Node Recovery Optimization of Cyber-Physical Power Systems Based on the Probability of Fault Propagation

This study focuses on the node recovery optimization of Cyber-Physical Power Systems (CPPS) based on a fault probability propagation model. The fault probability propagation model considers the weak interdependence between power and communication equipment. In order to search for the optimal recovery nodes in CPPS networks after failures, the study adopts ant colony optimization to explore recovery paths in the system network. This algorithm can comprehensively consider key factors such as network status, node importance, and the recoverability of faulty nodes in the fault probability model. By calculating the quality of the paths explored by the ant colony algorithm, the system can effectively select the recovery nodes with the strongest power supply capacity in the power network. To validate the effectiveness of the proposed method, simulations are conducted on the IEEE 39-bus system. The results indicate that using the ant colony algorithm to explore node recovery paths can significantly restore power supply capacity of the system.