New Statistical Description for the Reliability of Electric Power Systems

This paper is devoted to study a new statistical description based on the polynomial distribution function for the reliability of electric power systems. An electrical system can be represented as a structure composed of many components, parts and blocks, each of which ages and tends to fail. That is why preventing failures is especially important in electric power systems, where both industry and the population depend on the generation and constant delivery of energy. Any failure in the system affects a large number of consumers. Each system component is characterized by its time-dependent hazard function (or failure rate). Some of its statistical properties are discussed, method of moments and Weibull distribution are used for estimating the new distribution parameters. The Kaplan-Meier estimator and the Kolmogorov-Smirnov goodness-of-fit criterion are the estimation methods used in a simulation study conducted to compare the performance between distribution functions. Finally, for the description of the reliability of electrical systems, it was found that the representation of failure times by a distribution function with polynomial failure rate is more suitable according to the Kolmogorov-Smirnov (K-S) criterion.