Statistical Modeling for the Effects of Vegetative Growth on Power Distribution System Reliability

Abstract

The purpose of this paper is to examine the effects of vegetative growth on the reliability of electric power distribution system under normal (storm exclusion) operating conditions, and to determine an effective vegetation maintenance schedule. Generalized statistical linear regression models, including Poisson, Negative Binomial, Zero-Inflated, and their mixed model variants are developed and are applied into a 5-years outage data along with vegetation maintenance history from a power company in Midwestern United States. From the methodological point of view, advanced statistical models such as zero-inflated models and mixed models are utilized the first time on outage data and provided good fit to the occurrence of outages. In practice, numerical results from this study suggest that an optimal cycle length of every 6 years could be greatly helpful for power companies in devising a cost-effective schedule, improving system reliability, and maintaining customer satisfaction.