ANN-Based Statistical Computation for Remote End Fault Monitoring of the IEEE 14 Bus Microgrid Network

Datta, Sagnik; Chattopadhyay, Surajit; Das, Arabinda

doi:10.1080/03772063.2023.2182371

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2023

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“…Machine learning and artificial neural network-based protection methods to detect the fault location and forecast the asymmetrical faults can easily be managed by these methods [109,[117][118][119][120]. In certain circumstances, it is difficult to fit in and impossible to adjust to these changes.…”

Section: Advance Protection Schemementioning

confidence: 99%

Enhancing Microgrid Stability and Energy Management: Techniques, Challenges, and Future Directions

Safder,

Sanjari,

Hamza

et al. 2023

Energies

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Microgrid technology offers a new practical approach to harnessing the benefits of distributed energy resources in grid-connected and island environments. There are several significant advantages associated with this technology, including cost-effectiveness, reliability, safety, and improved energy efficiency. However, the adoption of renewable energy generation and electric vehicles in modern microgrids has led to issues related to stability, energy management, and protection. This paper aims to discuss and analyze the latest techniques developed to address these issues, with an emphasis on microgrid stability and energy management schemes based on both traditional and distinct approaches. A comprehensive analysis of various schemes, potential issues, and challenges is conducted, along with an identification of research gaps and suggestions for future microgrid development. This paper provides an overview of the current state of the field and proposes potential areas of future research.

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