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Hybrid Modulated Model Predictive Control in a Modular Multilevel Converter for Multi-Terminal Direct Current Systems

Author

Listed:
  • Zhi Wu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Jiawei Chu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Wei Gu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Qiang Huang

    (Jiangsu Electrical Power Company Research Institute, State Grid, Nanjing 211100, China)

  • Liang Chen

    (Jiangsu Electrical Power Company Research Institute, State Grid, Nanjing 211100, China)

  • Xiaodong Yuan

    (Jiangsu Electrical Power Company Research Institute, State Grid, Nanjing 211100, China)

Abstract

In this paper a hybrid modulated model predictive control (HM 2 PC) strategy for modular-multilevel-converter (MMC) multi-terminal direct current (MTDC) systems is proposed for supplying power to passive networks or weak AC systems, with the control objectives of maintaining the DC voltage, voltage stability and power balance of the proposed system. The proposed strategy preserves the desired characteristics of conventional model predictive control method based on finite control set (FCS-MPC) methods, but deals with high switching frequency, circulating current and steady-state error in a superior way by introducing the calculation of the optimal output voltage level in each bridge arm and the specific duty cycle in each Sub-Module (SM), both of which are well-suited for the control of the MMC system. In addition, an improved multi-point DC voltage control strategy based on active power balanced control is proposed for an MMC-MTDC system supplying power to passive networks or weak AC systems, with the control objective of coordinating the power balance between different stations. An MMC-HVDC simulation model including four stations has been established on MATLAB/Simulink (r2014b MathWorks, Natick, MA, USA). Simulations were performed to validate the feasibility of the proposed control strategy under both steady and transient states. The simulation results prove that the strategy can suppress oscillations in the MMC-MTDC system caused by AC side faults, and that the system can continue functioning if any one of the converters are tripped from the MMC-MTDC network.

Suggested Citation

  • Zhi Wu & Jiawei Chu & Wei Gu & Qiang Huang & Liang Chen & Xiaodong Yuan, 2018. "Hybrid Modulated Model Predictive Control in a Modular Multilevel Converter for Multi-Terminal Direct Current Systems," Energies, MDPI, vol. 11(7), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1861-:d:158309
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    Citations

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    Cited by:

    1. Stefano Farnesi & Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2019. "Solid-State Transformers in Locomotives Fed through AC Lines: A Review and Future Developments," Energies, MDPI, vol. 12(24), pages 1-29, December.
    2. Fabio Viola, 2018. "Experimental Evaluation of the Performance of a Three-Phase Five-Level Cascaded H-Bridge Inverter by Means FPGA-Based Control Board for Grid Connected Applications," Energies, MDPI, vol. 11(12), pages 1-47, November.
    3. Crestian Almazan Agustin & Jen-te Yu & Cheng-Kai Lin & Xiang-Yong Fu, 2019. "A Modulated Model Predictive Current Controller for Interior Permanent-Magnet Synchronous Motors," Energies, MDPI, vol. 12(15), pages 1-20, July.
    4. Xuhong Yang & Haoxu Fang, 2022. "RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model," Energies, MDPI, vol. 15(5), pages 1-18, February.
    5. Jin Zhu & Tongzhen Wei & Qunhai Huo & Jingyuan Yin, 2018. "A Full-bridge Director Switches based Multilevel Converter with DC Fault Blocking Capability and Its Predictive Control Strategy," Energies, MDPI, vol. 12(1), pages 1-22, December.

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