Grid-edge Modeling and Optimization to support Decarbonization and Resilience
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.