Journal of System Simulation ›› 2023, Vol. 35 ›› Issue (6): 1191-1202.doi: 10.16182/j.issn1004731x.joss.22-0191

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Secure State Estimation of Distribution Network Based on Kalman Filter Decomposition

Xinghua Liu(), Siwen Dong, Jiaqiang Tian()   

  1. School of Electrical Engineering, Xi'an University of Technology, Xi'an 710048, China
  • Received:2022-03-09 Revised:2022-05-11 Online:2023-06-29 Published:2023-06-20
  • Contact: Jiaqiang Tian E-mail:liuxh@xaut.edu.cn;tianjiaqiang@xaut.edu.cn

Abstract:

A new state estimation algorithm is proposed to improve the accuracy to obtain the optimal state estimation of distribution network against FDI attack. In the case of phasor measurement units being attacked and the measurement results being altered, the optimal Kalman estimate can be decomposed into a weighted sum of local state estimates. Focusing on the insecurity of the weighted sum method, a convex optimization based on local estimation is proposed to replace the method and combine the local estimation into a secure state estimation. The simulation results show that the proposed estimator is consistent with the Kalman estimator when all the PMU measuring devices operate well. When the PMU device is attacked and the measurement is abnormal, a sufficient condition is provided, under which the security state estimator is stable.

Key words: distribution network, state estimation, security, Kalman filter decomposition, FDI attack

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