Balancing Authority Hourly Generation Of Installed Plant Capacities in CONUS

This dataset contains the hourly generation time series for each Balancing Authority representing the installed capacity in each month from 2007 through 2020. The time series is aggregated from plant-level generation of plants that exist in the Energy Information Administration (EIA) database as of 2020. The time series are simulated actual generation meaning that the installed capacities have been applied to the hourly capacity factor profiles in Bracken et al. 2023. These historical generation time series reflect the actual monthly installed capacity at each plant; the EIA 860 and EIA 860m databases were mined to identify months of first operation, retirement, and extended periods of maintenance or non-operation. These databases were also used to create time series of Balancing Authority (BA) level hourly generation to reflect the actual monthly installed capacity. The BA-level time series tracks the BA membership of each power plant in each month; the time series reflects the monthly inventory and hourly production in each BA.

For more information please refer to Campbell et al. 2023, Dynamically Downscaled Power Production for All EIA Wind and Solar Power Plants, in prep, and to the code repository at https://github.com/GODEEEP/godeeep-eia-power.

The dataset contains three types of files:

Monthly Plant-Level Inventory - The monthly plant-level inventory (all_years_860m.csv) contains the identification codes for each generator (including the plant_code_unique identifier to link with the solar and wind profiles in Bracken et al. 2023), the capacity in that month, the balancing authority that plant operated for in that month, the resource type (solar or wind), the month and year, and whether the nameplate capacity in that month needs to be scale to account for aggregation of very large wind power plants (i.e., more than 300 turbines).

BA-level Hourly Generation - The BA-level hourly generation files (solar_BA_generation.csv and wind_BA_generation.csv) contain hourly generation at the BA level for each BA in the 2020 EIA 860 database. The first column contains a time stamp and each column header is the name of the BA as it exists in the EIA 860 database (e.g., ISO New England is ISNE, CAISO is CISO). The time series spans 2007 through 2020. The time series begin in 2007, as this aligns with the first year of publication of the EIA 923 monthly plant-level generation dataset and with the first year of available BA-level self-reported generation.  The purpose of the temporal baseline alignment is for validation of the time series, discussed in Campbell et al. 2023. Validation metrics in this paper are provided at the BA-level.

Plant-level Hourly Generation - The plant-level hourly generation files (solar_plant_generation.csv and wind_plant_generation.csv) contain hourly generation at the generator level for each power plant that exists in the EIA 860 database in 2020. The files are organized with an hourly timestamp for each row and a unique generator id for each column. The generator id is a concatenation of the EIA Plant ID and the EIA Generator ID with an underscore separating the strings. The plant-level hourly generation time series are intended to be aggregated to the BA-level. These plant-level time series are provided to the user to allow for re-aggregation for bespoke regional analyses.

Known Issues

• The following wind power plants (identifier plant_code_unique) have a cf greater than 1 and were scaled to 0.885
  • ['2024', '2024_1', '2024_3', '2024_4', '7855', '7855_1', '7927', '7927_1', '7927_2', '7965', '7965_1', '7974', '7974_1', '52162', '52163', '54300', '54793', '54793_2', '55741', '55944', '55995_1', '56577', '57214', '57257', '57258', '57258_1', '57594', '57721', '57721_1', '58105', '58112', '58113', '58113_1', '59328', '59329', '59330', '59331', '61677', '61677_1', '61677_2', '62442', '64130']

Changelog

• v1.1.0 - Updates the basis for plant-level inventory from the EIA860 monthly reports (considered preliminary) to the EIA860 annual reports (considered complete and final).

This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL).

PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.