Real-Time Energy Information and Consumer Behavior: A Meta-Analysis and Forecast

EPA Grant Number: FP917513
Title: Real-Time Energy Information and Consumer Behavior: A Meta-Analysis and Forecast
Investigators: Wang, Joy Huan
Institution: Georgia Institute of Technology
EPA Project Officer: Hahn, Intaek
Project Period: August 20, 2012 through August 19, 2015
Project Amount: $126,000
RFA: STAR Graduate Fellowships (2012) RFA Text |  Recipients Lists
Research Category: Academic Fellowships , Fellowship - Environmental Policy


What determines study-to-study variation in energy savings from projects and programs providing energy information feedback? What are the effect-sizes for program variables (such as duration, region, information type, information method and so forth) across multiple previous studies? How will nationally implemented smart metering in the residential sector affect U.S. energy demand? What are the associated costs and benefits?


First, a meta-analysis will be conducted regarding the current program results and implementation methods of various smart metering initiatives throughout the nation. Published literature on information effects on energy behavior also will be included. Next, the outputs of the metaanalysis will be used within the National Energy Modeling System (NEMS) to estimate the energy impacts of national smart metering.

Expected Results:

The meta-analysis of literature and program results will shed light on potential causes of study-to-study variation in information feedback programs and trials. Outputs from the meta-analysis, such as price elasticity, will be used in NEMS to estimate the impact of a national smart metering program. The potential energy saved will be estimated, as will other benefits and costs.

Potential to Further Environmental/Human Health Protection

The residential sector consumes almost one-quarter of total U.S. energy and emits almost one-third of national carbon emissions. Improved understanding of how smart meters affect energy behavior may help realize greater energy efficiency within households, saving significant energy while also avoiding carbon emissions.

Supplemental Keywords:

energy consumption, smart grid, smart meters

Progress and Final Reports:

  • 2013
  • 2014
  • Final