Determination of Minimum Singular Value Indices at Voltage Collapse by Means of Neural Network

Abstract

The minimum singular value of the power flow jacobian matrix has been used as a static voltage stability index representing system security in power flow based system models by the scalar magnitude of a voltage stability index may be a very difficult task. VSIs at voltage collapse points are difficult to predict when the reactive power generation limits are taken into account. Here a fast method to calculate the minimum singular value and the corresponding left and right singular vectors is presented. The main advantages of the developed algorithm are the small amount of computation time needed. In order to determine voltage collapse points for different patterns of load and generation increase, an optimal power flow approach for solving the maximum loading problem was used with these points the MSV is calculated and used for training and testing the NNs.