Power distribution system interruption duration model using reliability

Electricity is a fundamental resource to society as a whole, since it is used in the majority of modern activities, however, it has been supplied by large-scale systems whose infrastructure is liable to failures or interruptions. Therefore, two points are worth mentioning that result in supply interruptions: the number of failures/interruptions and their duration. Thus, a correct estimation of when an accident might occur and how long it can last is of fundamental importance for planning and operating power distribution systems. Regression models are statistical tools that allow a better understanding of such problems by accurately predicting such future scenarios. In this context, a reliability analysis regression was carried out to generate a model using data from real failure occurrences aiming to provide a model capable of effectively estimating the duration of failures in power distribution systems that can also assess and determine which probability distribution accurately calculates interruption duration time. Lognormal distribution presented the better results and the developed model can be used for the simulation of realistic duration time data given the occurrence of failures in distribution systems.

Automated summary

Electricity supply is vital to society, but large-scale systems can experience failures or interruptions. Accurately estimating the time and duration of these failures is crucial for planning and operating power distribution systems. This study used regression models to analyze real failure data and develop a model capable of effectively estimating failure duration, as well as determining the accurate probability distribution for interruption duration.