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Dynamic response and low voltage ride-through enhancement of brushless double-fed induction generator using Salp swarm optimization algorithm

Author

Listed:
  • Ahsanullah Memon
  • Mohd Wazir Bin Mustafa
  • Waqas Anjum
  • Ahsan Ahmed
  • Shafi Ullah
  • Saleh Masoud Abdallah Altbawi
  • Touqeer Ahmed Jumani
  • Ilyas Khan
  • Nawaf N Hamadneh

Abstract

A brushless double-fed induction generator (BDFIG) has shown tremendous success in wind turbines due to its robust brushless design, smooth operation, and variable speed characteristics. However, the research regarding controlling of machine during low voltage ride through (LVRT) need greater attention as it may cause total disconnection of machine. In addition, the BDFIG based wind turbines must be capable of providing controlled amount of reactive power to the grid as per modern grid code requirements. Also, a suitable dynamic response of machine during both normal and fault conditions needs to be ensured. This paper, as such, attempts to provide reactive power to the grid by analytically calculating the decaying flux and developing a rotor side converter control scheme accordingly. Furthermore, the dynamic response and LVRT capability of the BDFIG is enhanced by using one of the very intelligent optimization algorithms called the Salp Swarm Algorithm (SSA). To prove the efficacy of the proposed control scheme, its performance is compared with that of the particle swan optimization (PSO) based controller in terms of limiting the fault current, regulating active and reactive power, and maintaining the stable operation of the power system under identical operating conditions. The simulation results show that the proposed control scheme significantly improves the dynamic response and LVRT capability of the developed BDFIG based wind energy conversion system; thus proves its essence and efficacy.

Suggested Citation

  • Ahsanullah Memon & Mohd Wazir Bin Mustafa & Waqas Anjum & Ahsan Ahmed & Shafi Ullah & Saleh Masoud Abdallah Altbawi & Touqeer Ahmed Jumani & Ilyas Khan & Nawaf N Hamadneh, 2022. "Dynamic response and low voltage ride-through enhancement of brushless double-fed induction generator using Salp swarm optimization algorithm," PLOS ONE, Public Library of Science, vol. 17(5), pages 1-24, May.
    • Handle: RePEc:plo:pone00:0265611
    DOI: 10.1371/journal.pone.0265611
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    References listed on IDEAS

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    1. Junfang Hao & Jinhai Huang & Ailing Zhang & Hongjie Ai & Qun Zhang & Bo Yang, 2020. "Optimal coordinated control of hybrid AC/VSC-HVDC system integrated with DFIG via cooperative beetle antennae search algorithm," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-22, November.
    2. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Samer H. Atawneh & Madihah Md. Rasid & Nayyar Hussain Mirjat & Muhammad Akram Bhayo & Ilyas Khan, 2020. "Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids," Energies, MDPI, vol. 13(16), pages 1-22, August.
    3. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Madihah Md Rasid & Nayyar Hussain Mirjat & Zohaib Hussain Leghari & M. Salman Saeed, 2018. "Optimal Voltage and Frequency Control of an Islanded Microgrid Using Grasshopper Optimization Algorithm," Energies, MDPI, vol. 11(11), pages 1-20, November.
    4. Mei Su & Weiyu Jin & Guanguan Zhang & Weiyi Tang & Frede Blaabjerg, 2018. "Internal Model Current Control of Brushless Doubly Fed Induction Machines," Energies, MDPI, vol. 11(7), pages 1-19, July.
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