Visualization and Analysis of Voltage Stability Using Self-Organizing Neural Networks

On the basis of a compelling mathematical description of voltage stability in electrical power systems and its indication using the minimum singular value of the load flow Jacobian the application of a self-organizing Kohonen-Neural-Network (KNN) is presented for a fast and secure indication and visualization of voltage stability. The advantage of the structural representation of the system condition by the KNN is worked out bypassing the disabilities of standard voltage stability indicators. In addition the application of KNN aims at the analysis of measures for the improvement of voltage stability. All examples are calculated using a model of a real power transmission system.