Neuro-fuzzy approach to real-time transient stability prediction based on synchronized phasor measurements
Journal
Electric Power Systems Research
Journal Volume
49
Journal Issue
2
Pages
123-127
Date Issued
1999
Author(s)
Abstract
With new systems capable of making synchronized phasor measurements there are possibilities for real-time assessment of the stability of a transient swing 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 utilize real-time phasor angle measurements to provide fast transient stability prediction for use with high-speed control. From simulation tests on a sample power system, it reveals that the proposed tool can yield a highly successful prediction rate in real-time.
Subjects
Fuzzy hyperrectangular composite neural network (FHRCNN); Phasor measurement unit (PMU); Real-time transient stability prediction
Other Subjects
Computer simulation; Fuzzy control; Neural networks; Speed control; Transients; Synchronized phasor measurements; Electric power systems
Type
journal article