Advances and opportunities in the model predictive control of microgrids: Part I–primary layer

Zhenbin Zhang, Oluleke Babayomi, Tomislav Dragicevic, Rasool Heydari, Cristian Garcia, Jose Rodriguez, Ralph Kennel

Research output: Contribution to journalReview articlepeer-review

Abstract

The smart-grid has requirements of flexible automation, efficiency, reliability, resiliency and scalability. These are necessitated by the increasing penetration of power-electronics converters that interface distributed renewable energy systems which energize the fast-evolving electric power network. Microgrids (MGs) have been identified as modular grids with the potential to effectively satisfy these characteristics when enhanced with advanced control capabilities. Model predictive control (MPC) facilitates the multivariable control of power electronic systems while accommodating physical constraints without the necessity for a cascaded structure. These features result in fast control dynamic response and good performance for systems involving non-linearities. This paper is a survey of the recent advances in MPC-based converters in MGs. Schemes for the primary control of MG parameters are presented. We also present opportunities for the MPC converter control of autonomous MGs (power quality and inertia enhancement), and transportation electrification. Finally, we demonstrate MPC's capabilities through hardware-in-the-loop (HiL) results for a proposed adaptive MPC scheme for grid-forming converters.

Original languageEnglish
Article number107411
JournalInternational Journal of Electrical Power and Energy Systems
Volume134
DOIs
Publication statusPublished - Jan 2022

Keywords

  • Converter control
  • Future trends of microgrid control
  • Hierarchical microgrid control
  • Hybrid ac/dc microgrids
  • Model predictive control
  • Multi-agent control
  • Networked and autonomous microgrids

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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