Abstract
This paper reports an application of a simulationmethod called chronological Monte Carlo to evaluate power systems reliability. The Monte Carlo methods are, nowadays, the most widely used method for the estimation of reliability indices. Most of reliability studies that use Monte Carlo simulations are based on a hypothetical situation: the use of a constant failure rate ??. This paper demonstrates a new application that is able to include the typical variation of the failure rate ?? of electrical components that is represented by the well-known bathtub curve and, moreover, is able to show the advantages of different maintenance strategies. The results obtained with the Monte Carlo applications are compared with each other and with a typical Monte Carlo process. The proposed methodologies will be tested in the IEEE RTS-79.
Highlights
Monte Carlo simulations remain the standard method to compute estimates of reliability indices in Power Systems
It was proved that the inclusion of the real variation of the failure rate λλ has a significant impact upon the reliability indices
This new approach is more complex, it allows to include the impact of the natural process of degradation of electrical components
Summary
Monte Carlo simulations remain the standard method to compute estimates of reliability indices in Power Systems. Most of reliability studies that present a chronological approach use an exponential distribution to generate the life cycle of the components of a Power System. In this paper, the existence of a variable failure rate, the process of degradation of the components of a power system is included Another very important aspect in the power systems reliability evaluation is treated: the maintenance policies. This paper presents three different Monte Carlo applications that correspond to three different maintenance policies: reactive maintenance, preventive maintenance and predictive maintenance The inclusion of this new aspect has one goal: the improvement of the reliability indices through the extension of the useful life period of the components by applying different maintenance strategies
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