Hourly Electricity Demand Profiles for Each County in the Contiguous United States
This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. (2) Weighted averages of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector
Annual county-level retail sales are estimated by aggregating utility-reported sales to the state level and allocating the results to counties according to each county's share of state population. Annual county-level direct use is calculated by aggregating power plant-reported direct use values. Annual county-level on-site consumption of DPV-generated electricity is estimated by aggregating utility-reported net metering data to determine the amount of DPV-generated electricity sold back to the grid for each state, subtracting those values from modeled state-level DPV generation estimates, and allocating the results to counties according to each county's share of statewide modeled DPV generation.
The open-source Python code used to develop this dataset is available at "Historical Load Data Repository" link below.
Citation Formats
TY - DATA
AB - This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. (2) Weighted averages of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector
Annual county-level retail sales are estimated by aggregating utility-reported sales to the state level and allocating the results to counties according to each county's share of state population. Annual county-level direct use is calculated by aggregating power plant-reported direct use values. Annual county-level on-site consumption of DPV-generated electricity is estimated by aggregating utility-reported net metering data to determine the amount of DPV-generated electricity sold back to the grid for each state, subtracting those values from modeled state-level DPV generation estimates, and allocating the results to counties according to each county's share of statewide modeled DPV generation.
The open-source Python code used to develop this dataset is available at "Historical Load Data Repository" link below.
AU - Obika, Kodi
A2 - Cole, Wesley
A3 - Rivers, Marie
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Laboratory of the Rockies
DO -
KW - energy
KW - power
KW - demand
KW - electricity
KW - electricity demand
KW - electricity consumption
KW - county
KW - consumption
KW - electricity profiles
KW - energy profiles
KW - planning
KW - grid planning
KW - modeling
KW - retail sales
KW - direct use
KW - distributed pv
KW - data
KW - DPV
KW - processed data
KW - CONUS
KW - United States
KW - code
KW - python
KW - weighted averages
LA - English
DA - 2025/11/05
PY - 2025
PB - National Renewable Energy Laboratory
T1 - Hourly Electricity Demand Profiles for Each County in the Contiguous United States
UR - https://data.openei.org/submissions/8562
ER -
Obika, Kodi, et al. Hourly Electricity Demand Profiles for Each County in the Contiguous United States. National Renewable Energy Laboratory, 5 November, 2025, Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/8562.
Obika, K., Cole, W., & Rivers, M. (2025). Hourly Electricity Demand Profiles for Each County in the Contiguous United States. [Data set]. Open Energy Data Initiative (OEDI). National Renewable Energy Laboratory. https://data.openei.org/submissions/8562
Obika, Kodi, Wesley Cole, and Marie Rivers. Hourly Electricity Demand Profiles for Each County in the Contiguous United States. National Renewable Energy Laboratory, November, 5, 2025. Distributed by Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/8562
@misc{OEDI_Dataset_8562,
title = {Hourly Electricity Demand Profiles for Each County in the Contiguous United States},
author = {Obika, Kodi and Cole, Wesley and Rivers, Marie},
abstractNote = {This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. (2) Weighted averages of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector
Annual county-level retail sales are estimated by aggregating utility-reported sales to the state level and allocating the results to counties according to each county's share of state population. Annual county-level direct use is calculated by aggregating power plant-reported direct use values. Annual county-level on-site consumption of DPV-generated electricity is estimated by aggregating utility-reported net metering data to determine the amount of DPV-generated electricity sold back to the grid for each state, subtracting those values from modeled state-level DPV generation estimates, and allocating the results to counties according to each county's share of statewide modeled DPV generation.
The open-source Python code used to develop this dataset is available at "Historical Load Data Repository" link below. },
url = {https://data.openei.org/submissions/8562},
year = {2025},
howpublished = {Open Energy Data Initiative (OEDI), National Renewable Energy Laboratory, https://data.openei.org/submissions/8562},
note = {Accessed: 2026-04-10}
}
Details
Data from Nov 5, 2025
Last updated Feb 9, 2026
Submitted Nov 5, 2025
Organization
National Renewable Energy Laboratory
Contact
Kodi Obika
Authors
Research Areas
Keywords
energy, power, demand, electricity, electricity demand, electricity consumption, county, consumption, electricity profiles, energy profiles, planning, grid planning, modeling, retail sales, direct use, distributed pv, data, DPV, processed data, CONUS, United States, code, python, weighted averagesDOE Project Details
Project Name Integrated Energy Futures
Project Number FY25 AOP 2.6.1.1
