Fault detection for DFIG based on sliding mode observer of new reaching law

• Autorzy: Li RuiQi , Yu WenXin , Wang JunNian , Lu Yang , Jiang Dan , Zhong GuoLiang , Zhou ZuanBo

Identyfikatory

DOI

10.24425/bpasts.2021.137389

• Języki publikacji: EN

Abstrakty

EN

For fault detection of doubly-fed induction generator (DFIG), in this paper, a method of sliding mode observer (SMO) based on a new reaching law (NRL) is proposed. The SMO based on the NRL (NRL- SMO) theoretically eliminates system chatter caused by the reaching law and can be switched in time with system interference in terms of robustness and smoothness. In addition, the sliding mode control law is used as the index of fault detection. Firstly, this paper gives the NRL with the theoretically analyzes. Secondly, according to the mathematical model of DFIG, NRL-SMO is designed, and its analysis of stability and robustness are carried out. Then this paper describes how to choose the optimal parameters of the NRL-SMO. Finally, three common wind turbine system faults are given, which are DFIG inter-turn stator fault, grid voltage drop fault, and rotor current sensor fault. The simulation models of the DFIG under different faults is established. The simulation results prove that the superiority of the method of NRL-SMO in state tracking and the feasibility of fault detection.

Słowa kluczowe

EN

fault detection; doubly-fed induction generator; sliding mode observer; new reaching law

PL

wykrywanie uszkodzeń; generator indukcyjny dwustronnie zasilany; obserwator w trybie przesuwnym; nowe prawo osiągania

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2021
• Tom: Vol. 69, nr 3
• Strony: art. no. e137389
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Li RuiQi

• School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
• Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

autor

Yu WenXin

• School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
• Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

autor

Wang JunNian

• School of Physics and Electronics, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
• Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

autor

Lu Yang

• School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
• Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

autor

Jiang Dan

• School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
• Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

autor

Zhong GuoLiang

• School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
• Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

autor

Zhou ZuanBo

• School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China
• Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).