Demand growth, new demand-side technologies and the desire to integrate more renewable energy sources are driving rapid changes to the power grid. These changes pose operational challenges because the existing paradigm is not designed to deal with the added uncertainty from inherently variable and intermittent renewable energy sources or the changes in the system behavior that will arise from replacing synchronous generators with new asynchronous power sources. This talk illustrates the use of control and optimization based methods to provide insight into the analysis, design, and operation of the envisioned new power system through case studies of conventional and wind integrated power grids. First, we discuss algorithms for optimizing storage dispatch and allocation throughout the network as a means of providing greater system flexibility and efficiency. Our analysis exploits convex relaxations and model reduction techniques to understand the factors that drive optimal storage integration strategies. In the second part of the talk, we examine how increasingly distributed generation resources affects power system efficiency.
Prof. Gayme’s research interests are in modeling, design and control of distributed systems. Her group studies interconnected and spatially distributed systems using computational and theoretical methods from applied mathematics, dynamics, controls, optimization and fluid mechanics. The group focuses on two main application areas (1) the development of control oriented models for turbulent shear flows and (2) creating algorithms and tools to help facilitate the integration of renewable power sources into electric power grids. Recent work on shear flow turbulence aims to leverage knowledge of wind farm flow physics to design wind farm and grid level algorithms that can facilitate larger scale grid-integration of wind energy.