CAREER: Harnessing Smart Grid Data to Enable Resilient and Efficient Electricity

University Of Vermont & State Agricultural College, Burlington VT

Investigators

Abstract

The objective of this research is to harness Smart Grid data (Big Data) to enable more resilient and efficient electricity. Three research sub-projects contribute to this goal. Project 1 combines a new ?Random Chemistry? computational algorithm with complex networks methods to find patterns of vulnerability in power systems, and uses the results to reduce cascading failure blackout risk. Project 2 transforms smart grid data into actionable information about the health of a power grid by looking at statistical properties (structured noise) in data from grid sensors. Projects 1 and 2 seeks to make power grids more resilient to fluctuations from renewable generation or weather events. Project 3 uses crowdsourcing to identify trends affecting residential energy consumption through a web-based energy efficiency social network. Intellectual Merit This project integrates research ideas from diverse scientific disciplines, including complex systems, graph theory, data science, computational intelligence and crowdsourcing. Projects 1 and 2 use abstract complex systems approaches, while retaining critical information about the physics of power systems. By using data from real power systems the project will contribute to the emerging field of data science. The third project combines computational intelligence with crowdsourcing in a way that could open new ways to improve energy efficiency. Broader Impacts This project tests new educational approaches, including a unique LEGO-based grid simulator, and integrates smart grid data into new courses. New curriculum and a hands on ?smart grid road show? will be leveraged to attract students from diverse educational and demographic backgrounds to study electric energy.