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<p>To enhance the voltage gain and regulate the output voltage under various loading and wind speeds, the Quasi Z-Source Direct Matrix Converter (QZSDMC) is proposed for PMG-based Direct Drive Wind Energy Conversion Systems (DDWECS). At first, using state space analysis, the small signal model of the QSDMC in space domain has been attained, and the transfer function of QZSDMC has been further calculated and analyzed. The stability analysis of the QZSDMC was conducted and proved that the system remains stable for all ranges of output power without using filter. The proposed QZSDMC based DDWECS with Improved Space Vector Pulse Width Modulation (ISVPWM) Control Scheme was simulated using Matlab and compared with existing methods. The simulation results are validated with 1&#xa0;kW, 415&#xa0;V, 50&#xa0;Hz experimental setup with FPGA Processor. The outcomes are examined using the following metrics: switching stress, boost factor, total harmonic distortion, and efficiency.</p>

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Small signal modelling and analysis of quasi Z-source direct matrix converter for wind energy conversion system

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月24日

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  • K. T. Maheswari,
  • C. Kumar,
  • T. Dharma Raj,
  • Hady H. Fayek

摘要

To enhance the voltage gain and regulate the output voltage under various loading and wind speeds, the Quasi Z-Source Direct Matrix Converter (QZSDMC) is proposed for PMG-based Direct Drive Wind Energy Conversion Systems (DDWECS). At first, using state space analysis, the small signal model of the QSDMC in space domain has been attained, and the transfer function of QZSDMC has been further calculated and analyzed. The stability analysis of the QZSDMC was conducted and proved that the system remains stable for all ranges of output power without using filter. The proposed QZSDMC based DDWECS with Improved Space Vector Pulse Width Modulation (ISVPWM) Control Scheme was simulated using Matlab and compared with existing methods. The simulation results are validated with 1 kW, 415 V, 50 Hz experimental setup with FPGA Processor. The outcomes are examined using the following metrics: switching stress, boost factor, total harmonic distortion, and efficiency.