A synthetic building operation dataset

• Published in: Scientific data Vol. 8; no. 1; pp. 213 - 13
• Main Authors: Li, Han, Wang, Zhe, Hong, Tianzhen
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.08.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166/986; 639/4077/2790; 706/4066/4065; Air flow; civil engineering; Computer applications; Data Descriptor; Datasets; Energy; energy and behavior; energy modelling; Humanities and Social Sciences; Metadata; multidisciplinary; POWER TRANSMISSION AND DISTRIBUTION; Science; Science (multidisciplinary); Temperature preferences; Water flow; Weather
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-021-00989-6

This paper presents a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years’ historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants’ diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls. Measurement(s) energy consumption • power demand • humidity • air flow rate • Occupancy • water flow rate Technology Type(s) computational modeling technique Factor Type(s) temporal interval Sample Characteristic - Environment building Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14682948