Building environmental control demand characterization based on multi-occupant coupled temporal and spatial occupancy

¹ School of Energy and Environment, Southeast University, Nanjing 211189, China
² College of Architecture and Environment, Sichuan University, Chengdu 610065, China
³ Department of Building Science, Tsinghua University, Beijing 100084, China

Abstract

Energy conservation is pivotal for decarbonizing buildings, where occupant-centric part-time- local-space control optimizes thermal supply to match temporal-spatial demand, reducing energy use without compromising comfort. Implementing this strategy requires understanding fine-grained occupancy patterns. While prior studies have examined occupancy characteristics, they predominantly focus on room- scale occupancy or individual behaviors, overlooking localized co-occupancy patterns of multi-occupants that shape collective environmental control demands. This gap hinders personalized, efficient solutions for heterogeneous demand. To address this, we developed a methodology to analyze coupled temporal-spatial occupancy characteristics at localized scales. It identifies prolonged-occupancy subzones within rooms and quantifies temporal (shared occupancy periods) and spatial overlaps (shared occupancy subzones) across individuals. Taking a residential household as example, the analysis contrasts single-occupant profiles with multi-occupant scenarios, revealing synchronous occupancy patterns critical for adaptive control. The findings advance the understanding of collective behaviors, enabling adaptive environmental control strategies and intelligent multi-scenario technologies that harmonize energy efficiency with occupant- centric flexibility. By addressing the interdependence of occupants in shared spaces, this work bridges a critical gap in building operations, offering a pathway to reconcile energy-saving objectives with real-world multi-occupant complexities. The proposed approach supports demand-responsive thermal management, balancing system-level efficiency with individualized comfort in dynamic environments.