Predicting future behavior of transient events rapidly enough to evaluate remedial control options in real-time

Electric utilities are becoming increasingly interested in using synchronized phasor measurements from around power systems to enhance their protection and remedial action control strategies. Accordingly, the task of predicting future behavior of the power system before it actually occurs has become an important area of research. This paper presents and analyses several approaches for solving the real-time prediction problem. In order to solve power systems with detailed load models fast enough for real-time prediction, the authors present a new piecewise constant current load model approximation technique that can solve a model as complex as the New England 39 bus system with composite voltage dependent loads much faster than in real-time. If the reduced order model is too large for real-time solution, then a pattern recognition tool such as decision trees can be trained off line to associate the post-fault phasor measurements with the outcome of future behavior. In this case also, the piecewise constant current technique would be needed to perform the offline training set generation with sufficient speed and accuracy