Tree trimming is a go-to solution for many power utilities to reduce the number of power outages caused by storms. The effects of this are intuitive: because so many outages are caused by trees in storms, cutting back the trees will reduce outages.
Quantify or predicting this reduction is much more difficult, and yet, so critical for effective cost-benefit analysis. In Dynamic Modeling of the Effect of Vegetation Management on Weather-Related Power Outages published in Electric Power Systems Research we do just that by building a dynamic machine learning power outage prediction model, using the amount of aggressive tree trimming as one of the predictor variables. With this dynamic model we were able to run a counter-factual analysis to determine that historical tree trimming has reduced outages in Connecticut somewhere between 25 and 42%, and that additional tree trimming could have further reductions in outages in the future.
