Voltage stability using ANN Combined with Multilinear Regression Models

Abstract

This paper combined artificial neural network and multilinear regression models to predict voltage stability for power system. An approach for power system is considered by varying loads. Therefore, a modified model, depending on artificial neural network (ANN) dealed with estimated linear regression, is implemented on the 14-bus system electrical network dependent on its load flow data to estimate the maximum loading point and contingency ranking. This technique was compared with conventional methods (also with basic linear regression models). Application of simulation results shows that the proposed methods are feasible and effective. The application of neural networks for online voltage stability. The programming is done in MATLAB-SIMULINK environment.