The first data set estimates thermal energy use (i.e., fuels combusted for process heating, boilers, and combined heat and power/cogeneration) by end use, temperature, county, and facility employment size class for all U.S. manufacturing industries in 2014. The estimation methodology builds off of prior estimates of industrial energy use (https://dx.doi.org/10.7799/1481899, https://dx.doi.org/10.7799/1461488).
The second data set estimates hourly heat load (as a fraction of annual energy used for heat) using hourly observations of industrial boiler and combined heat and power/cogeneration heat load from EPA's Air Markets Program Data (https://ampd.epa.gov/ampd/), weekly operating hours in 2014 from Census Quarterly Survey of Plant Capacity Utilization (https://www.census.gov/programs-surveys/qpc/data.html), and annual production hours reported by assessments conducted by Industrial Assessment Centers (https://iac.university/).
ERRATA:
Representative heat load shapes were revised based on an updated estimation methodology. Hourly heat load relative to peak load is estimated by NAICS code, employment size class, month, day of week (Monday == 0) for a range of average weekly operating hours for boilers and process heating. The high and low operating hours values represent the 95% confidence interval of average weekly operating hours.
The second data set estimates hourly heat load (as a fraction of annual energy used for heat) using hourly observations of industrial boiler and combined heat and power/cogeneration heat load from EPA's Air Markets Program Data (https://ampd.epa.gov/ampd/), weekly operating hours in 2014 from Census Quarterly Survey of Plant Capacity Utilization (https://www.census.gov/programs-surveys/qpc/data.html), and annual production hours reported by assessments conducted by Industrial Assessment Centers (https://iac.university/).
ERRATA:
Representative heat load shapes were revised based on an updated estimation methodology. Hourly heat load relative to peak load is estimated by NAICS code, employment size class, month, day of week (Monday == 0) for a range of average weekly operating hours for boilers and process heating. The high and low operating hours values represent the 95% confidence interval of average weekly operating hours.
6 Data Resources
| Name | Size | Type | Resource Description | History |
|---|---|---|---|---|
| Manufacturing_Heat_Loadshapes.tar.gz | 9.18 MB | Archive | Parquet file partitioned by North American Industrial Classification (NAICS) code, compressed in a tar file. | |
| Manufacturing_Energy_by_Temperature_and_Enduse.tar.gz.gz | 7.45 MB | Archive | Parquet file partitioned by FIPS state code. | |
| Process_heat_load_shapes.gzip | 6.96 MB | Document | ERRATUM: Representative hourly heat load shapes for process heat use, relative to peak load, by NAICS code, employment size class, month, and day of week. | |
| Boiler_load_shapes.gzip | 6.77 MB | Document | ERRATUM: Representative hourly heat load shapes for boiler use, relative to peak load, by NAICS code, employment size class, month, and day of week | |
| Manufacturing_Energy_by_Temperature, corrected | 316.75 MB | Data | ERRATUM: An error was found in the underlying data collected from the EPA’s GHGRP for a single facility and has been corrected.” | |
| Metadata Manufacturing Energy by Temp | 2.31 KB | Document | ERRATUM: An error was found in the underlying data collected from the EPA’s GHGRP for a single facility and has been corrected.” |
Keywords
Submitted
• Sep •
27
2019
National Renewable Energy Laboratory
Cite This Dataset
McMillan, Colin. 2019. "Manufacturing Thermal Energy Use in 2014." NREL Data Catalog. Golden, CO: National Renewable Energy Laboratory. Last updated: December 12, 2023. DOI: 10.7799/1570008.
About This Dataset
118
10.7799/1570008
Public
12/12/2023
DOE Project
Solar for Industrial Process heat
Funding Organization
Department of Energy (DOE)
Sponsoring Organization
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
Research Areas
Energy Analysis
Solar Power
License
View License
Digital Object Identifier
10.7799/1570008