This article considers a cyber-physical system with multiple remote state estimation subsystems under denial-of-service (DoS) attack. Suppose that there are multiple distributed estimation systems, in each of which, a sensor monitors the system and sends its local estimation to a remote estimator over one of multiple wireless channels. A DoS attacker emits noise power to jam the wireless channels. A scheduler is installed to dispatch each sensor to transmit information through the specific channel to minimize the total estimation error covariance on account of energy-saving. Whereas, the DoS attacker attempts to jam a channel to realize an opposite objective. With considering interference from other individuals, a multisensor multichannel remote state estimation model is constructed. A myopic policy and a long-term online interaction strategy under varying network environment are investigated and compared by solving a two-player zero-sum game and a Markov game, respectively. Simulations are provided to demonstrate our results.

Resilient State Estimation of Cyber-Physical System With Multichannel Transmission Under DoS Attack

This article presents a novel dynamic event-triggered scheme for the load frequency regulation with periodic denial-of-service (DoS) attacks and deception attacks via decentralized output-based control algorithm. Compared with the existing event-triggered strategy, the proposed one automatically changes the parameters of the triggered condition by detecting the frequency trend of the DoS attack to change the release frequency, which can ensure the stability of the power system while increasing the probability of effective transmission subject to DoS attack and thus, reducing network bandwidth usage. First, the proposed dynamic event-triggered strategy combined with the decentralized output-based controller is presented in a unified framework to deal with deception attacks and DoS attacks in the multiarea power system. Then, we utilize the Lyapunov stability theory to analyze the exponential stability in the mean-square sense and the robustness of the power system. By solving a set of linear matrix inequalities (LMIs), a procedure is given for the design of output-based load frequency controllers. Finally, a three-area power system is exploited as a simulation to verify the effectiveness of the proposed results.

Dynamic Event-Triggered Output Feedback Control for Load Frequency Control in Power Systems With Multiple Cyber Attacks

Smart grid is built by combination of electric and information technologies and achieves the two-way interaction between power utilization and power generation. Unfortunately, new security threats appears together with cyber-physical communication systems. In order to properly monitor power network, an effective cyber attack detection and state estimation method are required to know attack and system states. This article considers the problem of robust grid state estimation and suggests a technique for distributed state estimation in power networks. First, the distribution power system incorporating multiple synchronous generators is modeled as a state-space framework, where attack occurs in measurements. Basically, the false data injection attacks can interfere with state estimation process by tampering with sensor measurements. Using mean squared error principle, the distributed dynamic state estimation algorithm is designed where local and neighboring gains are obtained using optimal filter and graph theory. For local gain computation, the attack parameter is obtained using the Bayesian learning process. The convergence condition of the proposed approach is derived. Extensive simulation results show that the proposed approach is able to estimate the system state within a short period of time. Hopefully, the proposed methodology can be used to tolerate the cyber attacks for improving the confidence of the grid state estimation process.

Distributed Grid State Estimation Under Cyber Attacks Using Optimal Filter and Bayesian Approach

This article presents a novel dynamic event-triggered scheme for the load frequency regulation with periodic denial-of-service (DoS) attacks and deception attacks via decentralized output-based control algorithm. Compared with the existing event-triggered strategy, the proposed one automatically changes the parameters of the triggered condition by detecting the frequency trend of the DoS attack to change the release frequency, which can ensure the stability of the power system while increasing the probability of effective transmission subject to DoS attack and thus, reducing network bandwidth usage. First, the proposed dynamic event-triggered strategy combined with the decentralized output-based controller is presented in a unified framework to deal with deception attacks and DoS attacks in the multiarea power system. Then, we utilize the Lyapunov stability theory to analyze the exponential stability in the mean-square sense and the robustness of the power system. By solving a set of linear matrix inequalities (LMIs), a procedure is given for the design of output-based load frequency controllers. Finally, a three-area power system is exploited as a simulation to verify the effectiveness of the proposed results. 

Detection against randomly occurring complex attacks on distributed state estimation

This paper proposes a switched system method (SSM) for the fusion state estimation (SE) under denial-of-service (DoS) attacks in power systems. One of the subsystems in the SSM employs the widely used dynamic model with unit state transition matrix and zero control input. The performance of this model is favorable when the system operates in normal conditions but tends to suffer while the system state dramatically changes. Moreover, its accuracy and convergence is sensitive to the value of the process noise covariance matrix. The other subsystem, with some opposite characteristics, utilizes a pseudo-dynamic model derived from the linearization of the power flow equation. A switching rule based on the innovations is established to make a tradeoff between the two subsystems with regard to estimation accuracy, converge speed, and computing time. Apart from the difference in the reporting rate of various measurements, cyber attacks, such as DoS attacks may result in the absence of measurements in the snapshot of SE at the finest time scale. To deal with this problem, the linear extrapolation and multistep prediction techniques are involved. Simulation studies are conducted on the IEEE-14 bus test system and a 33 bus distribution system under various scenarios, and the performance of the proposed method is discussed.

Ji Chen

Papers

Fusion State Estimation for Power Systems Under DoS Attacks: A Switched System Approach