Collaborative Research: Learning and Optimizing Power Systems: A Geometric Approach

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The transformations of the electrical grid present a plethora of challenges to system operators and utilities. They must adapt to manage a set of highly uncertain and distributed resources such as electric vehicles and solar PVs, while at the same time operating a grid infrastructure that was designed decades ago. These challenges are particularly acute in the distribution system, where the networks are traditionally not monitored closely, and operators lack the essential information to obtain an accurate real-time operational state of the system. At the same time, the number of outages in distribution systems has started to increase as the system ages, and the loads become more dynamic. The goal of this proposal is to overcome these challenges by developing novel algorithms and new insights that increase the efficiency and resilience of the distribution systems. Educational activities would be developed around these research thrusts to ensure diverse student participation and outreach to the broader community. The project focuses on three thrusts: i) system topology estimation using the wealth of data made available by smart meters and other sensors, where the network may contain loops and the data may be highly heterogeneous; ii) characterization of the feasibility of operating points using a new geometric understanding of power flow that leads to provably efficient and optimal algorithms; and iii) restoration of service right after outages through line switching by using the results from the first two thrusts. These investigations bring in tools from power system analysis, optimization, and statistical learning to enable fundamental advances in the distribution system operations. In particular, these thrusts allow us to leverage recent advances in both technology and theory to develop timely and rigorous algorithms that solve some pressing engineering problems for the power grids. Successful application of our proposed project will allow distribution system operators to answer various "what now" and "what if" questions deriving from those highly volatile grids with large amounts of distributed resources.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.