PMU-ANN based approach for real time voltage stability monitoring

Voltage Stability is one of the major problems to be taken into consideration for secure and reliable operation of modern power systems. This paper presents a Phasor Measurement Unit and Artificial Neural Network (PMU-ANN) based approach for voltage stability monitoring in real time. The proposed approach uses the Feed Forward Neural Network (FFNN). The input to FFNN is voltage magnitude and voltage angle measured from PMU. The optimal placement of PMU is obtained by Integer Linear Programming (ILP). Various voltage stability indices are used as indicator for voltage stability monitoring. The effectiveness of the proposed approach is demonstrated on New England 39 bus test system.