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AlphaBuilding - Synthetic Dataset

Publicly accessible License 

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

LBNL. (2020). AlphaBuilding - Synthetic Dataset [data set]. Retrieved from https://dx.doi.org/10.25984/1784722.
Export Citation to RIS
Li, Han, Wang, Zhe, and Hong, Tianzhen. AlphaBuilding - Synthetic Dataset. United States: N.p., 21 Dec, 2020. Web. doi: 10.25984/1784722.
Li, Han, Wang, Zhe, & Hong, Tianzhen. AlphaBuilding - Synthetic Dataset. United States. https://dx.doi.org/10.25984/1784722
Li, Han, Wang, Zhe, and Hong, Tianzhen. 2020. "AlphaBuilding - Synthetic Dataset". United States. https://dx.doi.org/10.25984/1784722. https://data.openei.org/submissions/2977.
@div{oedi_2977, title = {AlphaBuilding - Synthetic 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 Jul 2, 2021

Submitted Jan 4, 2021

Organization

LBNL

Contact

Han Li

510.486.4691

Authors

Han Li

LBNL

Zhe Wang

LBNL

Tianzhen Hong

LBNL

DOE Project Details

Project Name Secure Algorithm Testbed for Energy Data Fusion

Project Number 34488

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