Rethinking indoor thermal comfort in the era of rebound and pre-bound effect for the developing world: A systematic review.

This paper presents a review on thermal comfort research that is informed by changes in occupant behavior, lifestyle, and income leading to rebound or pre-bound effect. It explores the current state of research in thermal comfort domain through a systematic review to identify the gaps and opportunities specifically focusing on energy-intensive developing countries. This review argues that adaptive thermal comfort is a continuously evolving domain owing to dynamic modifications in occupant behavior occurring from changes in the cost of energy services and preference of comfort (rebound/pre-bound effect). A conceptual framework linking thermal comfort, rebound/pre-bound effect, and occupant behavior is forwarded through the introduction of an exogenous factor related to occupant well-being. The results ascertain that there is a need of localized thermal comfort model with an occupant-centric approach that can help in enhancing comfort and reducing energy consumption.

A Global Building Occupant Behavior Database.

This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants' schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.