State-of-the-art review of occupant behavior modeling and implementation in building performance simulation

Abstract

Occupant Behavior (OB) is one of the major drivers of building energy consumption. However, OB is usually oversimplified in Building Performance Simulation (BPS), resulting in a significant performance gap between actual and simulated building energy use. Thus, understanding the true nature of OB and its accurate representation within BPS is crucial. Despite the existence of many review articles that focus on several aspects of OB, the vast majority of reviews are centered on a specific aspect of OB modeling, scattering the main findings among various studies. The literature still lacks a comprehensive review that compiles and analyzes the recent studies on each stage of OB such as data collection and analysis, modeling, integration of OB models into BPS, validation, and presentation of the data in a suitable format. To this end, the present review summarizes, compiles, and analyzes the recent literature on every aspect of OB in BPS, and presents an up-to-date evaluation of the multiple facets of OB modeling in BPS. It aims to present the development and implementation steps of the OB model within BPS tools. A general outline characterizing the recommended workflow for modeling OB in BPS is described. A brief categorization of data collection methods used in OB modeling is presented. Common quantitative OB modeling approaches in BPS i.e., Stochastic, Statistical, Data mining, and Agent-based methods, are elucidated. The main applications, advantages, and limitations of each model are discussed. The available literature on the influence of different OB patterns and occupants’ interaction with building systems, such as cooling, lighting, shading, and appliances, on building energy performance is evaluated. In brief, this study provides an up-to-date review of OB in BPS, offering valuable insights to both academic researchers and industrial professionals to aid them in choosing and adopting correct strategies to accurately model OB and incorporate it into available BPS tools.