Abstract
The paper develops a technique of available 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. Artificial neural networks are used to quickly adjust the modified state estimator in real time.
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