An AI-based Approach for Scalable Cyber-Physical Optimal Response in Power Systems

Numerous research studies are being conducted to enhance the resilience of the power grid by detecting potential cyber or physical disturbances on the system. However, the development of effective mitigation techniques and remediation actions for cyber-physical systems (CPS) facing disturbance scenarios is in an early stage. Therefore, this paper focuses on building a framework of scalable cyber-physical optimal response. A review of artificial intelligence methods relevant to the design of the response framework is conducted. Then, an artificial intelligence method based on controller sensitivities is presented and initial results are discussed for a 9-bus system to motivate its use in improving AI-based intrusion response.