Add NG Multipliers as inputs

[SoLaraS2]

Summary

Technical details

• Added "get_degree_days" function to io.py
• Added "Natural Gas Price Diffs" block in fuelcostprep.py to create "natgas_price_diffs.h5"
• Added "get_natgas_price_diffs" function to hourly_writetimeseries.py to get a GAMS compatible csv with
  representative hourly NG price multipliers
• fuelcostprep.py now imports NumPy

Implementation notes

• "get_degree_days" has two options for how to calculate the degree days, default is:
  ----(Daily max + Daily min)/2 - 18.33C
• With houly_formula=True:
  ----daily sum (Hourly temp - 18.33C)

Relevant sources or documentation

• Monthly heating and cooling degree days from https://github.com/EIAgov/NEMS/blob/main/input/bld/kdegday.txt
• Population used for weighting remaining regions to get model region level from https://www.coopercenter.org/research/how-accurate-are-our-50-state-population-projections

Validation, testing, and comparison report(s)

• Imported the functions into a Jupyter Notebook and outputted check along the way. Also compared final outputs' formats to those of files known to have desired shape.

Checklist for author

Details to double-check

• Charge code provided to reviewers
• 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 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:
• Code formatting standardized
• Reusable functions used where possible instead of copy/pasted code (I tried my best to find preexisting relevant functions, but some may have slipped through)

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 (runbatch.py, d_solve_iterate.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

• LLMs used for timestamp compatibility between different outputs to ensure consistency in the final csv outputted
• LLMs used to run through the files and find relevant predefined functions I may have originally missed
• LLMs used to debug h5 file handling

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

[patrickbrown4]

1. How about gasreg instead of ngreg, since the techs are gas-cc/gas-ct and we don't use ng much throughout the code?
2. We'll need to add the new region level to https://reeds-model.github.io/ReEDS/model_documentation.html#figure-hierarchy (and describe the new method in the docs). If the regions are finalized, let me know and I can remake the figure.

[kodiobika]

gasreg SGTM and thanks for the heads up on the docs. The regions are finalized so if you could remake the figure that'd be great, thanks! Here's the charge code if needed: OOSP >-> 10291 - 05.18.01

[patrickbrown4]

Since this file is modified, can you run all the temporal tests from cases_test.csv and make sure they still work?

• Pacific_CC
• Pacific_weks
• Pacific_full_year
• Interday_storage
• Pacific_rep7

[kodiobika]

Thanks for your work on this! It's looking great so far -- mostly just some stylistic suggestions