A Comprehensive Review: Study of Artificial Intelligence Optimization Technique Applications in a Hybrid Microgrid at Times of Fault Outbreaks

Musawenkosi Lethumcebo Thanduxolo Zulu (), Rudiren Pillay Carpanen and Remy Tiako
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Musawenkosi Lethumcebo Thanduxolo Zulu: Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4001, KwaZulu-Natal, South Africa
Rudiren Pillay Carpanen: Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4001, KwaZulu-Natal, South Africa
Remy Tiako: Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4001, KwaZulu-Natal, South Africa

Energies, 2023, vol. 16, issue 4, 1-32

Abstract: The use of fossil-fueled power stations to generate electricity has had a damaging effect over the years, necessitating the need for alternative energy sources. Microgrids consisting of renewable energy source concepts have gained a lot of consideration in recent years as an alternative because they use advances in information and communication technology (ICT) to increase the quality and efficiency of services and distributed energy resources (DERs), which are environmentally friendly. Nevertheless, microgrids are constrained by the outbreaks of faults, which have an impact on their performance and necessitate dynamic energy management and optimization strategies. The application of artificial intelligence (AI) is gaining momentum as a vital key at this point. This study focuses on a comprehensive review of applications of artificial intelligence strategies on hybrid renewable microgrids for optimization, power quality enhancement, and analyses of fault outbreaks in microgrids. The use of techniques such as machine learning (ML), genetic algorithms (GA), artificial neural networks (ANN), fuzzy logic (FL), particle swarm optimization (PSO), heuristic optimization, artificial bee colony (ABC), and others is reviewed for various microgrid strategies such as regression and classification in this study. Applications of AI in microgrids are reviewed together with their benefits, drawbacks, and prospects for the future. The coordination and maximum penetration of renewable energy, solar PV, and wind in a hybrid microgrid under fault outbreaks are furthermore reviewed.

Keywords: artificial intelligence (AI); hybrid microgrids; distributed energy resources (DER); energy storage system; coordination strategies; fault outbreaks; optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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