Biblio
This paper sheds light on the collaborative efforts in restoring cyber and physical subsystems of a modern power distribution system after the occurrence of an extreme weather event. The extensive cyber-physical interdependencies in the operation of power distribution systems are first introduced for investigating the functionality loss of each subsystem when the dependent subsystem suffers disruptions. A resilience index is then proposed for measuring the effectiveness of restoration activities in terms of restoration rapidity. After modeling operators' decision making for economic dispatch as a second-order cone programming problem, this paper proposes a heuristic approach for prioritizing the activities for restoring both cyber and physical subsystems. In particular, the proposed heuristic approach takes into consideration of cyber-physical interdependencies for improving the operation performance. Case studies are also conducted to validate the collaborative restoration model in the 33-bus power distribution system.
Cascading failure, which can be triggered by both physical and cyber attacks, is among the most critical threats to the security and resilience of power grids. In current literature, researchers investigate the issue of cascading failure on smart grids mainly from the attacker's perspective. From the perspective of a grid defender or operator, however, it is also an important issue to restore the smart grid suffering from cascading failure back to normal operation as soon as possible. In this paper, we consider cascading failure in conjunction with the restoration process involving repairing of the failed nodes/links in a sequential fashion. Based on a realistic power flow cascading failure model, we exploit a Q-learning approach to develop a practical and effective policy to identify the optimal way of sequential restorations for large-scale smart grids. Simulation results on three power grid test benchmarks demonstrate the learning ability and the effectiveness of the proposed strategy.