Hines Receives NSF CAREER Award
- By Dawn Marie Densmore
Dr. Paul Hines has received a National Science Foundation (NSF) CAREER Award for $400,000 for his research proposal entitled, “CAREER: Harnessing Smart Grid Data to Enable Resilient and Efficient Electricity.” According to the NSF, “The CAREER program is a Foundation-wide activity that offers the National Science Foundation's most prestigious awards in support of junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of education and research within the context of the mission of their organizations.” The objective of Hines’ research project is to harness Smart Grid data (Big Data) to enable more resilient and efficient electricity. The award begins September 2013.
“Dr. Hines exemplifies the incredible research being done by our younger faculty members,” says Bernard “Chip” Cole, Interim Dean of CEMS. “His research has been featured in prestigious journals such as: Scientific American, the IEEE Transactions on Power Systems, and Energy Policy”
“This award provides the unique opportunity to conduct research that will hopefully lead to technology that can make power grids more resilient, including the ability to better incorporate variable power sources, such as wind and solar power,” says Dr. Hines.
Dr. Hines, assistant professor in the School of Engineering, has a BS in Electrical Engineering from Seattle Pacific University, an MS in Electrical Engineering from the University of Washington and a Ph.D. from Carnegie Mellon University in engineering and public policy. He previously served as a research scientist at the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), and as an Electrical Engineer at the US Federal Energy Regulatory Commission.
Dr. Hines scholarly contributions are in the areas of electrical energy systems, decentralized (agent-based) control systems, complex networks and vulnerability, optimization, and energy policy. A key goal of his research is to reduce the frequency of very large power grid failures, such as the Northeast blackout of August 2003.
Three research sub-projects contribute to the goal of harnessing Smart Grid data (Big Data) to enable more resilient and efficient electricity. 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.
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.
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.
For more information, on this award visit:
Contact Paul Hines at email@example.com.