Cyber-physical Interdependencies Research Articles

Boost Distribution System Restoration With Emergency Communication Vehicles Considering Cyber-Physical Interdependence

Enhancing restoration capabilities of distribution systems is one of the main strategies for resilient power systems to cope with extreme events. However, most of the existing studies assume the communication infrastructures are intact for distribution automation, which is unrealistic. Motivated by the applications of the emergency communication vehicles (ECVs) in quickly setting up wireless communication networks after disasters, in this paper, we propose an integrated distribution system restoration (DSR) framework and optimization models, which can coordinate the repair crews, the distribution system (physical sectors), and the emergency communication (cyber sectors) to pick up unserved power loads as quickly as possible. Case studies validated the effectiveness of the proposed models and proved the benefit of considering ECVs and cyber-physical interdependencies in DSR.

Cyber-physical cascading failure and resilience of power grid: A comprehensive review

Smart grid technologies are based on the integration of the cyber network and the power grid into a cyber-physical power system (CPPS). The increasing cyber-physical interdependencies bring about tremendous opportunities for the modeling, monitoring, control, and protection of power grids, but also create new types of vulnerabilities and failure mechanisms threatening the reliability and resiliency of system operation. A major concern regarding the interdependent networks is the cascading failure (CF), where a small initial disturbance/failure in the network results in a seemingly unexpected large-scale failure. Although there has been a significant volume of recent work in the CF research of CPPS, a comprehensive review remains unavailable. This article aims to fill the gap by providing a systematic literature survey regarding the modeling, analysis, and mitigation of CF in CPPS. The open research questions for further research are also discussed. This article allows researchers to easily understand the state of the art of CF research in CPPS and fosters future work required towards full resolutions to the remaining questions and challenges.

Clustering-based reliability assessment of smart grids by fuzzy c-means algorithm considering direct cyber–physical interdependencies and system uncertainties

The steadily growing deployment of cyber systems in smart grids (SGs) has highlighted the impacts of cyber–physical interdependencies (CPIs). Although much attention has been paid to the reliability evaluation of SGs considering the system uncertainties and CPIs by Monte Carlo simulation (MCS), the computation time is one of the essential challenges of MCS-based methods. This research tries to overcome the discussed challenge by developing a new clustering-based reliability evaluation method considering the direct CPIs (DCPIs) and stochastic behaviors of renewable distributed generation units (RDGUs) and the demand side. In the proposed method, the Fuzzy c-means (FCM) clustering algorithm has been used to reduce the number of scenarios for uncertain parameters besides the DCPIs. Determining the appropriate alternatives for the number of clusters of stochastic parameters in various cases based on cyber network topologies, DG technologies, and the penetration levels of RDGUs is another contribution of this paper. Test results of applying the proposed method to an actual test system illustrate the advantages of the proposed clustering-based method. The comparison of the proposed method with MCS shows the computation time could be reduced from 21658 s to 210 s (99%), while less than 1% EENS error appears.

Composite Reliability Impacts of Synchrophasor-Based DTR and SIPS Cyber–Physical Systems

The integration of smart infrastructures that facilitate two-way communication via information and communication technology (ICT) has enhanced the efficiency and sustainability of the power network. However, technologies, such as dynamic thermal rating (DTR) systems and system integrity protection schemes (SIPS), have disadvantages, including infrastructure failures, cyber–physical interdependencies, and cyber intrusions. These disadvantages contribute to the reduced reliability of the network. Comprehensive exploration of the reliability impacts of multiple smart grid technologies on a single power network has not been conducted. A DTR and SIPS system integrating wide area monitoring functions using phasor measurement units (PMUs) is presented in this study, and the effect of ICT contingencies on network reliability is investigated. A Monte Carlo simulation approach and a scenario reduction technique are utilized in this article. This approach is evaluated on the IEEE-RTS to demonstrate the advantages of ICTs. The approach is suitable for different network topologies, in which the difference lies in the number of required PMUs. Results demonstrate that a reliable SIPS can minimize the aging process while slightly influencing load curtailment despite the increase in overall network aging due to DTR. PMU functional failures result in load loss due to loss of observability despite their high availability.

Analytical reliability evaluation method of smart micro‐grids considering the cyber failures and information transmission system faults

The reliability of smart micro-grids (SMGs), as a cyber-physical system (CPS), might be influenced by cyber failures and information transmission faults. Several Monte Carlo simulation (MCS)-based approaches have been reported to assess the reliability of SMGs and smart grids. On the other hand, analytical reliability assessment methods have been presented in some research works, while the cyber system has not been concerned. However, the literature shows a research gap in developing an accurate and fast reliability evaluation method for SMGs based on the unavailability of cyber elements and information transmission faults. This article tries to fill the discussed gap by adding the analytical modelling of cyber-physical interdependencies and information transmission faults to available analytical methods, focusing on physical uncertainties. Comparing the proposed model with existing MCS-based and analytical reliability evaluation methods illustrates the advantages of this research. Test results show that less than 5.7% expected energy not supplied (EENS) error occurs by the proposed method, which would be much faster than MCS-based ones. Moreover, the sensitivity analyses highlight the impacts of the cyber network topologies on the cyber-physical interdependencies.

Guest Editorial: Situational awareness of integrated energy systems

Guest Editorial: Situational awareness of integrated energy systems

A novel clustering-based method for reliability assessment of cyber-physical microgrids considering cyber interdependencies and information transmission errors

In recent years, the evolution of microgrids (MGs) toward a complex interacted cyber-physical system is significant, which has received much attention. Cyber-physical MGs (CPMGs) are vulnerable to various cyber-physical interdependencies mainly. Therefore, the reliability evaluation of such systems is a crucial issue. Several research works have focused on the reliability assessment of CPMGs in the literature. However, there is a research gap in developing fast and accurate models to assess the reliability of CPMGs, simultaneously considering cyber and physical failures, cyber-power interdependencies, and information transmission errors. This article aims to fill such a knowledge gap by developing a new clustering-based method to evaluate the reliability of CPMGs. The scenarios for information transmission errors are generated by the Monte Carlo simulation (MCS), besides uncertain physical parameters, e.g., the output power of renewable distributed generations (DGs). Afterward, the clustering algorithms are used to reduce the number of scenarios. In this paper, the k-means clustering algorithm has been selected to cluster the scenarios. The introduced clustering-based method is applied to a CPMG, and test results are compared to available MCS-based studies. The inaccuracy of the proposed clustering-based method is less than 3%, while its execution time is about 22 times faster than MCS-based ones. The comparative test results under various scenarios like available methods, neglecting the cyber failures and information errors illustrate the advantages of this research. The comparative test results illustrate the accuracy of the reliability calculations, while the execution time is desired.

Resilience Optimization of Wide-Area Control in Smart Distribution Grids

Large-scale power distribution networks rely on the wide-area control (WAC) function to conduct daily grid operations. Grid control is even more critical during extreme events as the WAC function is required to orchestrate the response to contingencies and enhance the power system resilience through failure localization, isolation, and service restoration. Both power and telecommunication domains are involved in control applications, giving rise to multiple cyber-physical interdependencies. This paper proposes a resilience-based optimization of the distribution service restoration (DSR) by coordinating strategies of crew dispatch and manual/remote switches operation. The telecommunication service and underlying infrastructure are identified as main enablers of the co-optimization as all considered resilience strategies communicate with the control center that collects crisis management information. Therefore, the availability of telecom points in terms of power supply is examined in this work. Failure propagation in the coupled power-telecom network is highlighted, and differences in failure propagation between overhead and underground power lines are explored. The proposed approach is formulated as a mixed-integer linear programming (MILP) model, evaluated under a multi-feeder interdependent power-telecom test network. Results show that combined scheduling of resilience strategies as well as prioritization of power supply to telecom points-of-interest, yield an enhanced recovery strategy.

Cybersecurity of Smart Electric Vehicle Charging: A Power Grid Perspective

With the roll-out of electric vehicles (EVs), the automobile industry is transitioning away from conventional gasoline-fueled vehicles. As a result, the EV charging demand is continuously growing and to meet this growing demand, various types of electric vehicle charging stations (EVCSs) are being deployed for commercial and residential use. This nexus of EVs, EVCSs, and power grids creates complex cyber-physical interdependencies that can be maliciously exploited to damage each of these components. This paper describes and analyzes cyber vulnerabilities that arise at this nexus and points to the current and emerging gaps in the security of the EV charging ecosystem. These vulnerabilities must be addressed as the number of EVs continue to grow worldwide and their impact on the power grid becomes more viable. The purpose of this paper is to list and characterize all backdoors that can be exploited to seriously harm either EV and EVCS equipments, or power grid, or both. The presented issues and challenges intend to ignite research efforts on cybersecurity of smart EV charging and enhancing power grid resiliency against such demand-side cyberattacks in general.

Discrete game-theoretic analysis of defense in correlated cyber-physical systems

A cyber-physical system (CPS) is composed of a discrete number of cyber and physical components and subject to internal failures and external disruptions. The functionality of CPS therefore is determined not only by cyber and physical components but the adversary’s attacker strategy. We characterize the effect of cyber-physical interdependency on the CPS survival probability using a product-form function with cyber and physical exponential correlation coefficients. We model simultaneous and sequential discrete games between the provider and attacker on a CPS infrastructure to analyze its survivability and reinforcement strategy at Nash equilibrium. Our results show that the cyber and physical correlation coefficients can significantly affect CPS survival probability. In general, the provider’s cyber- (or physical-) reinforcement level increases as the cyber- (or physical-) attack level increases. In each of cyber and physical domains, the reinforcement level first increases then decreases in its own correlation coefficient, probability of successful component attacks, and maximum level of available resources, but decreases in the correlation coefficient of the other domain. We apply this game-theoretic analysis to a cloud computing infrastructure, and show that its residual capacity is relatively high when the attacker has no information about the distribution of servers. Also, a high level of survival probability does not necessarily lead to high utility.

Optical Layer Routing Influence on Software-Defined C-RAN Survivability

Cloud radio access network (C-RAN) architecture based on heterogeneous radio resources and centralized processing holds promise for satisfying the diverse requirements of fifth-generation mobile applications. In order to provide fronthaul/backhaul connectivity to the radio resources, not only does a dynamic software-defined networking (SDN) optical transport (X-haul) solution resolve the capacity scaling bottlenecks, it can also lead to statistical multiplexing gains and power efficiency in the system. Infrastructure programmability due to SDN, however, can result in network reliability concerns due to the inherent cyber-physical interdependency between the physical fiber and the higher-layer (IP) control networks. In this paper, we study the SDN C-RAN robustness to node failures, considering the interplay of wireless, optical, and control domains, and examine the effectiveness of two optical-layer routing mechanisms, i.e., static load balancing and dynamic routing, for survivable system operation. Our Monte Carlo analysis points to the marginal advantage of load balancing, irrespective of connection distribution in the control plane. However, optical X-haul programmability provides for robust C-RAN operation with essentially no sensitivity to critical network elements and negligible penalty in terms of fronthaul segment latency.

Consideration of Cyber-Physical Interdependencies in Reliability Modeling of Smart Grids

A smart grid is a cyber-physical system designed to achieve sustainability by facilitating the use of renewable energy sources, without compromising the reliability of power distribution and transmission. The research presented in this paper seeks to facilitate analysis of the reliability achieved by smart grids. To this end, we present an analytical reliability model that captures the effect of impairments originating from both physical and cyber components, as well as the effect of cyber-physical interdependencies among these components. The model can be instantiated with failure data from field use or simulation. We categorize and quantify dependencies in the smart grid and analyze the impact on reliability of introducing additional interdependencies. Finally, we present a case study that investigates the effect of physical and cyber improvements on overall reliability of the smart grid, and demonstrate that flawed cyber infrastructure can result in reliability lower than that of a conventional power grid with less advanced control.

Cyber-Physical Interdependency in Dynamic Software-Defined Optical Transmission Networks

Software-defined networking (SDN) has been proposed as a next-generation control and management framework, facilitating network programmability to address emerging dynamic application requirements. The separation of control and data planes in SDN demands the synergistic operation of the two entities for globally optimized performance. We identify the collaboration of the control plane and the data plane in software-defined optical transmission systems as a cyber-physical interdependency where the physical fiber network provides the “cyber” control network with means to distribute control and signaling messages and in turn is itself operated by these cyber control messages. We focus on the cyber-physical interdependency in SDN optical transmission from a network robustness perspective and characterize cascading failure behaviors. Our analysis suggests that topological properties pose a significant impact on failure extensibility. We further evaluate the effectiveness of optical layer reconfigurability in improving the resilience of SDN controlled optical transmission systems.