Remove supply curve cost clipping

[bsergi]

Summary

Remove clipping of supply_curve_cost_per_mw values.

Technical details

For wind and solar, the supply curve costs represent site-specific cost adjustments to the ATB cost assumptions. Although most of these adjustments are positive (e.g., spur line, network reinforcement), a few, such as the cost of land, can be negative, indicating the cost of that site is lower than the assumption for that cost component included in the ATB.

The model currently sums all adjustments, aggregates to the class/bin/region, and then clips negative values to zero and large values above 1e7. This resulted in a few regions having negative cost adjustment clipped to zero, which overestimates the costs in those regions.

Here are the regions with changes to supply_curve_cost_per_mw after removing the clipping. A few regions with costs above 1e7 now also show increased costs.

*i	r	rscbin	main_value	new_value	change
upv_1	NY_NYC	bin5	$10,000,000	$10,249,958	$249,958
upv_2	NY_NYC	bin2	$10,000,000	$10,212,167	$212,167
upv_4	CA_LA	bin31	$10,000,000	$10,224,170	$224,170
upv_2	SC	bin1	$0	-$23,740	-$23,740
upv_2	SC	bin2	$0	-$13,342	-$13,342
upv_2	SC	bin3	$0	-$8,231	-$8,231
upv_2	SC	bin4	$0	-$1,143	-$1,143
upv_3	SC	bin1	$0	-$32,741	-$32,741
upv_3	SC	bin2	$0	-$18,660	-$18,660
upv_3	SC	bin3	$0	-$9,049	-$9,049
upv_3	SC	bin4	$0	-$2,032	-$2,032
upv_3	AR_MISO	bin1	$0	-$6,012	-$6,012
upv_3	LA	bin1	$0	-$5,503	-$5,503

Additional changes

Updated write_site_parameters.py to work with new reV columns and added checks for negative cost parameters for those that shouldn't be negative

Known incompatibilities

write_site_parameters.py breaks on a unrelated issue (seems the transmission_distance_cost_500kVdc_ba.csv file has moved)

Relevant sources or documentation

Validation, testing, and comparison report(s)

Compare report for US defaults: results-main,no_clip.pptx

Removing the clipping results in some additional solar/storage in early years but the amount is small:

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

I used copilot to pull out and summarize the supply curve bins that had costs changed after removing the clipping.

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

[jvcarag]

After our discussion earlier today, I've reviewed this PR's changes to writesupplycurves.py and determined that they would not affect the new clipping procedures for PSH that would be introduced by PR #184, as PSH supply curves would use new clipping code separate from the lines of code this PR aims to remove.

Since I am still waiting on some final code review, I can wait to merge PR #184 until this PR is merged to avoid code conflict.

[patrickbrown4]

Thanks!

[patrickbrown4]

For production I would just throw the error (otherwise on the hpc I think it will hang)

Suggested change

	try:
	neg_vals = sum(df[cc] < 0)
	except:
	breakpoint()
	neg_vals = sum(df[cc] < 0)

[bsergi]

Thanks for catching--that was the plan but I was debugging a column name that broke here and forget to revert.