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In transmission networks, power flows and network topology are deeplyintertwined due to power flow physics. Recent literature shows that a specificmore hierarchical network structure can effectively inhibit the propagation ofline failures across the entire system. In particular, a novel approach namedtree partitioning has been proposed, which seeks to bolster the robustness ofpower networks through strategic alterations in network topology, accomplishedvia targeted line switching actions. Several tree partitioning problemformulations have been proposed by considering different objectives, amongwhich power flow disruption and network congestion. Furthermore, variousheuristic methods based on a two-stage and recursive approach have beenproposed. The present work provides a general framework for tree partitioningproblems based on mixed-integer linear programming (MILP). In particular, wepresent a novel MILP formulation to optimally solve tree partitioning problemsand also propose a two-stage heuristic based on MILP. We perform extensivenumerical experiments to solve two tree partitioning problem variants,demonstrating the excellent performance of our solution methods. Lastly,through exhaustive cascading failure simulations, we compare the effectivenessof various tree partitioning strategies and show that, on average, they canachieve a substantial reduction in lost load compared to the originaltopologies.

Mixed-integer linear programming approaches for tree partitioning of power networks