Predicting vegetation-related failure rates for overhead distribution feeders

Abstract

Faults on the electric power distribution system are responsible for a large portion of the interruptions that a customer will experience. To maintain a high level of system reliability, vegetation maintenance is often required. Analytical prediction of the effects of vegetation maintenance on distribution system reliability requires a model of the expected failure rate of line sections that includes the effects of vegetation. Vegetation-related failures are more likely to occur as the vegetation near the overhead power lines grows, increasing the line-section failure rate. Due to difficulties in using existing growth models, this paper proposes to use a direct model for failure-rate prediction based on factors that affect vegetation growth. Four models are considered: linear regression, exponential regression, linear multivariable regression, and an artificial neural network (ANN). The models are tested with historical vegetation growth parameter data and feeder failure rates. Results are compared and the features of each model are discussed.