Abstract
The paper presents a Markov chain reliability model of a cogeneration power plant substation. Stochastic automata networks formalism and functional transition rates were used to specify the reliability behavior of a system. Iterative solution techniques were used to find steady-state solution of Markov models with different sets of randomly generated failure and repair rates. Modeling results were used to perform uncertainty and sensitivity analysis of the reliability model. DOI: http://dx.doi.org/10.5755/j01.eee.19.5.1214
Highlights
Markov chain is an effective statistical modeling technique which can describe complex behavior of various stochastic systems and has a well-developed mathematical apparatus
Markov chain models of industrial power systems can have thousands or even millions of states. This means that the use of efficient model specification techniques and fast computation algorithms is very important in reliability modeling
There are 14 different items connected with 12 line segments, it means that a Markov chain reliability model has 1026, i.e. more than 67 million states
Summary
Markov chain is an effective statistical modeling technique which can describe complex behavior of various stochastic systems and has a well-developed mathematical apparatus. Markov chain models of industrial power systems can have thousands or even millions of states This means that the use of efficient model specification techniques and fast computation algorithms is very important in reliability modeling. One of the advantages of using Markov chain model is that it allows computing steady state probabilities of all system states, which helps to estimate probabilities of rare events and failure scenarios. This would be a difficult task in performing simulation, and would require a lot of CPU time or implementation of special modeling techniques [9]. Necessary computations can be executed efficiently using a Markov chain model and iterative solution algorithms
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
