Pruning kernel regression trees for security assessment of the Crete network

Abstract

This paper presents the capabilities provided by Kernel Regression Trees - a hybrid non-parametric regression technique - to on-line dynamic security assessment and monitoring of isolated power systems with high penetration of wind power. In the applied technique, to avoid overfitting a pruning algorithm is used to extract the security structure. This approach, which is demonstrated on the electrical power system of Crete island, proved to extract simple, interpretable, and reliable security structures. A description of the security problem and the data set generation procedure are included. Comparative results regarding performances of Regression Trees and Decision Trees are presented and discussed.