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A robust state estimation method for power systems using generalized loss function

delete2024-10-01
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PRE
AI
陈腾鹏 cover
陈腾鹏 (Tengpeng Chen)
H
Hongxuan Luo
H
Hoay Beng Gooi
E
Eddy Y. S. Foo
L
Lu Sun
N
Nianyin Zeng *
DOI:10.1016/j.eswa.2024.123994delete
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Abstract

Abstract

En 中文
The accurate estimation of power system states is crucial for effective monitoring and control. However, the performance of conventional state estimators, which assume Gaussian measurement noise and do not account for denial -of -service attacks, can deteriorate significantly in real power systems. To address these issues, this paper proposes a novel robust state estimation method based on the quadratic function (QF) and the generalized correntropy loss function (GCL). The proposed QF-GCL state estimation method can effectively deal with non -Gaussian measurement noise and denial -of -service attacks. To enhance the computational efficiency, an influence function based solving method is developed. To determine the optimal parameters for the proposed QF-GCL state estimation method, a new state estimation error covariance equation is further derived. Simulations are performed on the IEEE 30 -bus, 118 -bus and 300 -bus systems, to demonstrate the accurate and robust performance of the proposed QF-GCL robust state estimation method.
Keywords:
Non-Gaussian noise
Generalized correntropy loss
State estimation method
Denial-of-service attacks

Journal

Expert Systems with Applications cover
Expert Systems with Applications
IF:
7.5
Papers:
2.9W
Citations:
10.2W

Organization

N
Nanyang Technological University
Scholars:
4.9W
Papers: 4.8W
Citations: 8.1W
X
xiamen university
Scholars:
5.8W
Papers: 3.8W
Citations: 67