Application Strategies of Model Predictive Control for the Design and Operations of Renewable Energy-Based Microgrid: A Survey

Keifa Vamba Konneh, Oludamilare Bode Adewuyi, Mohammed Elsayed Lotfy, Yanxia Sun, Tomonobu Senjyu

Research output: Contribution to journalReview articlepeer-review

19 Citations (Scopus)

Abstract

In recent times, Microgrids (MG) have emerged as solution approach to establishing resilient power systems. However, the integration of Renewable Energy Resources (RERs) comes with a high degree of uncertainties due to heavy dependency on weather conditions. Hence, improper modeling of these uncertainties can have adverse effects on the performance of the microgrid operations. Due to this effect, more advanced algorithms need to be explored to create stability in MGs’. The Model Predictive Control (MPC) technique has gained sound recognition due to its flexibility in executing controls and speed of processors. Thus, in this review paper, the superiority of MPC to several techniques used to model uncertainties is presented for both grid-connected and islanded system. It highlights the features, strengths and incompetencies of several modeling methods for MPCs and some of its variants regarding handling of uncertainties in MGs. This survey article will help researchers and model developers to come up with more robust model predictive control algorithms and techniques to cope with the changing nature of modern energy systems, especially with the increasing level of RERs penetration.

Original languageEnglish
Article number554
JournalElectronics (Switzerland)
Volume11
Issue number4
DOIs
Publication statusPublished - 1 Feb 2022

Keywords

  • Grid-connected systems
  • Isolated systems
  • Microgrid
  • Model predictive control
  • Renewable energy resources
  • Uncertainty management

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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