Assessment of voltage stability risks under stochastic net loads using scalable SVM classification

Abstract

A novel approach is presented to identify and assess voltage stability risk in power networks that include nodes with variable loads and intermittent renewable generation. Given a power network configuration, the approach firstly assesses voltage instability boundaries at selected nodes in response to stochastic operational conditions (variable load and intermittent decentralised generation). By iteratively calculating Saddle Node Bifurcation (SNB) points one node at a time given a set of loads and intermittent generation conditions at the other nodes, those data points are used as training sets for support vector machine (SVM) classifiers. Secondly, a marginal voltage stability risk probabi..