Update natural gas regression parameters (betas and alphas) with AEO 2025 (old -> 2025)#50
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Yunzhi-Chen wants to merge 2 commits intomainfrom
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Update natural gas regression parameters (betas and alphas) with AEO 2025 (old -> 2025)#50Yunzhi-Chen wants to merge 2 commits intomainfrom
Yunzhi-Chen wants to merge 2 commits intomainfrom
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Yunzhi-Chen
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wesleyjcole
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Apr 24, 2026
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| [^ref32]: Supply curves are nonlinear in practice, but a linear regression approximation has been observed to be satisfactory under most conditions. | ||
| The elasticity coefficients are derived from all scenarios of AEO2018, but the price-demand setpoints are taken from any one single scenario of the AEO. | ||
| The elasticity coefficients are derived from AEO2025 scenarios via a demeaned fixed-effects OLS regression, and the price-demand setpoints are taken from any one single scenario of the AEO. |
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| The elasticity coefficients are derived from AEO2025 scenarios via a demeaned fixed-effects OLS regression, and the price-demand setpoints are taken from any one single scenario of the AEO. | |
| The elasticity coefficients are derived from AEO2025 scenarios via a demeaned fixed-effects ordinancy least squares regression, and the price-demand setpoints are taken from any one single scenario of the AEO. |
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| The $\beta$ terms are regressed from AEO2014 scenarios, with 9 of the 31 AEO2014 scenarios removed as outliers {cite}`eiaAnnualEnergyOutlook2014`. | ||
| These outlier scenarios typically include cases of very low or very high natural gas resource availability, which are useful for estimating NG price as a function of supply but not for estimating NG price as a function of demand within a given supply scenario. | ||
| The $\beta$ terms are regressed from AEO scenarios using a demeaned fixed-effects OLS approach in two stages. |
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| The $\beta$ terms are regressed from AEO scenarios using a demeaned fixed-effects OLS approach in two stages. | |
| The $\beta$ terms are regressed from AEO scenarios using a demeaned fixed-effects ordinary least squares approach in two stages. |
| 2048,-1.132644074,-0.732276816,-0.79209341,0.053735263,-0.23766312,0.67057009,0.107552391,0.053313444,-0.269915327 | ||
| 2049,-1.224774229,-0.776804013,-0.838981981,-0.021675882,-0.280933762,0.630302407,0.042285076,0.033514511,-0.317431645 | ||
| 2050,-1.230454535,-0.815888879,-0.868686511,-0.076279579,-0.317240188,0.631157758,0.008900914,0.023620292,-0.331612009 | ||
| t,New_England,Mid_Atlantic,East_North_Central,West_North_Central,South_Atlantic,East_South_Central,West_South_Central,Mountain,Pacific |
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Would you mind putting these back in alphabetical order? That occasionally makes life easier for other tasks. This applies to all of these files.
| @@ -1,10 +1,10 @@ | |||
| *cendiv,value | |||
| East_North_Central,0.262956 | |||
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Alphabetical ordering will also help in places like this--you'll be able to see the census division changes.
| @@ -1,42 +1,42 @@ | |||
| year,East_North_Central,East_South_Central,Mid_Atlantic,Mountain,New_England,Pacific,South_Atlantic,West_North_Central,West_South_Central | |||
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I'm not expecting these files to changes as the ng prices didn't change. I think switch back to the original ordering will show that.
| @@ -1,42 +1,42 @@ | |||
| year,East_North_Central,East_South_Central,Mid_Atlantic,Mountain,New_England,Pacific,South_Atlantic,West_North_Central,West_South_Central | |||
| 2010,0.326,0.567,0.89,0.641,0.42,0.989,1.544,0.124,2.049 | |||
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Samt thing with the demand files--I'm not expecting them to change as these should be independent of the regression outputs.
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We typically only keep the current AEO and last AEO in ReEDS, so you can delete the AEO2023 inputs for the natural gas files you are updating. |
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Summary
Update the natural gas price regression parameters (regional betas, national beta, and scenario-specific alphas) from old AEO 2018-era coefficients to newly regressed AEO 2025 values. The regression pipeline and detailed methodology are documented in ReEDS_Input_Processing PR #2. This is a data-only PR — 14 CSV files updated under
inputs/fuelprices/plus one scalar ininputs/scalars.csv.Files changed:
cd_beta0.csv— regional betas (re-estimated from AEO 2025)scalars.csv—nat_beta_nonenergyupdated (0.1352 → 0.080017)alpha_AEO_2025_{reference,HOG,LOG}.csv— alphas recomputed for three scenariosng_AEO_2025_{reference,HOG,LOG}.csv— NG pricesng_demand_AEO_2025_{reference,HOG,LOG}.csv— electric-sector NG demandng_tot_demand_AEO_2025_{reference,HOG,LOG}.csv— total NG demandTechnical details
See ReEDS_Input_Processing PR #2 for full regression methodology, pipeline code, and diagnostic plots.
Issues resolved
Resolves #30 — Update gas price elasticities.
Relevant sources or documentation
Validation, testing, and comparison report(s)
Three ReEDS runs were performed with old vs. new parameters to compare capacity expansion results:
Reference case
High NG demand case: High electricity demand growth + conservative ATB projections for renewable energy technologies (intended to create a scenario where natural gas demand is much higher to understand the impact of the elasticities).
Low NG demand case: Enforces net-zero emissions by 2035 (intended to create a scenario where natural gas demand is very low to understand the impact of the elasticities).
Capacity expansion results comparison
NG price elasticity update -2025.pptx
Checklist for author
Details to double-check
General information to guide review
Did you use LLM tools (chatbot or copilot) in the preparation of this PR? If so, describe how
Yes — used GitHub Copilot to assist with drafting the PR description.
Tag points of contact here if you would like additional review of the relevant parts of the model