A Framework for Service Restoration of Cyber-Physical Power Systems

Power systems with high penetration of distributed energy resources (DERs) are essentially cyber-physical systems. Cyber-physical energy systems provide several grid support functions including black-start in islanded mode. Hence, enhancing the resilience of the power system. After a major blackout, a self-sufficient power system can restore healthy nodes by forming microgrids (MGs) around black start distributed generators (DGs). These MGs evolve over time until all the critical loads are restored. The constellation of faults and radial nature of the network determine the load pick-up order and boundaries of MGs. The mathematical optimization model can only solve for the steady-state power equations. However, the associated dynamic transient response can cause instability across all connected nodes in a weak power grid. To address these challenges a multi-layer service restoration framework is proposed for a reconfigurable cyber-physical distribution system. The rolling horizon optimization problem is formulated as a mixed-integer second-order cone program (MISOCP) which explicitly incorporates dynamic stability constraints. The associated network traffic generated from the optimization layer is simulated in a network simulator to determine the communication latencies, whereas the power system simulations are performed in GridLAB-D. The approach is validated over a modified IEEE-123 node test feeder through simulation and the results are presented to demonstrate the efficacy of the framework for real-world applications including multiple fault scenarios with communication latencies.