The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017
The Foundational Industry Energy Dataset (FIED) addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization by facility. Each facility is identified by a unique registryID, based on the U.S. Environmental Protection Agency (EPA) Facility Registry Service, and includes its coordinates and other geographic identifiers. Energy-using units are characterized by design capacity, as well as their estimated energy use, greenhouse gas emissions, and physical throughput using 2017 data from the EPA's National Emissions Inventory and Greenhouse Gas Reporting Program.
An overview of the derivation methods is provided in a separate technical report which will be linked after publication. The Python code used to compile the dataset is available in a GitHub repository. An updated 2020 version is under development.
Citation Formats
National Renewable Energy Laboratory (NREL). (2024). The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017 [data set]. Retrieved from https://dx.doi.org/10.25984/2437657.
McMillan, Colin, Schoeneberger, Carrie, Supekar, Sarang, and Thierry, David. The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017. United States: N.p., 01 Jul, 2024. Web. doi: 10.25984/2437657.
McMillan, Colin, Schoeneberger, Carrie, Supekar, Sarang, & Thierry, David. The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017. United States. https://dx.doi.org/10.25984/2437657
McMillan, Colin, Schoeneberger, Carrie, Supekar, Sarang, and Thierry, David. 2024. "The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017". United States. https://dx.doi.org/10.25984/2437657. https://data.openei.org/submissions/6158.
@div{oedi_6158, title = {The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017}, author = {McMillan, Colin, Schoeneberger, Carrie, Supekar, Sarang, and Thierry, David.}, abstractNote = {The Foundational Industry Energy Dataset (FIED) addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization by facility. Each facility is identified by a unique registryID, based on the U.S. Environmental Protection Agency (EPA) Facility Registry Service, and includes its coordinates and other geographic identifiers. Energy-using units are characterized by design capacity, as well as their estimated energy use, greenhouse gas emissions, and physical throughput using 2017 data from the EPA's National Emissions Inventory and Greenhouse Gas Reporting Program.
An overview of the derivation methods is provided in a separate technical report which will be linked after publication. The Python code used to compile the dataset is available in a GitHub repository. An updated 2020 version is under development. }, doi = {10.25984/2437657}, url = {https://data.openei.org/submissions/6158}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {07}}
https://dx.doi.org/10.25984/2437657
Details
Data from Jul 1, 2024
Last updated Sep 9, 2024
Submitted Aug 17, 2024
Organization
National Renewable Energy Laboratory (NREL)
Contact
Colin McMillan
202.488.2251
Authors
Research Areas
Keywords
energy, industry, greenhouse gas emissions, combustion units, boilers, furnaces, ovens, process heat, FIED, data, dataset, energy analysis, industrial energy, unit-level, facility, capacity, energy use, greenhouse gas, throughput, energy estimate, code, processed data, PythonDOE Project Details
Project Name Foundational Industrial Data Development - Industrial Data Platform
Project Number 28759