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
Lawrence Berkeley National Laboratory. (2020). AlphaBuilding - Synthetic Buildings Operation Dataset [data set]. Retrieved from https://dx.doi.org/10.25984/1784722.
Li, Han, Wang, Zhe, and Hong, Tianzhen. AlphaBuilding - Synthetic Buildings Operation Dataset. United States: N.p., 21 Dec, 2020. Web. doi: 10.25984/1784722.
Li, Han, Wang, Zhe, & Hong, Tianzhen. AlphaBuilding - Synthetic Buildings Operation Dataset. United States. https://dx.doi.org/10.25984/1784722
Li, Han, Wang, Zhe, and Hong, Tianzhen. 2020. "AlphaBuilding - Synthetic Buildings Operation Dataset". United States. https://dx.doi.org/10.25984/1784722. https://data.openei.org/submissions/2977.
@div{oedi_2977, title = {AlphaBuilding - Synthetic Buildings Operation Dataset}, author = {Li, Han, 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.}, doi = {10.25984/1784722}, url = {https://data.openei.org/submissions/2977}, journal = {}, number = , volume = , place = {United States}, year = {2020}, month = {12}}
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