Static Security Assessment Using a Probabilistic Neural Network Based Classifier

In this paper, a probabilistic neural network (PNN) based classifier is used to judge the static security of the power system. The proposed classifier classifies the security of the power system based on the voltage profile of each bus in reference to changes in the generation and load profile in the system. The probabilistic neural network is used and compared with the radial basis function neural network (RBFNN) and the backpropagation neural network (BPNN). The PNN shows superior results in comparison to other techniques. The proposed methodology is examined using three IEEE standard test systems, where the input to the neural network is the voltage profile at each bus, the output of the PNN classifies the security of the power system into three classes, normal, alert and emergency. KeywordsStatic security, probabilistic neural networks, radial basis function neural networks, voltage level, power system classifier.