An admittance-guided optimization using harmonic perturbations and a physics-informed neural network identifies the worst-case dispatch command that drives a microgrid into sub-synchronous oscillations.
Destabilizing attack and robust defense for inverter-based microgrids by adversarial deep reinforcement learning,
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Admittance-Guided Inverter Dispatch Command Manipulation Attack: A Grid Stability-Oriented Approach
An admittance-guided optimization using harmonic perturbations and a physics-informed neural network identifies the worst-case dispatch command that drives a microgrid into sub-synchronous oscillations.