and (2) improving future designs. For instance, building monitoring can support energy and performance contracting, preventive building maintenance, smart load balancing, and model-predictive building systems control. Nevertheless, currently this potential is not sufficiently realized. To address a major gap in the current practice, the present chapter first introduces an ontology for the representation and incorporation of various kinds of building monitoring data in a number of applications such as building performance simulation tools and building automation systems. Subsequently, common data processing requirements are addressed and a number of typical queries are exemplified that building monitoring data repositories must support. Finally, data repository specifications and implementations for structured collection, storage, processing, and multi-user exchange of monitored data are described.

Special issue on the fundamentals of occupant behaviour research

It has been just six years since the Journal of Building Performance Simulation published a two-part special issue on modelling occupants. The motivation then, like now, is to improve the predictive power of simulation to support better design, retrofit, and operations of buildings. We will not elaborate here, as this background and motivation is flushed out in virtually every published paper on occupant modelling and simulation! In 2011, the guest editors of the special issue on occupant modelling noted that many areas required future research and development, with priorities of: developing occupant models from time use survey data; coupling occupant activity models with behaviour and movement/ presence; developing occupant models for broader contexts; and sharing model parameters. Since 2011, there has been a flurry of activity and formalized international collaboration. Most notably, International Energy Agency Energy in Buildings and Communities Annex 66 on “Definition and Simulation of Occupant Behavior in Buildings” has brought together over 100 experts from 16 countries to embark on a fouryear research programme. Annex 66 has played an important role in mixing engineers, architects, other designers, and social scientists. Annex 66 was the impetus for the current two-part special issue, for which the guest editors are active contributors. However, despite considerable advances made in the research community, the state of building occupant modelling and simulation research has barely penetrated practice (and O’Brien, Gaetani et al. in the current SI examine exactly this topic). Moreover, to paraphrase Aristotle, “the more we know, the more we know we don’t know”. Several papers in the current SI concluded that major fundamental questions remain unexplored. Given this circumstance, we set out to focus the current SI on contemporary fundamental contributions to the field of building occupant modelling and simulation, while following a structure that consists of three major stages of occupant research: data collection, modelling, and simulation. The conceptual structure of this two-part special issue is outlined in Figure 1.

Performance Simulation of External Metal Mesh Screen Devices: A Case Study

Early design decisions with regard to building facade characteristics play a significant role in the resulting buildings thermal performance. In this context, external metal mesh screens -used as a permanent second facade skin- are a rather new shading alternative, particularly in non-residential buildings. It has been suggested that such products can filter excessive incident solar radiation while maintaining the facade’s transparent quality. Given the multifaceted implications of this shading device for building energy performance, we undertook a detailed simulation-based study to evaluate the impact of metal mesh screens on annual energy demand for heating, cooling and electric lighting in different European climate zones. Possible design variations were considered in terms of mesh screen translucency, window to wall ratio and facade orientation. The feasibility of using such a shading strategy to provide passive cooling during summer was also explored, along with suitable ventilation scenarios. Toward this end, we examined a number of existing approaches to simulate metal mesh screens and identified their capabilities and limitations. A typical office space was tested in three European locations, taking local building construction standards into account. The results of this study can help planners in their choice of the appropriate shading strategy and provide recommendations for the application of metal mesh screens according to the climatic and architectural criteria.