Forecasting the Total Transfer Capability of Intersystem Lines for On-line Control of Electric Power System Operation

Abstract

Abstract: The paper develops a technique of total transfer capability forecasting in the controlled lines. The technique involves using dynamic state estimation, modified state estimation, and artificial neural networks. Dynamic state estimation yields the predicted values of the state variables. Modified state estimation calculates the total transfer capability on the basis of the forecast data. The obtained state is called the resultant steady state. Depending on operation constraints, the modified state estimation program parameters to be adjusted to provide optimal result of the modified state estimation are taken from the database by using ANN, and the resultant state variables of the interconnected power system are calculated. Artificial neural networks are used to quickly adjust the modified state estimator in real time.