Destabilizing attack and robust defense for inverter-based microgrids by adversarial deep reinforcement learning

HIGHLIGHTS

• who: -Destabilizing attack et al. from the (UNIVERSITY) have published the research work: Destabilizing Attack and Robust Defense for Inverter-Based Microgrids by Adversarial Deep Reinforcement Learning, in the Journal: (JOURNAL)
• what: This approach shows its potential for addressing the destabilizing attack and robust defense problem in inverter-based systems. In this paper, the cyber-attack and defense strategy in inverter-based microgrids is studied systematically. The analysis reveals that such attacks can be defended by changing sensitive droop gains of the system.
• how: The simulation studies are conducted in an inverter-based . . .
  

   

  

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