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Duke Energy Carbon-Free Resource Integration Study

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Supporting data for the Phase 2 of the Duke Energy Carbon-Free Resource Integration Study, which studied pathways to meeting emissions reduction targets in the Carolinas. The data sets include results from two modeling components of the study: capacity expansion modeling using ReEDS and operational modeling using PLEXOS. Details on the data features included from each component are outlined below. For information on the methods, scenarios, or context for these data, as well as further explanation of NREL's collaboration with Duke Energy, can be found at https://www.nrel.gov/grid/carbon-free-integration-study.html. Capacity expansion results: Installed capacity (GW, annual by fuel type for the Carolinas) Firm capacity estimates (GW, seasonal by fuel type for the Carolinas) Undiscounted system cost (billion 2020$ USD, annual by cost category) CO2 emissions (million metric tons, annual for North Carolina / Total Carolinas) Annual generation (TWh, annual by fuel type for the Carolinas) Transmission investment (GW, total capacity for 2030 and 2050 by transmission corridor) Capacity expansion results are provided for all ReEDS cases (including sensitivities) and are supplied as csv files. Operational modeling results: Generator information (summarized by generator category): Installed capacity (MW, annual) Available capacity (MW, hourly) Generation (MW, hourly) Curtailment (MW, hourly) Charging (MW, hourly) Operating reserve provision (MW-h, hourly) CO2 emissions (metric ton, hourly) Fuel offtakes (million BTU, hourly) Cost information (summarized by cost type and generator type): Fuel cost (2020$ USD, hourly) Start & shutdown cost (2020$ USD, hourly) VO&M cost (2020$ USD, hourly) Region information (summarized by region): Load (MW, hourly) Net interchange (MW, hourly) Operational modeling results are provided in two sets: the nodal model results, which focus on analysis of the 2030 timeframe; and the zonal model results, which focus on analysis of the 2050 timeframe. Results are provided in h5 file format.

Citation Formats

TY - DATA AB - Supporting data for the Phase 2 of the Duke Energy Carbon-Free Resource Integration Study, which studied pathways to meeting emissions reduction targets in the Carolinas. The data sets include results from two modeling components of the study: capacity expansion modeling using ReEDS and operational modeling using PLEXOS. Details on the data features included from each component are outlined below. For information on the methods, scenarios, or context for these data, as well as further explanation of NREL's collaboration with Duke Energy, can be found at https://www.nrel.gov/grid/carbon-free-integration-study.html. Capacity expansion results: Installed capacity (GW, annual by fuel type for the Carolinas) Firm capacity estimates (GW, seasonal by fuel type for the Carolinas) Undiscounted system cost (billion 2020$ USD, annual by cost category) CO2 emissions (million metric tons, annual for North Carolina / Total Carolinas) Annual generation (TWh, annual by fuel type for the Carolinas) Transmission investment (GW, total capacity for 2030 and 2050 by transmission corridor) Capacity expansion results are provided for all ReEDS cases (including sensitivities) and are supplied as csv files. Operational modeling results: Generator information (summarized by generator category): Installed capacity (MW, annual) Available capacity (MW, hourly) Generation (MW, hourly) Curtailment (MW, hourly) Charging (MW, hourly) Operating reserve provision (MW-h, hourly) CO2 emissions (metric ton, hourly) Fuel offtakes (million BTU, hourly) Cost information (summarized by cost type and generator type): Fuel cost (2020$ USD, hourly) Start & shutdown cost (2020$ USD, hourly) VO&M cost (2020$ USD, hourly) Region information (summarized by region): Load (MW, hourly) Net interchange (MW, hourly) Operational modeling results are provided in two sets: the nodal model results, which focus on analysis of the 2030 timeframe; and the zonal model results, which focus on analysis of the 2050 timeframe. Results are provided in h5 file format. AU - Sergi A2 - Brinkman A3 - Emmanuel A4 - Guerra Fernandez A5 - Steinberg A6 - Hodge DB - Open Energy Data Initiative (OEDI) DP - Open EI | National Renewable Energy Laboratory DO - KW - Duke Energy KW - North Carolina KW - Southeast KW - carbon-free KW - capacity expansion KW - ReEDS KW - production cost KW - PLEXOS LA - English DA - 2022/08/10 PY - 2022 PB - National Renewable Energy Laboratory T1 - Duke Energy Carbon-Free Resource Integration Study UR - https://data.openei.org/submissions/8245 ER -
Export Citation to RIS
Sergi, et al. Duke Energy Carbon-Free Resource Integration Study. National Renewable Energy Laboratory, 10 August, 2022, NREL. https://data.nrel.gov/submissions/193.
Sergi, Brinkman, Emmanuel, Guerra Fernandez, Steinberg, & Hodge. (2022). Duke Energy Carbon-Free Resource Integration Study. [Data set]. NREL. National Renewable Energy Laboratory. https://data.nrel.gov/submissions/193
Sergi, Brinkman, Emmanuel, Guerra Fernandez, Steinberg, and Hodge. Duke Energy Carbon-Free Resource Integration Study. National Renewable Energy Laboratory, August, 10, 2022. Distributed by NREL. https://data.nrel.gov/submissions/193
@misc{OEDI_Dataset_8245, title = {Duke Energy Carbon-Free Resource Integration Study}, author = {Sergi and Brinkman and Emmanuel and Guerra Fernandez and Steinberg and Hodge}, abstractNote = {Supporting data for the Phase 2 of the Duke Energy Carbon-Free Resource Integration Study, which studied pathways to meeting emissions reduction targets in the Carolinas. The data sets include results from two modeling components of the study: capacity expansion modeling using ReEDS and operational modeling using PLEXOS. Details on the data features included from each component are outlined below. For information on the methods, scenarios, or context for these data, as well as further explanation of NREL's collaboration with Duke Energy, can be found at https://www.nrel.gov/grid/carbon-free-integration-study.html. Capacity expansion results: Installed capacity (GW, annual by fuel type for the Carolinas) Firm capacity estimates (GW, seasonal by fuel type for the Carolinas) Undiscounted system cost (billion 2020$ USD, annual by cost category) CO2 emissions (million metric tons, annual for North Carolina / Total Carolinas) Annual generation (TWh, annual by fuel type for the Carolinas) Transmission investment (GW, total capacity for 2030 and 2050 by transmission corridor) Capacity expansion results are provided for all ReEDS cases (including sensitivities) and are supplied as csv files. Operational modeling results: Generator information (summarized by generator category): Installed capacity (MW, annual) Available capacity (MW, hourly) Generation (MW, hourly) Curtailment (MW, hourly) Charging (MW, hourly) Operating reserve provision (MW-h, hourly) CO2 emissions (metric ton, hourly) Fuel offtakes (million BTU, hourly) Cost information (summarized by cost type and generator type): Fuel cost (2020$ USD, hourly) Start & shutdown cost (2020$ USD, hourly) VO&M cost (2020$ USD, hourly) Region information (summarized by region): Load (MW, hourly) Net interchange (MW, hourly) Operational modeling results are provided in two sets: the nodal model results, which focus on analysis of the 2030 timeframe; and the zonal model results, which focus on analysis of the 2050 timeframe. Results are provided in h5 file format.}, url = {https://data.nrel.gov/submissions/193}, year = {2022}, howpublished = {NREL, National Renewable Energy Laboratory, https://data.nrel.gov/submissions/193}, note = {Accessed: 2025-04-25} }

Details

Data from Aug 10, 2022

Last updated Jan 21, 2025

Submitted Aug 10, 2022

Organization

National Renewable Energy Laboratory

Contact

Brian Sergi

Authors

Sergi

National Renewable Energy Laboratory

Brinkman

National Renewable Energy Laboratory

Emmanuel

National Renewable Energy Laboratory

Guerra Fernandez

National Renewable Energy Laboratory

Steinberg

National Renewable Energy Laboratory

Hodge

National Renewable Energy Laboratory

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