Fast growing distributed resources create technical challenges for utilities. Advanced DMS technology promises to help keep local grids balanced.
Reconsidering Resource Adequacy, Part 2
Capacity planning for the smart grid.
efficiency improvements) in principle should be included in peak load forecasts to avoid double-counting reductions.
Longer term, the objective should be to de-emphasize or phase out the practice of treating demand reductions as capacity resources, which is unique to the electricity industry; ultimately, consumers should pay based on what and when they consume, as they do in other industries (price-responsive demand has been called “third-generation” demand response, with direct load control and RTO demand-response programs constituting the first and second generations, respectively 6). However, this will require further development of wholesale and retail pricing approaches; in the meanwhile, treating demand response as a resource provides a strong incentive for further development of this valuable capability.
Transition to the Smart Grid
The next several years likely will be a transitional period during which price-responsive demand will be developing at a pace that will vary considerably from region to region, and will be difficult to predict in advance. During this transitional period, resource adequacy approaches should be adapted to fully anticipate, accommodate, encourage, and reward peak-reducing technologies and practices in a manner that does not jeopardize reliability. There’s a significant risk that if traditional, highly conservative resource adequacy policies are continued, they will lead to over-procurement and excess capacity during this period, which could discourage and delay the development of the smart grid and price-responsive demand.
Peak load forecasts for capacity planning should fully anticipate the potential for peak load reductions, including the reductions induced by the potential for prices to rise to very high levels ( i.e., approaching the value of lost load, or VOLL) when operating reserves fall below target levels. A portion of the reductions may be treated as resources and recognized in supply plans, with the remainder recognized in peak load forecasts. The challenge during the transitional period is to accurately forecast, without double-counting, all reasonably anticipated future peak load reductions and energy efficiency improvements. Unfortunately, future load reductions are highly uncertain, even looking out just a few years. And forecasting approaches that primarily extrapolate past trends to predict future peak load levels generally won’t accurately project new and accelerating trends, such as efficiency improvements and increasingly price-responsive demand, except with a substantial lag.
While utilities and RTOs will play a large role in implementing the smart grid, they understandably will be cautious about anticipating, in their long-term peak load forecasts and capacity planning, significant impacts of unproven targets and programs regarding efficiency, demand response and price-responsive demand. RTOs especially will have little control over these developments and won’t be able to ensure that programs intended to realize peak load reductions will be implemented in a timely and effective manner. Therefore, there is a risk that peak load forecasting and capacity planning will continue to be conservative and to reflect a believe-it-when-I-see-it approach to much of the potential for peak load reductions.
Because the pace with which the various smart-grid elements will be put in place will vary from area to area and is largely under the control of states, utilities, and load-serving entities (LSEs), these entities should