Building Benchmark Data Platform
Abstract
This project is a three-year, four-laboratory collaboration to collect and curate a handful of high-resolution building systems datasets that have broad applicability to address highest-impact use cases. We will collect and curate high-resolution, well-calibrated time series of building operational and indoor/outdoor environmental data, which are crucial to understanding and optimizing building energy efficiency performance and demand flexibility capabilities as well as benchmarking energy algorithms.
- Authors:
-
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pacific Northwest National Laboratory
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
- Subject:
- 29 ENERGY PLANNING, POLICY, AND ECONOMY; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; Buildings, Energy, Efficiency, Facility, Engineering
- OSTI Identifier:
- 1968871
- DOI:
- https://doi.org/10.17041/BBD/1968871
Citation Formats
Sivaraman, Chitra. Building Benchmark Data Platform. United States: N. p., 2018.
Web. doi:10.17041/BBD/1968871.
Sivaraman, Chitra. Building Benchmark Data Platform. United States. doi:https://doi.org/10.17041/BBD/1968871
Sivaraman, Chitra. 2018.
"Building Benchmark Data Platform". United States. doi:https://doi.org/10.17041/BBD/1968871. https://www.osti.gov/servlets/purl/1968871. Pub date:Mon Dec 31 23:00:00 EST 2018
@article{osti_1968871,
title = {Building Benchmark Data Platform},
author = {Sivaraman, Chitra},
abstractNote = {This project is a three-year, four-laboratory collaboration to collect and curate a handful of high-resolution building systems datasets that have broad applicability to address highest-impact use cases. We will collect and curate high-resolution, well-calibrated time series of building operational and indoor/outdoor environmental data, which are crucial to understanding and optimizing building energy efficiency performance and demand flexibility capabilities as well as benchmarking energy algorithms.},
doi = {10.17041/BBD/1968871},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Dec 31 23:00:00 EST 2018},
month = {Mon Dec 31 23:00:00 EST 2018}
}
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