Abstract
In power systems, reliability evaluations mainly depend on the precise forecasting of the reliability parameters of the internal components. Nonetheless, the procedure of calculating the reliability parameters such as failure rate and repair rate parameters is based on the failure statistics and measurements which can cause much inherent uncertainty and thus affecting the reliability indices of the system. Therefore, the main purpose of this work is to suggest a sufficient and easy-implemented approach based on scenario production to capture the uncertainty of the reliability parameters including the failure rate and repair rate variables. Here, the scenario generation process is constructed using the roulette wheel mechanism along with the probability density function of the random variables. Then, the proposed scenario based approach makes use of a scenario reduction mechanism to avoid high computational burden. This aspect of the proposed stochastic framework makes it useful for the optimization applications which require iterative analysis. In order to see the feasibility and satisfying performance of the proposed framework, an IEEE standard test system is used as the case study.