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Adaptive constrained population extremal optimisation-based robust proportional-integral-derivation frequency control method for an islanded microgrid

  • Kang-Di LU
  • , Guo-Qiang ZENG*
  • , Wuneng ZHOU*
  • *Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

The expected penetration of renewable sources is driving the islanded microgrid towards uncertainties, which have highly influence the reliability and complexities of frequency control. To alleviate the influence caused by load fluctuations and inherent variability of renewable sources, this article proposes an optimised robust proportional-integral-derivation (PID) frequency control method by taking full advantage of a robust control strategy while simultaneously maintaining the basic characteristics of a PID controller. During the process of iterated optimisation, a weighted objective function is used to balance the tracking error performance, robust stability and disturbance attenuation performance. Then, the robust PID frequency (RPIDF) controller is determined by an adaptive constrained population extremal optimisation algorithm based on self-adaptive penalty constraint-handling technique. The proposed control method is examined on a typical islanded microgrid, and the control performance is evaluated under various disturbances and parametric uncertainties. Finally, the simulation results indicate that the fitness value of the proposed method is 1.7872, which is lower than 2.9585 and 3.0887 obtained by two other evolutionary algorithms-based RPIDF controllers. Moreover, the comprehensive simulation results fully demonstrate that the proposed method is superior to other comparison methods in terms of four performance indices on the most considered scenarios.

Original languageEnglish
Pages (from-to)210-227
Number of pages18
JournalIET Cyber-systems and Robotics
Volume3
Issue number3
DOIs
Publication statusPublished - Sept 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 The Authors. IET Cyber-systems and Robotics published by John Wiley & Sons Ltd on behalf of Zhejiang University Press.

Funding

This work was partially supported by the National Natural Science Foundation of China (Grant No. 61972288), the Key-Area Research and Development Program of Guangdong Province (2020B0101090004) and Natural Science Foundation of Shanghai (Grant No. 20ZR1402800).

Keywords

  • constrained evolutionary algorithm
  • frequency control
  • islanded microgrid
  • population extremal optimisation
  • robust PID controller

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