ANN BASED ONLINE VOLTAGE STABILITY MARGIN ASSESSMENT IN DEREGULATED POWER SYSTEM

Abstract

Recently the operation of power system strategies have changed significantly due to the introduction of deregulation in electricity markets. Today, the power system are being operated with high stress, hence sufficient voltage stability margin and reactive power support are necessary to be managed to ensure secured operation of power system. This paper proposes an Artificial Neural Network (ANN) along with Fuzzy Logic Controller (FLC)based tool for online voltage stability monitoring and estimation of VAR support requirement at the critical buses of power system for improving voltage stability margin at different operating conditions. The ANN input vector is in the form of bus voltage angle and reactive power load. The voltage stability margin (VSM) and voltage stability factor (VSF) of the most vulnerable bus are used as target for ANN. The proposed tool can successfully estimate the voltage stability margin and VAR support for various transactions in deregulation environment and also under N-1 contingency. The ANN input and output patterns are generated from offline process for various simulated loading conditions using conventional continuation power flow method. The proposed method has been successfully applied to the IEEE 14 bus and IEEE 30 bus test system.