Topology Estimation in Bulk Power Grids: Guarantees on Exact Recovery
This addresses the need for faster control actions in power grids following emergencies, offering a method with theoretical guarantees, though it appears incremental as it builds on existing graphical model frameworks.
The paper tackles the problem of real-time topology estimation in bulk power grids using voltage measurements, proposing graphical model algorithms that guarantee exact recovery for radial distribution grids and provide sufficient conditions for grids with cycles.
The topology of a power grid affects its dynamic operation and settlement in the electricity market. Real-time topology identification can enable faster control action following an emergency scenario like failure of a line. This article discusses a graphical model framework for topology estimation in bulk power grids (both loopy transmission and radial distribution) using measurements of voltage collected from the grid nodes. The graphical model for the probability distribution of nodal voltages in linear power flow models is shown to include additional edges along with the operational edges in the true grid. Our proposed estimation algorithms first learn the graphical model and subsequently extract the operational edges using either thresholding or a neighborhood counting scheme. For grid topologies containing no three-node cycles (two buses do not share a common neighbor), we prove that an exact extraction of the operational topology is theoretically guaranteed. This includes a majority of distribution grids that have radial topologies. For grids that include cycles of length three, we provide sufficient conditions that ensure existence of algorithms for exact reconstruction. In particular, for grids with constant impedance per unit length and uniform injection covariances, this observation leads to conditions on geographical placement of the buses. The performance of algorithms is demonstrated in test case simulations.