Smart Grid Project

Smart Grid Adoption

Adoption of smart grid technologies by electrical utilities:

Factors influencing organizational innovation in a regulated environment

Principal investigator: Jason Dedrick, Syracuse University

Co-principal investigators: Jeffrey Stanton and Murali Venkatesh, Syracuse University

Electric utilities are challenged to modernize a deteriorating infrastructure, improve grid resilience, reduce outages, incorporate renewable energy sources, and give customers more control over their energy use. Smart grid technologies can help utilities respond to these challenges by incorporating ICTs across the grid. Yet smart grid adoption and integration presents major organizational and technical challenges to utilities. As a result, smart grid adoption varies widely across U.S. utility companies, and the much of the potential benefit remains untapped.

This research addresses the following questions: (1) What internal and external factors determine the motivation and willingness of utility companies to develop and deploy smart grid innovations? (2) How do organizations in a regulated environment respond to innovation opportunities and challenges? (3) What policy changes would be required to overcome obstacles to the adoption and integration of smart grid technologies?

This project is creating new knowledge about organizational adoption of potentially disruptive innovations in the context of a regulated market. The results of the project will provide useful practical insights for managers, regulators and policymakers involved in smart grid adoption and implementation.

Acknowledgement: This project is supported by the National Science Foundation under Grant No. SES-1231192.

Data Privacy

Data Privacy for Smart Meters and Smart Devices: A Scenario-Based Study

Principal investigator: Jason Dedrick, Co-PI: Jeffrey Stanton, Syracuse University Contact:

Smart meters capture data on household energy usage which can be used by utilities to automate meter reading and billing, detect and respond to outages, manage grid operations, and better match supply to demand. In addition a new generation of smart home products is being introduced to the market, such as smart thermostats, lighting systems, and devices that can help customers manage energy use. These technologies offer potential value to consumers, but may also raise privacy concerns for some consumers. They may worry about what data is being collected, who has access to the data, and how it might be used.

This project investigates the privacy attitudes, concerns, and practices of consumers, device manufacturers, policymakers and regulators. The goal is to provide fact-based analysis that will help develop solutions that give customers confidence about the protection of their privacy and allow data to be used in ways that benefit consumers and firms.

The project uses focus groups, interviews and a survey to addresses the following research questions:

1. How do consumers perceive privacy risks when presented with information about the nature of data collection and use by utilities and others?

2. How do utility companies and other firms currently protect data privacy and how well do their policies and practices correspond to the privacy concerns of consumers?

3. Given information about consumers’ concerns, what privacy policies and practices will utility companies, other firms and regulators recommend as appropriate, and how will consumer concerns be addressed?

The project will advance knowledge in the field of privacy in information systems; and will provide insights to utilities, policy makers, regulators, privacy advocates, consumers and other stakeholders.

Acknowledgement: This research is supported by a grant from the U.S. National Science Foundation (SES-1447589), and a grant from the Alfred P. Sloan Foundation.

Big Data

Big Data analysis of household electricity use

Large amounts of data on household electricity use are becoming available with the widespread deployment of smart meters and adoption of smart electric devices by consumers. These data can be used by consumers to conserve energy or shift usage away from peak load times when it is most expensive. It also can be used by utilities to improve planning for capacity, peak use, and grid optimization.

This project uses data from the Pecan Street Institute in Austin, TX on electricity use by about 1200 households in several parts of Texas, as well as Colorado and California. The data is captured at one-minute and fifteen-minute intervals, and covers specific appliances (e.g., air conditioners, refrigerators, stoves) as well as electric vehicles (EVs) and rooftop solar systems where they are in use. The project team is cleaning, analyzing and visualizing the data using big data tools to look at issues such as:

1. Hourly, daily, and seasonal patterns of electricity use, and how those are related to weather and other factors.

2. The output of rooftop solar and how it is related to electricity usage.

3. How electricity costs would be affected under different pricing plans, and how consumers could participate in power markets by selling solar power, adjusting demand in response to price changes, and incorporating storage (including EV batteries).

4. Privacy and security issues associated with capturing, storing and sharing detailed energy data.

The project will advance knowledge of factors influencing energy usage, the potential value of household renewable energy, and the possible dynamics of distributed energy markets under different regulatory and pricing regimes.