A Bank of Kalman Filters for Current Sensors Faults Detection and Isolation of DFIG for Wind Turbine

被引：0
|
作者：
Idrissi, Imane [1 ,2 ]
Chafouk, Houcine [2 ]
El Bachtiri, Rachid [3 ]
机构：
[1] USMBA Univ, PERE Lab, REEPER Grp, EST,STI,FST, Fes, Morocco
[2] Normandie Univ, UNIRouen, IRSEEM, ESIGELEC, Rouen, France
[3] USMBA Univ, EST, PERE Lab, REEPER Grp, Fes, Morocco
来源：
PROCEEDINGS OF 2017 INTERNATIONAL RENEWABLE & SUSTAINABLE ENERGY CONFERENCE (IRSEC' 17) | 2017年
关键词：
Doubly Fed Induction Generator (DFIG); Linear Parameter Varying (LPV); Kalman Filter; Dedicated Observer Scheme (DOS);
D O I：
暂无
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
This paper presents a model based Fault diagnosis approach. This approach is based on a bank of Kalman filters. These filters are structured according to the Dedicated Observer Scheme (DOS), for detecting and isolating multiple and simultaneous current sensors faults of a doubly fed induction generator (DFIG) widely used in variable speed wind turbines. Then, a linear varying parameter model of DFIG is established and the faults diagnosis procedure is implemented. The DFIG model design and the model-based Fault Detection and Isolation (FDI) approach are performed in the Matlab/Simulink environment.
引用
收藏
页码：285 / 290
页数：6
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