AlphaBuilding - Synthetic Buildings Operation Dataset
This is 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.
Citation Formats
TY - DATA
AB - This is 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.
AU - Li, Han
A2 - Wang, Zhe
A3 - Hong, Tianzhen
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.25984/1784722
KW - building
KW - energy
KW - simulation
KW - synthetic data
KW - occupancy
KW - HVAC
KW - lighting
KW - miscellaneous electric loads
KW - MEL
KW - energy consumption
KW - environmental
KW - efficiency
KW - AlphaBuilding
KW - Synthetic
LA - English
DA - 2020/12/21
PY - 2020
PB - Lawrence Berkeley National Laboratory
T1 - AlphaBuilding - Synthetic Buildings Operation Dataset
UR - https://doi.org/10.25984/1784722
ER -
Li, Han, et al. AlphaBuilding - Synthetic Buildings Operation Dataset. Lawrence Berkeley National Laboratory, 21 December, 2020, Open Energy Data Initiative (OEDI). https://doi.org/10.25984/1784722.
Li, H., Wang, Z., & Hong, T. (2020). AlphaBuilding - Synthetic Buildings Operation Dataset. [Data set]. Open Energy Data Initiative (OEDI). Lawrence Berkeley National Laboratory. https://doi.org/10.25984/1784722
Li, Han, Zhe Wang, and Tianzhen Hong. AlphaBuilding - Synthetic Buildings Operation Dataset. Lawrence Berkeley National Laboratory, December, 21, 2020. Distributed by Open Energy Data Initiative (OEDI). https://doi.org/10.25984/1784722
@misc{OEDI_Dataset_2977,
title = {AlphaBuilding - Synthetic Buildings Operation Dataset},
author = {Li, Han and Wang, Zhe and Hong, Tianzhen},
abstractNote = {This is 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.},
url = {https://data.openei.org/submissions/2977},
year = {2020},
howpublished = {Open Energy Data Initiative (OEDI), Lawrence Berkeley National Laboratory, https://doi.org/10.25984/1784722},
note = {Accessed: 2025-05-29},
doi = {10.25984/1784722}
}
https://dx.doi.org/10.25984/1784722
Details
Data from Dec 21, 2020
Last updated Jan 2, 2024
Submitted Jan 4, 2021
Organization
Lawrence Berkeley National Laboratory
Contact
Han Li
510.486.4691
Authors
Research Areas
Keywords
building, energy, simulation, synthetic data, occupancy, HVAC, lighting, miscellaneous electric loads, MEL, energy consumption, environmental, efficiency, AlphaBuilding, SyntheticDOE Project Details
Project Name Secure Algorithm Testbed for Energy Data Fusion
Project Number 34488
