Statistical models of the effects of tree trimming on power system outages

This paper develops statistical models for estimating the impacts of tree trimming on electric power system outages under normal (nonstorm) operating conditions. The models are based on an extensive data set from Duke Power, a company in the southeastern U.S., and the models used are a negative binomial generalized linear model and a Poisson generalized linear mixed model (GLMM). The results show that: 1) increasing tree trimming frequency does lead to a decrease in the number of outages on the electric power distribution system; 2) the effects of tree trimming on different circuits can be differentiated and measured; and 3) the Poisson GLMM provides a good fit to the data in this situation. In particular, the results of the model show that for the Duke Power system, one would have expected, on average, 0.9 fewer outages per circuit over the 43-month data recording period if the time between tree trimming cycles was decreased by 1 yr across the whole system. These models could be applied to other power systems, and the results should be useful for power managers in setting tree trimming frequencies and in focusing on the most frequent trimming efforts on those circuits for which trimming will have the greatest benefit.