An experimental comparative study of energy saving based on occupancy-centric control in smart buildings

被引:1
作者
Qaisar, Irfan [1 ]
Liang, Wei [2 ]
Sun, Kailai [1 ,2 ]
Xing, Tian [1 ]
Zhao, Qianchuan [1 ]
机构
[1] Tsinghua Univ, Ctr Intelligent & Networked Syst, Dept Automat, Beijing 100084, Peoples R China
[2] Natl Univ Singapore, Coll Design & Engn, Dept Built Environm, Singapore 117566, Singapore
基金
中国国家自然科学基金;
关键词
Energy saving; Occupancy-centric control; Building; EnergyPlus; OpenStudio; HVAC control; BEHAVIOR; SYSTEMS; CONSUMPTION; SIMULATION; OFFICE; IMPACT;
D O I
10.1016/j.buildenv.2024.112322
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Buildings account for approximately one-third of global energy consumption and greenhouse gas emissions. Accurate occupancy data is critical for enabling energy-efficient control strategies and enhancing comfort in buildings. However, most current research on multi-zone occupancy-centric control (OCC) relies on simulated rather than real-world occupancy data. Additionally, the optimal operational intervals of existing OCC-based HVAC systems have not been fully explored in dynamic indoor environments. This study presents an extensive experimental study evaluating the impact of multi-zone real-world OCC systems on energy conservation and comfort in a multi-zone building. We collected real-world occupancy data using vision-based methods and developed HVAC control strategies using operational intervals of 5, 10, 15, 30, and 60 min to evaluate their effects on energy efficiency and occupant comfort. Simulations were performed using OpenStudio with EnergyPlus. The results indicate that customized operational intervals significantly improve both energy efficiency and occupant comfort. Shorter intervals can provide effective energy savings in dynamic settings, while longer intervals yield improved comfort and energy efficiency in more stable environments. This study demonstrates the effectiveness of OCC systems in optimizing energy usage and comfort and sets the stage for future developments in building management strategies. Emerging trends, such as integrating large language models into OCC, are also discussed for future exploration.
引用
收藏
页数:16
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