The answers to a host of pressing questions in energy policy, such as how best to help consumers use electricity more efficiently or where to site new electricity distribution infrastructure, depend crucially on a nuanced understanding of how consumers use electricity and how that demand differs from household to household. New opportunities to study differences in household electricity consumption have arisen in recent years thanks to the increasingly widespread installation of smart electricity meters that track household energy use at finely grained intervals, in some cases measuring energy consumption as frequently as every 15 minutes. Partnering with the Electric Reliability Council of Texas (ERCOT), Michael Webber, deputy director of the Energy Institute at the University of Texas, Austin, plans to explore household electricity usage patterns by integrating ERCOT’s 15?minute residential smart meter data with other relevant data sets, such as local tax records, demographic statistics, meteorological data, and locational marginal pricing information. Webber has identified a set of initial hypotheses to be tested through an examination of the integrated data set, including how energy use varies with income, time of day across different locations in Texas, and the introduction of demand response programs. Funds from this grant will help Webber and his team take in the over 45 terabytes of ERCOT smart meter data, suitably anonymize the data set, merge it with additional information sources, and disseminate it for use by other researchers.