Efficient Data-driven Approach for Solving AC Optimal Power Flow with Physics-informed Learning and Feasibility Calibrations
A physics-informed deep learning framework that generates optimal solutions for the AC Optimal Power Flow problem while ensuring feasibility through a novel calibration algorithm.
