Conventional power systems are developing into cyber-physical power systems (CPPS) with wide applications of communication, computer and control technologies. However, multiple practical cases show that the failure of cyber layers is a major factor leading to blackouts. Therefore, it is necessary to discuss the cascading failure process considering cyber layer failures and analyze the vulnerability of CPPS. In this paper, a CPPS model, which consists of cyber layer, physical layer and cyber-physical interface, is presented using complex network theory. Considering power flow properties, the impacts of cyber node failures on the cascading failure propagation process are studied. Moreover, two vulnerability indices are established from the perspective of both network structure and power flow properties. A vulnerability analysis method is proposed, and the CPPS performance before and after cascading failures is analyzed by the proposed method to calculate vulnerability indices. In the case study, three typical scenarios are analyzed to illustrate the method, and vulnerabilities under different interface strategies and attack strategies are compared. Two thresholds are proposed to value the CPPS vulnerability roughly. The results show that CPPS is more vulnerable under malicious attacks and cyber nodes with high indices are vulnerable points which should be reinforced.
30 July 2018 in Journal of Modern Power Systems and Clean Energy
This paper presents a model of cascading failures in cyber-physical power systems (CPPSs) based on an improved percolation theory, and then proposes failure mitigation strategies. In this model, the dynamic development of cascading failures is divided into several iteration stages. The power flow in the power grid, along with the data transmission and delay in the cyber layer, is considered in the improved percolation theory. The interaction mechanism between two layers is interpreted as the observability and controllability analysis and data update analysis influencing the node state transformation and security command execution. The resilience indices of the failures reflect the influence of cascading failures on both topological integrity and operational state. The efficacy of the proposed mitigation strategies is validated, including strategies to convert some cyber layer nodes into autonomous nodes and embed unified power flow controller (UPFC) into the physical layer. The results obtained from simulations of cascading failures in a CPPS with increasing initial failure sizes are compared for various scenarios. Dynamic cascading failures can be separated into rapid and slow processes. The interdependencies and gap between the observable and controllable parts of the physical layer with the actual physical network are two fundamental reasons for first-order transition failures. Due to the complexity of the coupled topological and operational relations between the two layers, mitigation strategies should be simultaneously applied in both layers.
This paper proposes a novel approach to analyze the impacts of cyber layer failures (i.e., protection failures and monitoring failures) on the reliability evaluation of composite power systems. The reliability and availability of the cyber layer and its protection and monitoring functions with various topologies are derived based on a reliability block diagram method. The availability of the physical layer components are modified via a multi-state Markov chain model, in which the component protection and monitoring strategies, as well as the cyber layer topology, are simultaneously considered. Reliability indices of composite power systems are calculated through non-sequential Monte-Carlo simulation. Case studies demonstrate that operational reliability downgrades in cyber layer function failure situations. Moreover, protection function failures have more significant impact on the downgraded reliability than monitoring function failures do, and the reliability indices are especially sensitive to the change of the cyber layer function availability in the range from 0.95 to 1.