Status: Published
**Citation:**Goteti, Naga Srujana, Eric Hittinger, and Eric Williams. 2025. "Stochastic Capacity Expansion Model Accounting for Uncertainties in Fuel Prices, Renewable Generation, and Demand" Energies 18, no. 5: 1283. https://doi.org/10.3390/en18051283.
The paper "Stochastic Capacity Expansion Model Accounting for Uncertainties in Fuel Prices, Renewable Generation, and Demand" by Goteti, Hittinger, and Williams presents a stochastic approach to electricity grid capacity expansion, integrating uncertainties in fuel prices, renewable generation, and demand directly into the optimization process. This method contrasts with traditional deterministic models that handle uncertainty through ex-post analysis.
The authors explore two cost-based risk objectives:
- Risk-Neutral: Minimizes the expected total system cost.
- Risk-Averse: Minimizes the costs in the most expensive 5% of the cost distribution.
Applying this model to the U.S. Midwest grid, the study accounts for uncertainties in electricity demand, natural gas prices, and wind generation patterns. The findings indicate that while uncertain natural gas prices lead to increased wind energy adoption, accounting for wind variability results in reduced wind adoption. The risk-averse objective yields a more diverse generation portfolio. This study underscores the importance of incorporating uncertainties directly into capacity expansion models to develop robust and cost-effective strategies for future electricity grids.
Link to Journal Publication: Stochastic Capacity Expansion Model Accounting for Uncertainties in Fuel Prices, Renewable Generation, and Demand