A Robust Alternative to Critical Peak Pricing for Electricity Using Distributed Energy Storage

This article addresses the classic problem of pricing electricity on peak-load days to lower the system peak and meet the conditions for long-run efficiency. It is assumed implicitly that the wholesale market is monitored to ensure that the price equals the short-run marginal cost of supply. Distributed storage can be used to shift load and/or provide ramping services, and when the supply is inelastic, the storage is used mainly to shift load and reduce the system peak. However, our analysis focuses on the case when supply is elastic on a peak-load day, and consequently, the storage is used mainly for ramping and is not long-run efficient. To overcome this problem, Critical Peak Pricing (CPP) is evaluated as the conventional way to provide the incentive needed for storage to shift load away from the peak. Our main contribution is to demonstrate that the uncertainty of wind generation and price undermines the performance of CPP, and we propose a better, robust storage strategy. Daily simulations of wind generation on the peak-load day are used to determine the wholesale electricity price using a linear supply curve of net-load plus a stochastic residual. We argue that meeting the established reliability standard for "system adequacy" of only failing one-day-in-ten-years corresponds to covering the worst case, with the lowest realized wind generation, in 1000 simulations. Using this standard, the robust strategy maximizes the attainable peak reduction, and this is nearly three times larger than the corresponding reduction using the CPP strategy. The CPP strategy stabilizes the savings earned in the wholesale market, but all ramping requirements must be provided by the system operator. In contrast, the robust strategy provides the ramping needed to stabilize peak net-load, but the savings in the wholesale market are lower and much riskier. Since the owners of storage are likely to prefer the CPP strategy, we conclude that regulators should focus on ways to reduce the ramping requirements for adequacy by, for example, using the more accurate forecasts of wind generation associated with a receding-horizon optimization.