Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency Stabilization

  • Abdul Latif
  • , S. M.Suhail Hussain
  • , Ahmed Al-Durra
  • , Atif Iqbal*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

This article delves into the intricate challenge of frequency stabilization within islanded microgrids (IMGs), particularly exacerbated by the integration of low-inertia renewable power generations. A hierarchical control strategy is proposed, comprising a fuzzy rule-based controller, a two-degree-of-freedom fractional-order PI controller, and a proportional resonant controller. The bolstering of frequency stabilization is achieved by the integration of aggregated electric vehicle storage into the IMG. Adaptive tuning of the fuzzy rule-based load frequency controller's parameters is facilitated by a novel quasi-oppositional prairie dog technique (QOPDT), developed within this study. A comprehensive comparison is conducted between the efficacy of the QOPDT technique and various other optimization methods. Significant improvements in system frequency stability across diverse scenarios are observed with the adoption of the QOPDT-based controller, as evidenced by qualitative assessment. Furthermore, the investigation extends to consider the impact of time-varying delay on the integrated electric vehicle system, broadening the scope of the investigation. Validation of the effectiveness and practicality of the proposed control framework is undertaken utilizing the real-time OPAL-RT 5700 testbed platform..

Original languageEnglish
Pages (from-to)704-721
Number of pages18
JournalIEEE Open Journal of the Industrial Electronics Society
Volume5
DOIs
StatePublished - 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors. T.

Keywords

  • Electric vehicle (EV)
  • communication delay
  • fuzzy rule-based control (FRC)
  • load frequency regulation (LFR)
  • quasi-oppositional prairie dog technique (QOPDT)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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