Turning interval meter data into analytics to improve program performance for demand-side management.
Demand Response: Breaking Out of the Bubble
Using demand response to mitigate rate shocks.
By protecting customers from price spikes during a few hours in the year, existing rate-design regulations also are preventing them from lowering their average rates throughout the entire year. That is the paradox of utility regulation.
Responding to the directives of the Energy Policy Act of 2005 (EPACT), two recent reports by the U.S. Department of Energy and the Federal Energy Regulatory Commission (FERC) make a strong case for dynamic pricing of electricity. 1 These reports pick up on a theme that was first articulated by the California Public Utilities Commission (CPUC) in 2002. As it began its deliberations on dynamic pricing, advanced metering, and demand response (DR), the CPUC instituted Rulemaking (R.) 02-06-001 “to provide the forum to formulate comprehensive policies that will develop demand flexibility as a resource to enhance electric system reliability, reduce power purchase and individual consumer costs, and protect the environment.” 2
Five years after the nation’s biggest power crisis, the percentage of Americans on advanced metering and dynamic pricing in the United States continues to be in the single digits. Prices for basic electricity service— i.e., standard rates in regulated markets and default rates in restructured markets—do not vary by time of use, let alone vary dynamically with changing market conditions. In the minds of many policy-makers, dynamic pricing has become associated with rate shocks, rate volatility, unpredictability, and loss of control over energy costs. This is ironic, since it is designed to overcome precisely these very problems. How has this occurred and what can be done to change it? These questions are taken up here.
The Game Plan
Because electricity cannot be stored easily in large quantities, and because the cost of providing power varies across the day and season, wholesale electricity prices exhibit significant temporal variability. For markets to function efficiently, this temporal variation needs to be passed through to retail customers. Otherwise, customers will over-consume electricity during peak hours, necessitating the installation of expensive peaking capacity.
There are three generic ways in which such time variation could be provided to customers (see Table 1).
Within each category, several varieties exist. Essentially, there is almost no limit to the choices that can be given to customers so they can make a well-informed tradeoff between average electricity costs and price volatility.
There is strong empirical evidence that during critical peak hours, when the power system is stressed by a shortage of supply relative to demand, reducing customer loads by a few percentage points can lower the wholesale cost of electricity significantly. As shown in California’s recent statewide pricing pilot, customers do not have to make drastic adjustments in order to drop their load during these critical