Measurement and Verification Principles for Behavior-Based Efficiency Programs
Prepared for OPOWER
An increasing number of utilities across the United States have deployed or are planning to deploy behavior-based energy efficiency programs. Just as these programs use a relatively new approach to driving efficiency at utility scale, new measurement approaches are also needed. There has been recognition at the regulatory and advocacy level that an experimental design approach – that is, the use of statistically equivalent treatment and control groups – renders rigorous results at high confidence when properly executed. Because of this growing interest in behavioral efficiency solutions and a limited number of resources detailing their implementation, the need for a document that discusses best practices for designing and evaluating behaviorbased programs has become increasingly evident.
This guideline document aims to fill in this gap and lays out the main principles of scientific research that yields a statistically valid program design and program impact metrics. The measurement and verification principles in this document may apply to a broad group of residential energy efficiency behavioral programs that promote efficient usage behavior, customer engagement, and individual energy management. More specifically, these programs may have one or more of the following features:
- Normative comparison of a customer’s usage against comparable customers in the same geographical area;
- Targeted conservation and peak reduction tips based on an analysis of a customer’s past usage and individual profile;
- Encourage participation in other utility programs based on previous usage patterns and individual consumer profile.
It is important to note that the objective of this document is not to develop a comprehensive measurement and verification protocols document that addresses all possible program design and evaluation decisions one can make. Nevertheless, it is our intent to identify the best practices in program design and impact evaluation and provide guidance to utilities in their efforts to design statistically valid programs which will yield reliable impact metrics.
