Dr. Anamika Dubey
Assistant Professor
Electrical Engineering and Computer Science
Washington State University
Pullman, Washington, USA
Embedded Files
Dr. Anamika Dubey (Senior Member, IEEE) received the Ph.D. degree in electrical and computer engineering from The University of Texas at Austin, Austin, TX, USA, in December 2015. She is currently Huie-Rogers Endowed Chair Associate Professor of electrical engineering with the School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, USA. She also holds a joint appointment as a Research Scientist with the Pacific Northwest National Laboratory, Richland, WA, USA. Her research focuses on the optimization and control of large-scale electric power distribution systems for improved efficiency, flexibility, and resilience. She was the recipient of the National Science Foundation CAREER Award in 2019 and IEEE PES Outstanding Young Engineer Award in 2023. She is an Associate Editor for IEEE Transactions on Power Systems and IEEE Power Engineering Letters. She is the current Secretary of IEEE PES Distribution Systems Analysis Subcommittee and IEEE PES University Education Subcommittee and the PES Chapter Chair for the IEEE Palouse Section.
Keynote Speech: Grid-edge Modeling and Optimization to Support Decarbonization and Resilience
Abstract: With rapid decarbonization goals and ambitious urban electrification targets, the electric power grid is undergoing unprecedented changes. The proliferation of distributed energy resources and flexible loads is pushing the control and operational requirements of the grid to the edge, thus significantly increasing the scale and complexity of grid operations. These grid-edge resources also hold the potential to support grid resilience in the aftermath of extreme weather events, which are impacting grid more often and with higher severity. Effective use of grid-edge resources to support decarbonization goals and resilience necessitates advances in modeling, analysis, and optimization of emerging electric power networks. In this talk, we will focus on the challenges and solutions to integrating grid-edge into grid operations. Along with traditional physics-based approaches, we will emphasize the need for scientific machine learning techniques to address the emerging computational challenges.
Google Sites
Report abuse