Dynamic state estimation of distribution network under Markov DOS attack

Energy information is vulnerable to malicious denial of service (DoS) attacks due to the diversity and openness of the smart grid environment. In order to cope with the above challenges, this paper first proposes to adopt Markov hopping model to describe the random packet loss of measurement due to DoS attacks. Then, based on Holt two‐parameter exponential smoothing and untraced Kalman filtering techniques, a one‐step predictive value compensation method for measurement data loss is proposed, and an improved dynamic untraced particle filtering algorithm based on data fusion compensation strategy is designed. Finally, an IEEE‐30 bus system is used to simulate the proposed dynamic state estimation method, which proves that the proposed method can effectively resist DoS attack. In order to address the degradation of power system state estimation performance caused by denial of service (DoS) attacks, this paper proposes a one‐step predictive value compensation method to improve UPF state estimation algorithm, and uses Markov chain model to depict packet loss caused by DoS attacks. The proposed method has better performance than the anti‐DoS attack method proposed by Li, X. The effectiveness of the method is validated through simulation experiments conducted on the IEEE‐30 node system.