2026 State RPS / CES /Hydrofrac Update#11
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Jun 23, 2026
| | `RPS & CES Targets and Demand_June 2026.xlsx` | Annual LBNL state RPS / CES dataset, provided by Galen Barbose. Source: https://emp.lbl.gov/projects/renewables-portfolio. The script reads four sheets from this file: `Statewide Sales`, `RPS & CES Demand (GWh)`, and `Non-RE Accounting`. Note: starting with the June 2026 release LBNL no longer publishes the `Non-RE Accounting` sheet in the public workbook. Galen sends it separately to NREL, and we paste it back into this file as the `Non-RE Accounting` tab so the workbook is self-contained. | | ||
| | `nrel-green-power-data-v2024.xlsx` | NLR Green Power Data (formerly NREL), used for the voluntary RPS row. Source: https://www.nlr.gov/analysis/voluntary-power-procurement. | | ||
| | `RPS_nonUS.csv` | Non-US RPS data provided by the ReEDS team (currently only Nova Scotia, `NS`). | | ||
| | `hierarchy.csv` | Region hierarchy from a recent ReEDS Reference run, used to map BAs to states for the hydrofrac calculation. | |
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Would you give a version number or date rather than "recent" to make things clearer down the road?
| | `nrel-green-power-data-v2024.xlsx` | NLR Green Power Data (formerly NREL), used for the voluntary RPS row. Source: https://www.nlr.gov/analysis/voluntary-power-procurement. | | ||
| | `RPS_nonUS.csv` | Non-US RPS data provided by the ReEDS team (currently only Nova Scotia, `NS`). | | ||
| | `hierarchy.csv` | Region hierarchy from a recent ReEDS Reference run, used to map BAs to states for the hydrofrac calculation. | | ||
| | `gen_ann.csv` | Annual generation by tech and BA from a recent ReEDS Reference run, used to compute hydro / non-RE shares for the hydrofrac calculation. | |
Co-authored-by: Wesley Cole <49044852+wesleyjcole@users.noreply.github.com>
…DS_Input_Processing into yc/26statepolicy
Co-authored-by: Wesley Cole <49044852+wesleyjcole@users.noreply.github.com>
Co-authored-by: Wesley Cole <49044852+wesleyjcole@users.noreply.github.com>
Co-authored-by: Wesley Cole <49044852+wesleyjcole@users.noreply.github.com>
…DS_Input_Processing into yc/26statepolicy
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Summary
Annual update of state RPS / CES / voluntary policy inputs in
state_policies/to the June 2026 LBNL release of "RPS & CES Targets and Demand". The three CSVs ReEDS consumes —rps_fraction.csv,ces_fraction.csv, andhydrofrac_policy.csv— are regenerated from the new data.Technical details
Two upstream data sources were refreshed:
RPS & CES Targets and Demand_June 2025.xlsx→RPS & CES Targets and Demand_June 2026.xlsx.The June 2026 release renamed several sheets and shifted header rows:
Statewide Load→Statewide SalesRPS & CES Demand Projections→RPS & CES Demand (GWh)Non-RE Accountingsheet from the public workbook. Galen sent it directly to Wesley, and it was pasted back into the workbook as a sheet namedNon-RE Accountingso the script's input is self-contained.nrel-green-power-data-v2023.xlsx→nrel-green-power-data-v2024.xlsx. The 2024 release added one more historical year (2024) and revised earlier years' market-wide estimates downward, which propagates into a uniformly lower voluntary trajectory inrps_fraction.csv.Implementation notes
Changes in
state_policies/data_processing.pyare all configuration at the top of the file — no algorithmic changes:filename→RPS & CES Targets and Demand_June 2026.xlsxfilename_voluntary→nrel-green-power-data-v2024.xlsx.<= 2023to<= 2024so the new 2024 data point is included inrps_seriesrather than projected; projection still extrapolates to 2050 using the minimum year-over-year growth in the historical series.base_yearbumped from 2023 to 2025. Years strictly beforebase_yearare passed through as raw values from the LBNL workbook, while years ≥base_yeargo through the change-point detection + linear interpolation + monotonic max pipeline.hydro_year(forgen_ann.csv) kept at 2023 to stay time-consistent with the vintage of Galen'sNon-RE Accountingnumerator data (2022–2023 reports).Additional changes
state_policies/README.md.old and new data comparison/old and new data comparison.ipynbwithold and new data comparison/generate_comparison_plots.py, which produces standardized PNGs from the old and new outputs.old and new data comparison/old ReEDS input/so the diffs/plots are reproducible by reviewers.Issues resolved
Closes #122.
Relevant sources or documentation
2025 vs 2026 comparisons
Additional details
python data_processing.pyto regenerate all six before/after PNGs inold and new data comparison/plots/. Spot-checked notable state-level changes against the LBNL summary slides (e.g., the CT RPS decline traces to the Class I / LFG / biomass eligibility change cited above). Voluntary trajectory verified; the uniform downward shift matches NLR's revised market-wide estimates in v2024.data_processing.pyfor the new LBNL sheet layouts, drafting the README's annual-update procedure, writinggenerate_comparison_plots.py, extracting text from the LBNL summary-slides PDF when investigating the CT decline, and locating the v2024 NLR file. All resulting code/text was reviewed and the regenerated CSVs were spot-checked against the source workbooks before committing.