A General Decentralized Dynamic State Estimation With Synchronous Generator Magnetic Saturation

Bendong Tan; Junbo Zhao; Marcos Netto

doi:10.1109/TPWRS.2022.3216503

A General Decentralized Dynamic State Estimation With Synchronous Generator Magnetic Saturation

Bendong Tan, Junbo Zhao, Marcos Netto

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

The saturation of the nonlinear magnetic circuit of synchronous generators is often neglected when performing Kalman filter-based dynamic state estimation (DSE), yielding significant estimation bias. This letter addresses this problem and proposes a generalized DSE framework to handle magnetic saturation. Moreover, this letter derives a state initialization procedure that improves the Kalman filter tracking speed. The framework is flexible in dealing with different saturation functions and generator models. Numerical results on the Texas 2000-bus system verify the effectiveness of the proposed method.

Original language	English (US)
Pages (from-to)	960-963
Number of pages	4
Journal	IEEE Transactions on Power Systems
Volume	38
Issue number	1
DOIs	https://doi.org/10.1109/TPWRS.2022.3216503
State	Published - Jan 1 2023
Externally published	Yes

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Electrical and Electronic Engineering

Keywords

Dynamic state estimation
magnetic saturation
nonlinear magnetic circuit
unscented Kalman filter

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10.1109/TPWRS.2022.3216503

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title = "A General Decentralized Dynamic State Estimation With Synchronous Generator Magnetic Saturation",

abstract = "The saturation of the nonlinear magnetic circuit of synchronous generators is often neglected when performing Kalman filter-based dynamic state estimation (DSE), yielding significant estimation bias. This letter addresses this problem and proposes a generalized DSE framework to handle magnetic saturation. Moreover, this letter derives a state initialization procedure that improves the Kalman filter tracking speed. The framework is flexible in dealing with different saturation functions and generator models. Numerical results on the Texas 2000-bus system verify the effectiveness of the proposed method.",

keywords = "Dynamic state estimation, magnetic saturation, nonlinear magnetic circuit, unscented Kalman filter",

author = "Bendong Tan and Junbo Zhao and Marcos Netto",

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T1 - A General Decentralized Dynamic State Estimation With Synchronous Generator Magnetic Saturation

AU - Tan, Bendong

AU - Zhao, Junbo

AU - Netto, Marcos

PY - 2023/1/1

Y1 - 2023/1/1

N2 - The saturation of the nonlinear magnetic circuit of synchronous generators is often neglected when performing Kalman filter-based dynamic state estimation (DSE), yielding significant estimation bias. This letter addresses this problem and proposes a generalized DSE framework to handle magnetic saturation. Moreover, this letter derives a state initialization procedure that improves the Kalman filter tracking speed. The framework is flexible in dealing with different saturation functions and generator models. Numerical results on the Texas 2000-bus system verify the effectiveness of the proposed method.

AB - The saturation of the nonlinear magnetic circuit of synchronous generators is often neglected when performing Kalman filter-based dynamic state estimation (DSE), yielding significant estimation bias. This letter addresses this problem and proposes a generalized DSE framework to handle magnetic saturation. Moreover, this letter derives a state initialization procedure that improves the Kalman filter tracking speed. The framework is flexible in dealing with different saturation functions and generator models. Numerical results on the Texas 2000-bus system verify the effectiveness of the proposed method.

KW - Dynamic state estimation

KW - magnetic saturation

KW - nonlinear magnetic circuit

KW - unscented Kalman filter

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JF - IEEE Transactions on Power Systems

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A General Decentralized Dynamic State Estimation With Synchronous Generator Magnetic Saturation

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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