Power system transient stability assessment for real-time applications

Time-domain integration of power system differential equations is the most accurate method for transient stability assessment. However, it has heave computational burden, which restricts it from being used for on-line applications. All other on-line transient stability assessment methods make some compromise between accuracy and speed.; Most of the conventional methods used for transient stability assessment are limited to certain operating conditions, have power system modeling complexity limitations, or have heavy computational burden, which degrade their performance when used for on-line transient stability assessment. Some other real time transient stability assessment methods need special communication or multiprocessor systems for on-line implementation.; The Critical Clearing Time (CCT) is chosen as the index for transient stability assessment. Higher CCT means better system transient stability. In real-time applications, the actual fault clearing time can be compared to the CCT to assess system stability.; Artificial Neural Networks (ANN's) application on transient stability assessment is not limited to power system modeling complexity. It is trained off-line; so, the heavy computational burden is avoided in on-line applications. It has the advantage of accomplishing the complex mapping between the inputs and outputs for well designed, well trained ANN's.; It is essential to evaluate the features that have to be selected as inputs to the ANN. A technique for the selection and ranking of input features that are very crucial for transient stability assessment is proposed.; Application of Multi-Layer Perceptron (MLP) ANN, for Critical Clearing Time (CCT) estimation, to large-scale systems needs inputs that are mostly system-size independent. To achieve this goal, a MLP ANN scheme is proposed.; Time-domain integration is the most accurate method to assess system stability. Recurrent Radial Basis Function (RBF), and Multi-Layer Perceptron (MLP) ANN schemes are proposed for dynamic system modeling, and generators' angles and angular velocities prediction.; Automatic line reclosing plays an important role to restore power continuity, especially for transmission systems. It is also one of the corrective actions used to improve system stability for temporary faults. An investigation on the effect of line reclosing on transient stability assessment for multi-machine power systems is done. (Abstract shortened by UMI.)...