Application of a novel fuzzy neural network to real-time transient stability swings prediction based on synchronized phasor measurements

The ability to rapidly acquire synchronized phasor measurements from around the system opens up new possibilies for power system protection and control. In this paper we develop a novel class of fuzzy hyperrectangular composite neural networks which utilize synchronized phasor measurements to provide fast transient stability swings prediction for use with high-speed control. Primary features of the method include constructing a fuzzy neural network for all fault locations, using a short window of realistic-precision post-fault phasor measurements for the prediction, and testing robustness to variations in the operating point. From simulation tests on a sample power system, it reveals that the proposed tool can yield a highly successful prediction rate in real-time.