BEAR-Data: Analysis and Applications of an Open Multizone Building Dataset

被引：1

作者：

Bian, Yuexin ^{[1
]}

Fu, Xiaohan ^{[1
]}

Liu, Bo ^{[1
]}

Rachala, Rohith ^{[1
]}

Gupta, Rajesh K. ^{[1
]}

Shi, Yuanyuan ^{[1
]}

机构：

[1] Univ Calif San Diego, San Diego, CA 92103 USA

来源：

PROCEEDINGS OF THE 10TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION, BUILDSYS 2023 | 2023年

关键词：

Multi-zone building; Dataset; Thermal dynamics; HVAC controls;

D O I：

10.1145/3600100.3623740

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce BEAR-Data, an open dataset that captures the dynamics of a large multi-zone building by providing measurements of zone temperature and corresponding HVAC (Heating, Ventilation, and Air Conditioning) control actions for over 80 thermal zones. This paper presents a detailed description of the dataset's collection process and features, and data analysis of system utilization and building thermal patterns. To showcase the dataset's usefulness, we demonstrate one potential application of thermal dynamic identification and discuss how the released dataset supports various applications in building research, such as energy consumption forecasting, model-based control, and building performance bench-marking. We envision that the availability of this work can foster innovation and drive improvements in building energy systems.

引用

页码：240 / 243

页数：4

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