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Continuous-Control-Set Model Predictive Control Strategy for MMC-UPQC Under Non-Ideal Conditions

Author

Listed:
  • Lianghua Chen

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Jianping Zhou

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Jiayu Zhai

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Lisheng Yang

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Xudong Qian

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Zhiyong Tao

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

Abstract

In the MMC-based unified power quality conditioner (MMC-UPQC), the computational burden of finite-control-set model predictive control (FCS-MPC) increases rapidly with the number of MMC submodules. Meanwhile, conventional linear and nonlinear control methods suffer from limited compensation accuracy. To address this, a control strategy combining continuous-control-set model predictive control (CCS-MPC) and phase-shifted carrier pulse-width modulation (PSC-PWM) is proposed. CCS-MPC performs repeated time-domain optimization based on the system model. It offers advantages such as fast dynamic response and ease of implementation, thereby enhancing both dynamic and steady-state performance, as well as compensation effectiveness. Unlike FCS-MPC, the computational complexity of CCS-MPC combined with PSC-PWM does not depend on the number of submodules, which significantly reduces the overall computational burden. Simulation results verify that the proposed method exhibits superior performance under three scenarios: grid-side voltage unbalance, high-order harmonic injection, and nonlinear load connection. Compared with the linear PI control strategy and the nonlinear passivity-based control strategy, the proposed method significantly enhances power quality and system robustness.

Suggested Citation

  • Lianghua Chen & Jianping Zhou & Jiayu Zhai & Lisheng Yang & Xudong Qian & Zhiyong Tao, 2025. "Continuous-Control-Set Model Predictive Control Strategy for MMC-UPQC Under Non-Ideal Conditions," Energies, MDPI, vol. 18(11), pages 1-14, June.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:11:p:2946-:d:1671208
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    References listed on IDEAS

    as
    1. Jingtao Zhou & Jianping Zhou & Hao Yang & Liegang Huang, 2024. "Passive Super-Twisting Second-Order Sliding Mode Control Strategy for Input Stage of MMC-PET," Energies, MDPI, vol. 17(9), pages 1-20, April.
    2. Xuhong Yang & Wenjie Chen & Congcong Yin & Qiming Cheng, 2024. "Fractional-Order Sliding-Mode Control and Radial Basis Function Neural Network Adaptive Damping Passivity-Based Control with Application to Modular Multilevel Converters," Energies, MDPI, vol. 17(3), pages 1-18, January.
    3. Yongchun Yang & Xiangning Xiao & Shixiao Guo & Yajing Gao & Chang Yuan & Wenhai Yang, 2018. "Energy Storage Characteristic Analysis of Voltage Sags Compensation for UPQC Based on MMC for Medium Voltage Distribution System," Energies, MDPI, vol. 11(4), pages 1-17, April.
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