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