The deployment-dependence of occupancy-related models in building performance simulation

• Published in: Energy and buildings Vol. 117; pp. 313 - 320
• Main Authors: Mahdavi, Ardeshir, Tahmasebi, Farhang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.04.2016
• Subjects: Annual heating and cooling demands; Building performance simulation; Buildings; Computer simulation; Control systems; Deployment space; Mathematical models; Model evaluation statistics; Occupancy models; Phases; Predictive building systems control; Probabilistic methods; Probability theory; Query processing; Deployment space; Annual heating and cooling demands; Model evaluation statistics; Occupancy models; Building performance simulation; Predictive building systems control
• ISSN: 0378-7788
• DOI: 10.1016/j.enbuild.2015.09.065

•Selection of occupancy-related models in the context of simulation tool deployment.•A conceptual multi-dimensional simulation deployment space.•Two case studies of purpose-responsive evaluation of occupancy-related models. The relationship between the proper choice of occupancy-related models for building performance simulation and the pertinent purpose of the simulation-based query is not well understood. We thus address the necessary conditions for a better understanding of the context-dependence of occupancy-related model use in building performance simulation. First, given the multitude of application scenarios (involving different users, different phases of the building delivery process, different queries, etc.) in which building performance simulation can be deployed, we propose a conceptual framework in terms of a multi-dimensional simulation deployment space. To demonstrate the desirability and usability of such a framework, we provide two specific case studies, involving deployment instances of probabilistic and non-probabilistic occupancy models. One case study focuses on occupancy model deployment options in the context of simulation-based predictive building systems control. The second case study explores the implications of occupancy model selection in the context of simulation-based building design support.