A new robust dynamic state estimation approach for power systems with non-Gaussian noise

A new robust dynamic state estimation approach for power systems with non-Gaussian noise

The Gaussian noise distribution is typically used in dynamic state estimation (DSE) but it is not always true in practice because of abnormal system inputs, impulsive noise and measurement outliers. In this paper, a new robust DSE approach based on a new robust Lp norm based estimator and the cubatu...

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Bibliographic Details
Main Authors: Chen, Tengpeng, Liu, Fangyan, Luo, Hongxuan, Foo, Eddy Yi Shyh, Sun, Lu, Sun, Yuhao, Gooi, Hoay Beng
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2024
Subjects:
Engineering
Non-Gaussian noise
Cubature Kalman filter
Online Access:https://hdl.handle.net/10356/178654
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Institution: Nanyang Technological University
Language: English
Description
Summary:The Gaussian noise distribution is typically used in dynamic state estimation (DSE) but it is not always true in practice because of abnormal system inputs, impulsive noise and measurement outliers. In this paper, a new robust DSE approach based on a new robust Lp norm based estimator and the cubature Kalman filter (CKF) is developed for power systems with non-Gaussian noise statistics. The Lp norm based estimator is derived from the Lp norm formula and the quadratic formula in order to alleviate the impacts from bad data and outliers. The proposed Lp-CKF DSE approach exhibits good accuracy because a new estimation error covariance is obtained by using the influence function. The robustness of the proposed Lp-CKF DSE approach is verified by performing simulations on a generator in the IEEE 39-bus system.

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