Fault Tolerant Control of DFIG Wind Turbine Back-to-Back Converter Based on Developed Sliding Mode Method

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Fault detection and tolerable control of wind turbine increases its reliability and availability. One of the electrical components of the wind turbine with a high error rate is the power converter. In this paper, a new method for fault tolerant (FT) control of the wind turbine back-to-back converter based on Dual Feed Induction Generator (DFIG) is presented. When a open circuit fault occurs in each of the IGBTs of the wind turbine converter, the performance of the converter is distorted and part of the current signal of each leg of the converter is lost. The classical controller cannot completely correct this change in current behavior, and for this reason, it has an abnormal performance. As a result, power generation will be accompanied by many fluctuations. In order to compensate, a new method based on sliding mode control is presented in this article. First, when an error occurs, the fault detection system identifies the faulty leg, and after reconfiguring the hardware, the proposed control system based on sliding mode control replaces the classic control system and switching operation. The fault detection method presented in this article is based on artificial neural network and it was developed based on matching with the functional parameters of the wind turbine. The proposed FT method is evaluated using a hardware simulator in a laboratory loop with a 90 kW DFIG generator. The experimental results show the proper accuracy of the fault detection method and on the other hand, the proposed FT method was able to compensate the open circuit fault of the IGBT.

Language:
Persian
Published:
Iranian Journal of Electrical and Computer Engineering, Volume:20 Issue: 4, 2023
Pages:
263 to 279
https://www.magiran.com/p2530465  
سامانه نویسندگان
  • Author (3)
    Parviz Amiri
    Associate Professor Electrical, Shahid Rajaee Teacher Training University, Tehran, Iran
    Amiri، Parviz
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