Parameter coordination fuzzy adaptive VSG control strategy
DOI:
CSTR:
Author:
Affiliation:

1.College of Electrical and New Energy, China Three Gorges University, Yichang 443002, China; 2.Hubei Engneering Research Center for Smart Energy Technology, China Three Gorges University, Yichang 443002, China; 3.Institute of Advanced Technology for Carbon Neutrality, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Clc Number:

TP2

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Although conventional Virtual synchronous Generator (VSG) solves the problem of lack of inertia of new energy grid-connection and can effectively support the system frequency, it also brings active power and frequency oscillation phenomenon under disturbance. In order to further suppress the power oscillation and improve the dynamic response performance of the system comprehensively, a small signal model of VSG active power control loop was established, and the influence of virtual parameter selection on system performance was analyzed according to the pole distribution diagram of the closed-loop transfer function. Secondly, by observing the curves of power angular and frequency of a synchronous generator, refined fuzzy rules were designed to regulate the value of the virtual inertia. An appropriate damping ratio was selected by simultaneously considering the maximum overshoot of active power, the rate of change of frequency, the settling time and the rise time. The value of the virtual damping was coordinately adapted based on the chosen damping ratio and the relationship between the virtual damping and the virtual inertia. Finally, several VSG control strategies were compared by simulations with Matlab/Simulink to verify the feasibility and effectiveness of the proposed control strategy.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: March 19,2024
  • Published:
Article QR Code