Classification des états de stabilité en tension d'un système électrique par des fonctions de base radiales et des cartes auto-organisatrices
Self organizing feature map and radial basis function based voltage stability state classification of power system
This paper presents an application of self-organizing feature map (SOFM) in conjunction with radial basis function (RBF) fo r determining voltage stability states of a power network. These voltage stability states are compared with a voltage stability index (LVSI) calculated using information obtained from dynamic simulation. Simulations were carried out on IEEE57 bus test system consid ering load changes and contingencies. The data collected from simulations are th en used as inputs to the SOFM which acts as a classifier to determine the voltage stability st ates of the system under test. To augment the effectiveness of the proposed method, the initial classification re sults were improved with the application of RBF technique. Studies show that the SOF M-RBF combination delivers high classification accuracy in the order of almost 100%, and can be considered an effecti ve soft-computing tool to ease the operation of large-multi bus power network under variable operating conditions.
Kabir CHAKRABORTY, Abhinandan DE, Abhijit CHAKRABARTI
Voltage Stability, Kohonen’s Self-Organi zing Feature Map (SOFM), Radial basis function (RBF