LBNL Report Number
Demand response is increasingly recognized as an essential ingredient to well functioning electricity markets. This growing consensus was formalized in the Energy Policy Act of 2005 (EPACT), which established demand response as an official policy of the U.S. government, and directed states (and their electric utilities) to consider implementing demand response, with a particular focus on "price-based" mechanisms. The resulting deliberations, along with a variety of state and regional demand response initiatives, are raising important policy questions: for example, How much demand response is enough? How much is available? From what sources? At what cost? The purpose of this scoping study is to examine analytical techniques and data sources to support demand response market assessments that can, in turn, answer the second and third of these questions. We focus on demand response for large (> 350 kW), commercial and industrial (C&I) customers, although many of the concepts could equally be applied to similar programs and tariffs for small commercial and residential customers. A number of utilities and regional groups have performed demand response market potential studies in recent years. Such studies have been conducted primarily to develop the demand-side section of utility resource plans, or to assist with planning or screening of potential demand response programs. Going forward, in addition to these motivations, we anticipate that market assessments may be useful to utilities and state policymakers in their response to EPACT, as a means to help determine the feasibility of various demand response options in their service territories. Additionally, some states and regions have begun to set demand response goals; market assessment studies could serve as a foundation to ensure that such goals are achievable, and help identify market segments and strategies to meet them. In this scoping study, we review analytical methods and data that can support market assessments (e.g., for dynamic pricing tariffs) or market potential studies (e.g., for programmatic demand response) that can support these functions. We present a conceptual framework for estimating market potential for large customer demand response, compile participation rates and elasticity values from six large customer dynamic pricing and demand response programs and apply them to estimate demand response market potential in an illustrative utility service territory. Finally, we present a research agenda that identifies additional information and improved methods that would support more reliable demand response market assessments.