ONLINE VOLTAGE STABILITY MARGIN ASSESSMENT AND ENHANCEMENT IN DEREGULATED ENVIRONMENT USING SUPPORT VECTOR REGRESSION

Abstract

Recently the operation of power system strategies has changed significantly due to the introduction of deregulation in electricity markets. The power systems are being operated with high stress, hence sufficient voltage stability margin and reactive power support are necessary to be managed to ensure secure operation of the power system. This paper proposes a Support Vector Regression (SVR) along with Fuzzy Logic Controller (FLC) based tool for online voltage stability monitoring and estimation of VAR support requirement at the critical load buses of power system for improving voltage stability margin at different operating conditions. The SVR input vector is in the form of bus voltage angle and reactive power load. The voltage stability margin index (VSMI) and voltage stability factor (VSF) of the most vulnerable bus is used as target for SVR. The proposed tool successfully estimates the voltage stability margin and VAR support for various transactions in deregulation environment and also under N-1 contingency. This method has been successfully applied to the IEEE 14 bus and IEEE 30 bus test systems and the results of SVR are compared with Artificial Neural Networks (ANN) based methods. The results obtained using SVR is better than that of ANN in terms of mean squared error and execution time. Which are chosen as performance indices.