登入
洞見 - Power Systems Optimization
Conditions for Exact Solutions in Optimal Power Flow Conic Relaxations
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.
Physics-Informed Graph Neural Network for Optimizing Dynamic Reconfiguration of Power Distribution Grids
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.