Outage prediction of distribution network overhead lines using support vector machine to improve resiliencece

Predicting the status of power grid components, especially overhead lines in response to extreme weather event, plays an important role in planning pre-resource allocation, as well as restoring loads more quickly at a faster time which can improve the power grid resilience. In this paper, a Multi-dimensional Support Vector Machine algorithm is proposed to predict outage overhead lines assuming storm paths. In this model, dimensions are based on five distinct features: the distance from building, distance from tree, distance from center of storm, storm speed and cable type. The result of the proposed model is the classification of overhead lines status into two out and operational statuses implemented on the 33-bus IEEE network. The results show that the proposed model predicts outage lines with high accuracy.