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Advanced Small-Signal Model of Multi-Terminal Modular Multilevel Converters for Power Systems Based on Dynamic Phasors

  • Hu, Pan (School of Electrical Engineering, Wuhan University) ;
  • Chen, Hongkun (School of Electrical Engineering, Wuhan University) ;
  • Chen, Lei (School of Electrical Engineering, Wuhan University) ;
  • Zhu, Xiaohang (School of Electrical Engineering, Wuhan University) ;
  • Wang, Xuechun (School of Electrical Engineering, Wuhan University)
  • Received : 2017.06.14
  • Accepted : 2017.11.27
  • Published : 2018.03.20

Abstract

Modular multilevel converter (MMC)-based high-voltage direct current (HVDC) presents attractive technical advantages and contributes to enhanced system operation and reduced oscillation damping in dynamic MMC-HVDC systems. We propose an advanced small-signal multi-terminal MMC-HVDC based on dynamic phasors and state space for power system stability analysis to enhance computational accuracy and reduce simulation time. In accordance with active and passive network control strategies for multi-terminal MMC-HVDC, the matchable small-signal stability models containing high harmonics and dynamics of internal variables are conducted, and a related theoretical derivation is carried out. The proposed advanced small-signal model is then compared with electromagnetic-transient and traditional small-signal state-space models by adopting a typical multi-terminal MMC-HVDC network with offshore wind generation. Simulation indicates that the advanced small-signal model can successfully follow the electromechanical transient response with small errors and can predict the damped oscillations. The validity and applicability of the proposed model are effectively confirmed.

Keywords

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Fig. 1. Four-terminal MMC?HVCD test system.

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Fig. 2. Topology of MMC?HVDC. (a) Structure of the converter and active network. (b) Averaged EMT model of MMC?HVDC.

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Fig. 3. Control block diagrams of dual-loop and circulating?suppressing controllers. (a) Dual-loop controller. (b) 2ndharmonic circulating?suppressing controller.

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Fig. 4. DC network model. (a) DC node model. (b) Equivalentmodel of DC line.

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Fig. 5. Methodology used to obtain the complete small-signal model of a multi-terminal MMC?HVDC.

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Fig. 6. Response of the MMC1 converter. (a) D-axis AC current. (b) Q-axis AC current. (c) Direct voltage. (d) Direct current.

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Fig. 7. Response of the MMC2 converter. (a) D-axis AC current. (b) Q-axis AC current. (c) Direct voltage. (d) Direct current.

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Fig. 8. Response of the MMC3 converter. (a) D-axis AC current. (b) Q-axis AC current. (c) Direct voltage. (d) Direct current.

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Fig. 9. Response of the MMC4 converter. (a) D-axis AC current. (b) Q-axis AC current. (c) Direct voltage. (d) Direct current.

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Fig. 10. Response of the MMC1 converter. (a) D-axis AC current. (b) Q-axis AC current. (c) Direct voltage. (d) Direct current.

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Fig. 11. Response of the MMC2 converter. (a) D-axis AC current. (b) Q-axis AC current. (c) Direct voltage. (d) Direct current.

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Fig. 12. Response of the MMC3 converter. (a) D-axis AC current. (b) Q-axis AC current. (c) Direct voltage. (d) Direct current.

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Fig. 13. Response of the MMC4 converter. (a) D-axis AC current. (b) Q-axis AC current. (c) Direct voltage. (d) Direct current.

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Fig. 14. Frequency response for state-space and dyn.phasor models.

TABLE I MMC CONVERTER PARAMETERS

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TABLE II RUNNING TIME OF SIMULATION UNDER THE THREE MODELS

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