This paper discusses about MCS method to analyse the power system reliability with the state model of components. A random number can be generated through several methods with equal probability of each number to be chosen. Random sampling is used to estimate the reliability parameter within an acceptable range. Deterministic and probabilistic reliability parameters are explained in this paper. As the power system consists of several components which causes an unreliable situation in most of the unhealthy operation of components. MCS gives a state model of individual components and with a combination of components connected through bidirectional transition rates. The probability associated with each transition is used to estimate and predict the system reliability performance. This paper explains a review of the basic idea of MCS used in power system reliability evaluation and model of different states of the existing components of the system. The outcome of this review paper is that MCS makes the system more efficient in terms of computational approach of reliability parameters.
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