Abstract This research investigates the dynamics of capacity planning and dispatch in the US electric power sector under a range of technological, economic, and policy-related uncertainties. Using a two-stage stochastic programming approach, model results suggest that the two most critical risks in the near-term planning process of the uncertainties considered here are natural gas prices and the stringency of climate policy. Stochastic strategies indicate that some near-term hedging from lower-cost wind and nuclear may occur but robustly demonstrate that delaying investment and waiting for more information can be optimal to avoid stranding capital-intensive assets. Hedging strategies protect against downside losses while retaining the option value of deferring irreversible commitments until more information is available about potentially lucrative market opportunities. These results are explained in terms of the optionality of investments in the electric power sector, leading to more general insights about uncertainty, learning, and irreversibility. The stochastic solution is especially valuable if decision-makers do not sufficiently account for the potential of climate constraints in future decades or if fuel price projections are outdated.

keywords: Climate Policy; Electricity; Natural Gas; Planning Under Uncertainty; Risk Assessment; Stochastic Programming

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