Abstract
With the push for higher efficiency and reliability, an increasing number of intelligent electronic devices (IEDs) and associated information and communication technology (ICT) are integrated into the Internet of Things (IoT)-enabled smart grid. These advanced technologies and IEDs also bring potential vulnerabilities to the intelligent cyber–physical smart grid. State estimation, as a primary step of system monitoring and situational awareness, is a potential target for attackers. A number of other smart grid applications, such as voltage stability assessment and contingency screening, utilize state estimation results as input data. False data injection (FDI) is a specific way to attack state estimation by manipulating input data. Existing research mainly focuses on the mathematical analysis of FDI attacks; however, in these methods, discussions of reachability requirements to compromise measurements considering cyberinfrastructure are limited. Reachability is defined as a measure that estimates the number of hosts to compromise for the possible FDI. Most of the existing FDI attack methods require the simultaneous manipulation on multiple measurement devices in different substations, in order to bypass the bad data detection, which may be impractical. In this paper, a new type of reachability-based FDI attack considering the cybernetwork with a practical attack is proposed and validated on two IEEE test systems. The corresponding defence mechanisms are (a) decentralized state estimation (DSE), (b) DSE with additional backup computational nodes, (c) communication network rerouting, and (d) intrusion detection system, and they were developed and presented with validation for two IEEE test systems with superior performance for an IoT-enabled intelligent smart grid system.
Highlights
Introduction published maps and institutional affilWith the integration of information and communication technology (ICT) and the Internet of Things (IoT) enabling advanced control automation in the intelligent cyber–physical systems, smart grid technology is confronted with an increasing number of challenges from cyber vulnerabilities [1–5]
Given that it is assumed that a special protection system is deployed to protect the control center from attacks, this assumption can be applied to all group leaders
With the additional backup group leader involved in the decentralized state estimation (DSE), all potential reachabilitybased False data injection (FDI) were mitigated in the IEEE 14-bus system
Summary
Introduction published maps and institutional affilWith the integration of information and communication technology (ICT) and the Internet of Things (IoT) enabling advanced control automation in the intelligent cyber–physical systems, smart grid technology is confronted with an increasing number of challenges from cyber vulnerabilities [1–5]. By applying state estimation applications, the operating condition is analytically determined by the measurements of system states at different measuring nodes in the smart grid. By gathering measurement values throughout the system such as bus voltage magnitudes, transferred active power, and reactive power flows on the transmission lines, and reactive power injections among the system on the basis of the mathematical formulation in [32], a DC power-flow-based measurement system can be expressed as follows. This analytical method is extended for linear state estimators (LSE): z = Hx + e (1).
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