"Womp Womp! Your browser does not support canvas :'("

AlphaBuilding - Synthetic Buildings Operation 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

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 -
Export Citation to RIS
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: 2025-05-08}, 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

Han Li

Lawrence Berkeley National Laboratory

Zhe Wang

Lawrence Berkeley National Laboratory

Tianzhen Hong

Lawrence Berkeley National Laboratory

DOE Project Details

Project Name Secure Algorithm Testbed for Energy Data Fusion

Project Number 34488

Share

Submission Downloads