Enhancing grid resiliency in distributed energy systems through a comprehensive review and comparative analysis of islanding detection methods
Status PubMed-not-MEDLINE Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články
PubMed
38802449
PubMed Central
PMC11130157
DOI
10.1038/s41598-024-62690-z
PII: 10.1038/s41598-024-62690-z
Knihovny.cz E-zdroje
- Klíčová slova
- Artificial neural network, Distributed generation, Islanding detection, Microgrid, Non-detection zone, Renewable energy, Signal processing,
- Publikační typ
- časopisecké články MeSH
Reduction of fossil fuel usage, clean energy supply, and dependability are all major benefits of integrating distributed energy resources (DER) with electrical utility grid (UG). Nevertheless, there are difficulties with this integration, most notably accidental islanding that puts worker and equipment safety at risk. Islanding detection methods (IDMs) play a critical role in resolving this problem. All IDMs are thoroughly evaluated in this work, which divides them into two categories: local approaches that rely on distributed generation (DG) side monitoring and remote approaches that make use of communication infrastructure. The study offers a comparative evaluation to help choose the most efficient and applicable IDM, supporting well-informed decision-making for the safe and dependable operation of distributed energy systems within electrical distribution networks. IDMs are evaluated based on NDZ outcomes, detection duration, power quality impact, multi-DG operation, suitability, X/R ratio reliance, and efficient functioning.
Department of Electrical Engineering Graphic Era Dehradun 248002 India
Electrical Engineering Department 1 K G Punjab Technical University Jalandhar 144603 India
Graphic Era Hill University Dehradun 248002 India
Hourani Center for Applied Scientific Research Al Ahliyya Amman University Amman Jordan
Sharad Institute of Technology College of Engineering Yadrav Maharashtra India
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