[shashwatsharma24]

Summary

This PR addresses issue#233 and adds geothermal regional capital cost multipliers to ReEDS.

Technical details

Currently inputs/financials/reg_cap_cost_diff_default.csv does not include values for geothermal techs. This PR adds values for GEO tech group (covers all geothermal techs) using data from Table 1-11 of EIA's capital costs report.

Implementation notes

EIA reported values for geothermal locational adjustments are at the state-city level; these are processed using the workflow in ReEDS_Input_Processing/capital_cost_multipliers repo. 32 counties had missing values, so I assigned them values from the nearest county in the same state (nearly all of these were in the eastern interconnect and had difference values of zero).

The list of missing counties and counties they were mapped to is available here: geo_missing_fips.csv

Values for WI states are plotted below.

Issues resolved

Issue#233

Validation, testing, and comparison report(s)

Total capacity stack remains nearly similar under both ATB Moderate and Advanced scenario cases; geothermal buildout decreases slightly (~2-3GW) by 2050 due to higher state-level capital costs, and PV/onshore wind buildout increases by 4-6GW. Discounted total system cost increases slightly by ~$3B (ATB Moderate) to ~$6.7B (ATB Advanced).

ATB Moderate:

ATB Advanced:

Looking at state-level differences in geothermal buildout, we can see that most of the ~2-3GW decrease is in installed capacity for California and Oregon.

ATB Moderate:

ATB Advanced:

Comparison reports:

1. ATB Moderate costs:
   results-ATB-Mod,ATB-Mod_ccmult.pptx

2. ATB Advanced costs:
   results-ATB-Adv,ATB-Adv_ccmult.pptx

Checklist for author

Details to double-check

• Charge code provided to reviewers
• Included comparison reports for appropriate test cases
• Documentation updated if necessary
• If input data added/modified:
  • Dollar year recorded and converted to 2004$ for GAMS
  • Timeseries are in Central Time
  • Units are specified
  • Preprocessing steps have been documented and committed to ReEDS_Input_Processing
  • New large data files handled with .h5 instead of .csv
  • If new parameters are added to d_objective.gms, they are included in objective_function_params.yaml for completeness checking
  • If spatially resolved inputs are modified, the following visualizations for each file are included in the PR description (time-averaged if the inputs are time-resolved):
    • Map of absolute values before
    • Map of absolute values after
    • Map of differences: (after - before) or (after / before)
  • If entries are added/removed/changed in the EIA-NEMS unit database:
    • Changes have been committed to ReEDS_Input_Processing
    • hourlize/resource.py was rerun to regenerate the existing/prescribed VRE capacity data
• Code formatting standardized
• Reusable functions used where possible instead of copy/pasted code

General information to guide review

• Zero impact on results of default case
• No large data file(s) added/modified
• No substantive impact on runtime for full-US reference case
• No substantive impact on folder size for full-US reference case
• No change to process flow (runreeds.py, reeds/core/solve/solve.py)
• No change to code organization
• No change to package requirements (environment.yml or Project.toml)

Did you use LLM tools (chatbot or copilot) in the preparation of this PR? If so, describe how

Tag points of contact here if you would like additional review of the relevant parts of the model