A distributed robust state estimation algorithm for power systems considering maximum exponential absolute value

•The proposed distributed MEAV based algorithm can restrain the impacts of bad data and obtain less AMSE than other estimators such as WLS, MS, WLS with LNR, LAV and MLE.•The proposed algorithm can reduce computation time and is pretty robust to bad data and communication failure.•The assumption of...

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Bibliographic Details
Published in:International journal of electrical power & energy systems Vol. 133; p. 107267
Main Authors: Chen, Tengpeng, Wu, Tong, Qing, Xinlin, Amaratunga, Gehan A.J.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.12.2021
Subjects:
Distributed state estimation
Matrix-splitting
Maximum exponential absolute value
Multiple segment
Matrix-splitting
Distributed state estimation
Maximum exponential absolute value
Multiple segment
ISSN:0142-0615
Online Access:Get full text
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Summary:•The proposed distributed MEAV based algorithm can restrain the impacts of bad data and obtain less AMSE than other estimators such as WLS, MS, WLS with LNR, LAV and MLE.•The proposed algorithm can reduce computation time and is pretty robust to bad data and communication failure.•The assumption of the known distribution of measurement noise is no longer required in the proposed algorithm. In traditional power system state estimation application, the distribution of measurement noise is frequently assumed to be Gaussian. However, the distribution is sometimes unknown in practice and the above assumption may be wrong. In this paper, a totally distributed robust state estimation algorithm considering maximum exponential absolute value (MEAV) is proposed for multi-area power systems. The state estimation optimization problem is founded on the basis of the maximum correntropy criterion with Laplace kernel function. Considering that the cost function of MEAV is nondifferentiable, the limited case of multiple segment (MS) estimator and the matrix-splitting technique are further utilized together to carry out the MEAV based algorithm within a fully distributed framework. Each local area only utilizes local information and limited information from neighboring areas but can obtain the estimation solution respectively. The communication load is alleviated and the robustness of state estimation is increased. The proposed distributed robust MEAV based algorithm has been tested using the IEEE 14-bus, 118-bus and 300-bus systems. The simulation results demonstrate the effectiveness and robustness of the proposed distributed robust MEAV based algorithm.
ISSN:0142-0615
DOI:10.1016/j.ijepes.2021.107267