Many human activities are electricity-dependent. As major providers of electricity, the performance of high-power stations represents a vital part of any national economy. In the present study, we identified the distribution fitting to TBF. The distribution fitting based on failure data collection, calculated TBF, plotted the histogram for TBF and matched the plot on the continuous distributions' functions have been investigated. Then, the most valid distribution was found to be the Three-parameter Weibull distribution. Shape, scale and location parameters values were 0.75169, 32.125 and 1.9375, respectively.

No abstract

This paper presents an algorithm for estimating the performance of high-power station systems connected in series, parallel, and mixed series-parallel with collective factor failures caused by any part of the system equipment. Failures that occur frequently can induce a selective effect, which means that the failures generated from different equipment parts can cause failures in various subsets of the system elements. The objectives of this study are to increase the lifetime of the station and reduce sudden station failures. The case study data was collected from an electricity distribution company in Baghdad, Iraq. Data analysis was performed using the most valid distribution of the Weibull distribution with scale parameterα= 1.3137 and shape parameterβ= 94.618. Our analysis revealed that the reliability value decreased by 2.82% in 30 days. The highest critical value was obtained for components T1, CBF5, CBF7, CBF8, CBF9, and CBF10and must be changed by a new item as soon as possible. We believe that the results of this research can be used for the maintenance of power systems models and preventive maintenance models for power systems.

No abstract

No abstract

No abstract

No abstract

No abstract