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A Novel Voltage Sensorless Estimation Method for Modular Multilevel Converters with a Model Predictive Control Strategy

Author

Listed:
  • Yantao Liao

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China)

  • Long Jin

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China)

  • Jun You

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China)

  • Zhike Xu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China)

  • Kaiyuan Liu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China)

  • Hongbin Zhang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China)

  • Zhan Shen

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China)

  • Fujin Deng

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China)

Abstract

This paper proposes a novel voltage estimation scheme for the modular multilevel converter (MMC) based on model predictive control (MPC). The developed strategy is presented by combining a disturbance observer (DOB) with an adaptive neural network (ANN) for voltage estimation in the MMC. Firstly, the ac-side and dc bus voltages are estimated as the disturbance items of the DOB which acts as the cost function during each control cycle and ensures the minimal computational cost. Then, the submodule (SM) capacitor voltage estimation is achieved based on the ANN with the estimated ac-side and dc bus voltages. The proposed method requires only one current sensor per arm and has a simple structure with three weights to be adjusted. Comprehensive simulation studies and experiments are presented to demonstrate its effectiveness and feasibility. The results indicate that the proposed method has a high accuracy, a fast dynamic response, and no effects on the original MPC performance.

Suggested Citation

  • Yantao Liao & Long Jin & Jun You & Zhike Xu & Kaiyuan Liu & Hongbin Zhang & Zhan Shen & Fujin Deng, 2023. "A Novel Voltage Sensorless Estimation Method for Modular Multilevel Converters with a Model Predictive Control Strategy," Energies, MDPI, vol. 17(1), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:17:y:2023:i:1:p:61-:d:1305057
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    References listed on IDEAS

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    1. Junda Li & Zhenbin Zhang & Zhen Li & Oluleke Babayomi, 2023. "Predictive Control of Modular Multilevel Converters: Adaptive Hybrid Framework for Circulating Current and Capacitor Voltage Fluctuation Suppression," Energies, MDPI, vol. 16(15), pages 1-17, August.
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