Frontiers in Computer Science (Jun 2024)

Fuzzy Markov model for the reliability analysis of hybrid microgrids

  • Kunjabihari Swain,
  • Murthy Cherukuri,
  • Indu Sekhar Samanta,
  • Abhilash Pati,
  • Jayant Giri,
  • Jayant Giri,
  • Amrutanshu Panigrahi,
  • Hong Qin,
  • Saurav Mallik

DOI
https://doi.org/10.3389/fcomp.2024.1406086
Journal volume & issue
Vol. 6

Abstract

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This research presents a process for analyzing a hybrid microgrid's dependability using a fuzzy Markov model. The research initiated an analysis of the various microgrid components, such as wind power systems, solar photovoltaic (PV) systems, and battery storage systems. The states that are induced by component failures are represented using a state-space model. The research continues by suggesting a hybrid microgrid reliability model that analyzes data using a Markov process. Problems arise when trying to estimate reliability metrics for the microgrid using data that is both restricted and imprecise. This is why the study takes uncertainties into account to make microgrid reliability estimations more realistic. The importance of microgrid components concerning their overall availability is evaluated using fuzzy sets and reliability assessments. The study uses numerical analysis and then carefully considers the outcomes. The overall availability of hybrid microgrids is 0.99999.

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