Abstract
Electricity system operations are often affected by energy policies, but spatial differences in policy impacts are difficult to model. We develop a method for estimating zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods (not necessarily engineering) and with publicly-available data. Our nonlinear statistical model uses fuel prices and zonal electric loads to determine piecewise supply curves, each segment of which represents the influence of a particular fuel type on the zonal electricity price. Our problem thus requires the simultaneous estimation of the slope of each supply-curve segment, as well as the thresholds defining the endpoints of each segment. We illustrate our methodology by estimating zonal supply curves for the utility zones in the PJM electricity grid. We use our supply curves to estimate regional impacts of a policy initiative in the state of Pennsylvania that requires utilities to reduce annual and peak electric load. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. We also find that the policy reduces electricity prices in most other regions, although the impacts are not uniform across regions.
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