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Intelligent secondary control in smart microgrids: an on-line approach for islanded operations

  • Shoresh Shokoohi
  • Sajjad Golshannavaz
  • Rahmat Khezri
  • Hassan Bevrani
Article
  • 82 Downloads

Abstract

Dealing with islanded microgrids (MGs), this paper aims at improving the secondary control process to restrict the fluctuations in both the voltage and frequency signals. With the aim of retrieving these parameters at the nominal values, an intelligent control scheme is devised to adjust the corresponding control parameters. To do so, an on-line self-optimizing control approach is embedded in the MG’s central controller. In the tuning process, evolutionary-based techniques such as genetic algorithms provide proper initial adjustment for the parameters. Subsequently, an artificial neural network (ANN) is triggered to provide accurate online modification of the control parameters. Specifically, the training capability of the ANN mechanism along with its extensibility feature avoids the dependency of the controller on the operating point conditions and accommodates different changes and uncertainty reflections. Detailed simulation studies are conducted to investigate the performance of the proposed approach, and the results are discussed in depth.

Keywords

Microgrid (MG) Distributed generation (DG) Intelligent secondary voltage and frequency controller Artificial neural networks (ANNs) Self-optimizing on-line controller 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Shoresh Shokoohi
    • 1
  • Sajjad Golshannavaz
    • 2
  • Rahmat Khezri
    • 1
  • Hassan Bevrani
    • 1
  1. 1.Electrical Engineering DepartmentUniversity of KurdistanSanandajIran
  2. 2.Electrical Engineering DepartmentUrmia UniversityUrmiaIran

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