Cyber-attack Detection Strategy Based on Distribution System State Estimation

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Abstract

Cyber-attacks that tamper with measurement information threaten the security of state estimation for the current distribution system. This paper proposes a cyber-attack detection strategy based on distribution system state estimation (DSSE). The uncertainty of the distribution network is represented by the interval of each state variable. A three-phase interval DSSE model is proposed to construct the interval of each state variable. An improved iterative algorithm (IIA) is developed to solve the interval DSSE model and to obtain the lower and upper bounds of the interval. A cyber-attack is detected when the value of the state variable estimated by the traditional DSSE is out of the corresponding interval determined by the interval DSSE. To validate the proposed cyber-attack detection strategy, the basic principle of the cyber-attack is studied, and its general model is formulated. The proposed cyber-attack model and detection strategy are conducted on the IEEE 33-bus and 123-bus systems. Comparative experiments of the proposed IIA, Monte Carlo simulation algorithm, and interval Gauss elimination algorithm prove the validation of the proposed method.

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APA

Long, H., Wu, Z., Fang, C., Gu, W., Wei, X., & Zhan, H. (2020). Cyber-attack Detection Strategy Based on Distribution System State Estimation. Journal of Modern Power Systems and Clean Energy, 8(4), 669–678. https://doi.org/10.35833/MPCE.2019.000216

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