Load Frequency Controller Considering Interconnection with a Hybrid Distributed Generation

DIambomba Hyacinthe Tungadio, Yanxia Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposed an optimal model of frequency control based on predictive strategy approach. The proposed model was validated using three microgrids interconnected together via tie-lines. Two conventional power plants, hydro and thermal was interconnected with a hybrid generation system made by a photovoltaic and a wind farm. It is well known that the predictive controller and the storage system control parameters are found by expertise of the designer or using the trial and error approach. To solve this issue, the grey Wolf Optimiser (GWO) algorithm is used to tune the proposed controller and the storage system parameters to keep the power flow between the interconnected areas as scheduled when considering load variations. The proposed predictive controller was built in Matlab/Simulink and the effectiveness of the model was shown with the obtained simulation results.

Original languageEnglish
Title of host publicationInternational Conference on Electrical, Computer, and Energy Technologies, ICECET 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665442312
DOIs
Publication statusPublished - 2021
Event2021 International Conference on Electrical, Computer, and Energy Technologies, ICECET 2021 - Cape Town, South Africa
Duration: 9 Dec 202110 Dec 2021

Publication series

NameInternational Conference on Electrical, Computer, and Energy Technologies, ICECET 2021

Conference

Conference2021 International Conference on Electrical, Computer, and Energy Technologies, ICECET 2021
Country/TerritorySouth Africa
CityCape Town
Period9/12/2110/12/21

Keywords

  • Distributed generation
  • Energy storage system
  • Model predictive control
  • Photovoltaic
  • load frequency control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • General Computer Science
  • Energy Engineering and Power Technology

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