
Obtaining a rank-1 voltage matrix or self-coherent cycles in the voltage matrix from a conic relaxation of the optimal power flow problem guarantees that the solution is exact and coincides with the optimal solution to the original non-convex problem.


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conditions-for-exact-solutions-in-optimal-power-flow-conic-relaxations


Conditions for Exact Solutions in Optimal Power Flow Conic Relaxations


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GraPhyR, a physics-informed graph neural network framework, can learn to optimize dynamic reconfiguration of power distribution grids to minimize grid losses and satisfy operational constraints.


physics-informed-graph-neural-network-for-optimizing-dynamic-reconfiguration-of-power-distribution-grids


Physics-Informed Graph Neural Network for Optimizing Dynamic Reconfiguration of Power Distribution Grids
