The use of Markov Chain method to determine spare transformer number and location

Abstract

<span lang="EN-US">The purpose of this study is to develop a method to determine spare transformer number and location. Using Markov Chain method, state transition model and steady state probability was used on each 500-kV substation in order to analyze the effect of spare number and location variation with the reliability changes. To give an actual result of the case study, calculation of spare transformer number and location on 500/150 kV transformers in Java Bali System was analyzed. The steady state probability results will vary depending on the number of spare transformer, these results can then be used to assess the spare transformer needed. The variation of spare transformer location can be used to analyze the best possible location of the spare in order to satisfy the reliability required. The methodology presented shows an integrated calculation for determining the spare transformer number and location.</span>

Improving Graph-based methods for computing qualitative properties of markov decision processes

“…Because of the stochastic behaviors of many computer systems, probabilistic structures are more useful for modeling such systems [4][5][6]. Markov chains and Markov decision processes (MDPs) are wellknown structures for modelling stochastic systems and are widely used in artificial intelligence, economy, operations research and software engineering [7][8][9]. Several examples of the stochastic systems and their modelling are available in [3,4,7].…”