Smart electric meters comprise one key technology element in an overall strategy to modernize the nation's energy infrastructure. Smart meters capture data on household energy usage at frequent intervals and transmit those data to utility companies, who use the data to automate meter reading and billing, detect and respond to outages, and manage grid operations. Data collected over time can be used to forecast demand, understand customer behavior and develop new service and pricing plans. In the long run, these data can drive forecasting and control models that allow utilities to respond rapidly to fluctuations in power demand with compensatory load control strategies. This capability can reduce the magnitude of peak demand, thereby reducing both infrastructure costs and the consumption of fossil fuels that power peak generation facilities. Despite these advantages, smart meter data also appear to create powerful customer privacy concerns that may inhibit the adoption of smart meter technology by utilities. To address privacy concerns pertaining to the smart meter data, this project proposes three studies: Study 1 uses public data on electricity usage to develop a set of privacy scenarios that will be tested in focus groups to explore consumer privacy concerns. Study 2 involves a quasi-experiment to assess key dimensions of the scenarios and help identify which scenario has the highest level of acceptability to consumers. Study 3 involves one-on-one discussions with utility company representatives to develop a toolbox of communication methods and content that balance consumers' privacy concerns with the goals and constraints of utilities. The current theoretical model of privacy and technology, based on an information boundary framework, posits that consumers' willingness to share private information is rooted in the nature of the relationship with the party with whom the information is shared. Although a number of researchers have applied this information boundary framework to intra-organizational situations, the framework has not been tested in the context of smart meter data privacy. In the proposed sequence of three studies, this project gathers data from informants with the intention of understanding whether the information boundary framework is applicable to examining the relationships between consumers and regulated monopolies. The proposed project provides insights into public attitudes and concerns, as well as industry practices and policies regarding privacy of smart meter data. Through direct interaction with utility companies, as well as dissemination at industry conferences, in trade journals and through the media, the researchers will share their findings with practitioners, regulators and others who can create solutions that give customers confidence about the protection of their data.
EAGER: Data Privacy for Smart Meter Data: A Scenario-Based Study