Stochastic modeling and parameter estimation of turbogenerator unit of a thermal powerplant under classical and Bayesian inferential framework
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Date
2023-10
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Abstract
Theworkreported in present study deals with the development of a novel stochastic model
andestimation of parameters to assess reliability characteristics for a turbogenerator unit of
thermal power plant under classical and Bayesian frameworks. Turbogenerator unit consists
of five components namely turbine lubrication, turbine governing, generator oil system, gen
erator gas system and generator excitation system. The concepts of cold standby redun
dancy andWeibull distributed random variables are used in development of stochastic
model. The shape parameter for all the random variables is same while scale parameter is
different. Regenerative point technique and semi-Markov approach are used for evaluation
of reliability characteristics. Sufficient repair facility always remains available in plant as well
as repair done by the repairman is considered perfect. As the life testing experiments are
time consuming, so to highlight the importance of proposed model Monte Carlo simulation
study is carried out. A comparative analysis is done between true, classical and Bayesian
results of MTSF, availability and profit function.