Electronic Science and Technology ›› 2025, Vol. 38 ›› Issue (7): 89-96.doi: 10.16180/j.cnki.issn1007-7820.2025.07.012

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Research on Parameter Identification of Voltage Ride Through in Cascading Faults for Doubly Fed Induction Generator

YANG Zhi1, ZHANG Jing1(), HE Yu1, YE Yongchun2, CAO Guoqiang1, SUN Qichen1, LI Shunyu1, WANG Zhiyang1   

  1. 1. College of Electrical Engineering,Guizhou University,Guiyang 550025,China
    2. Power China Guizhou Electric Power Engineering Co., Ltd.,Guiyang 550025,China
  • Received:2024-01-10 Revised:2024-02-06 Online:2025-07-15 Published:2025-07-10
  • Supported by:
    The Science and Technology Foundation of Guizhou(2022一般013);The Science and Technology Foundation of Guizhou(GCC[2022]016-1);Educational Technology Foundation of Guizhou([2022]043)

Abstract:

With the grid-connected operation of large-scale Doubly Fed Induction Generator(DFIG), the nonlinear, impact and unbalanced characteristics of the operation process are easy to cause the chain failures of DFIG off-grid operation. In view of the existing DFIG parameter identification studies based on a single voltage sudden change for transient analysis and control strategy formulation, a single voltage sudden change study is difficult to characterize the applicability of control parameter identification. In this study, a parameter identification method of doubly-fed fan rotor controller based on IMOLA(Improved Multi-ObjectiveLichtenberg Algorithm) is proposed. The PSASP platform is used to build the electromechanical transient model of doubly-fed wind turbine, and the main control mode during steady-state operation and chain fault voltage crossing is determined. The measured data of voltage, active power and reactive power are input into the identification model, and the control parameters are identified based on IMOLA algorithm. The effectiveness and practicability of the proposed method are verified by simulation data and measured data. The results show that compared with traditional methods, IMOLA identification method can effectively improve the identification accuracy of model control parameters.

Key words: doubly-fed wind turbines, cascading faults, voltage ride through, electromechanical transient, control strategy, rotor side controller, actual measurement data, parameter identification, improved multi-objective Lichtenberg optimization algorithm

CLC Number: 

  • TM74