Neuro-fuzzy approach to real-time transient stability prediction based on synchronized phasor measurements

With new systems capable of making synchronized phasor measurements there a re possibilities for real-time assessment of the stability of a transient s wing in power systems. In the future, on-line control will be necessary as operating points are pushed closer toward the margin and fast reaction time becomes critical to the survival of the system. In this paper we develop a novel class of fuzzy hyperrectangular composite neural networks which util ize real-time phasor angle measurements to provide fast transient stability prediction for use with high-speed control. From simulation tests on a sam ple power system, it reveals that the proposed tool can yield a highly succ essful prediction rate in real-time. (C) 1999 Elsevier Science S.A. All rig hts reserved.