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author:

Su, Minghong (Su, Minghong.) [1] | Zheng, Feng (Zheng, Feng.) [2] (Scholars:郑峰) | Liu, Baojin (Liu, Baojin.) [3] (Scholars:刘宝谨) | Liu, Wanling (Liu, Wanling.) [4]

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EI

Abstract:

Aiming at the problem that the bus voltage in low-inertia DC microgrid is prone to be affected by internal power fluctuations, a virtual inertial control strategy of DC microgrid based on improved model prediction control is proposed. Firstly, analog virtual synchronous generator (AVSG) control is introduced into the voltage outer loop, and the inertia of DC microgrid is improved by introducing virtual capacitance and damping coefficient. Secondly, in order to avoid the lag phenomenon caused by control delay, an improved model predictive control is introduced into the current inner loop to achieve fast tracking of the current set value, while eliminating the traditional PI controller and PWM regulator, thus improving the dynamic performance of the control system. Finally, a system model is established based on Matlab/Simulink for simulation. The results show that compared with the traditional PI-based virtual inertia control strategy, the proposed control strategy in this paper has smaller bus voltage fluctuation amplitude and better dynamic performance, which can effectively improve the stability of DC bus voltage and the inertia of DC microgrid. © 2023 IEEE.

Keyword:

Capacitance MATLAB Microgrids Model predictive control Power converters Power electronics Virtual Power Plants

Community:

  • [ 1 ] [Su, Minghong]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 2 ] [Zheng, Feng]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 3 ] [Liu, Baojin]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 4 ] [Liu, Wanling]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China

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Year: 2023

Page: 390-395

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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