Ensemble Kalman Filter based Dynamic State Estimation of PMSG-based Wind Turbine

被引：1

作者：

Afrasiabi, Shahabodin ^{[1
]}

Afrasiabi, Mousa ^{[1
]}

Rastegar, Mohammad ^{[1
]}

Mohammadi, Mohammad ^{[1
]}

Parang, Benyamin ^{[1
]}

Ferdowsi, Farzad ^{[2
]}

机构：

[1] Shiraz Univ, Sch Elect & Comp Engn, Shiraz, Iran

[2] Univ Louisiana, Elect & Comp Engn Dept, Lafayette, LA USA

来源：

2019 IEEE TEXAS POWER AND ENERGY CONFERENCE (TPEC) | 2019年

关键词：

Permanent Magnet Synchronous Generator (PMSG); Dynamic state estimation; Ensemble Kalman filter (EnKF); Wide area monitoring and control (WAMAC);

D O I：

10.1109/tpec.2019.8662174

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Permanent magnet synchronous generators (PMSGs) are commonly used in wind power generation because of less maintenance cost and flexible speed control. Dynamic state estimation is beneficial in wide area monitoring and control (WAMAC). Because, it enables the access to non-measurable variables. This paper proposes a nonlinear dynamic state estimation based on ensemble Kalman filter (EnKF) for PMSG-based wind turbines. The results of the proposed method are evaluated by comparing with extended Kalman filter (EKF) and unscented Kalman filter (UKF).

引用

页数：4

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