Voltage Stability Assessment in Power Network Using Artificial Neural Network

In present days, electrical load demand is growing day by day and in order to meet the increasing electrical load demand, power generating plants are operating their plants at their maximum capacity. So there is always a risk of voltage collapse, which will cause the shutdown of entire power system and its block out, which will cause an inconvenience to the customers and great losses to the power utility companies. It is always a better practice to know about the weakest elements in the system and weakest buses and their maximum loading limit. The objective of this paper is to evaluate the reliability using artificial neural network (ANN) in voltage stability assessment to determine secure/insecure state of the power system. The input data of ANN are derived from offline Newton-Raphson (NR) load flow analysis in MATLAB environment. The result obtained from the ANN method is compared with the NR load flow analysis in terms of accuracy to predict the status of the system. The proposed method has been tested using IEEE data test and shows it effectiveness in assessing the voltage stability in large network using ANN by predicting voltage stability indicator.