A step-by-step approach to intelligent rate design.
Ahmad Faruqui and Ryan Hledik are economists with The Brattle Group in San Francisco. They acknowledge funding from the Demand Response Research Center (DRRC) in Berkeley, Calif. However, the views in this paper are their own and not necessarily those of Brattle or the DRRC.
With the advent of the smart grid, state commissions throughout North America are showing increasing interest in dynamic pricing as a means of enhancing economic efficiency by reducing the need for expensive peaking capacity. But several barriers stand in the way of its rapid deployment.
As noted by MIT’s Paul Joskow in a recent discussion of the economics of climate change, “On the demand side there are relatively low-cost ways to reduce electricity consumption by increasing energy efficiency in building, lighting, heating, ventilating, air conditioning and other equipment. That’s why getting the retail price signals right is important and why muting them with regulation based on traditional cost- of-service models is inconsistent with promoting adoption of economical energy efficiency opportunities.”1
While the rate-design process (in conjunction with the revenue-requirements process) in principle results in utility recovery of all prudent costs, it doesn’t provide sufficient incentives to utilities to pursue energy efficiency and demand-response programs at a level commensurate with state and federal goals. A review of default rate designs across the continent reveals that prices paid by customers do not reflect the scarcity of capacity to produce energy at various times of day.