advanced
Journal Information
Journal Information
   Description
   Editorial Board
   Guide for Authors
   Ordering

Contents Services
Contents Services
   Regular Issues
   Special Issues
   Authors Index

Links
Links
   FEI STU Bratislava
   SAS Bratislava

   Feedback

[1, 2018] 

Journal of Electrical Engineering, Vol 69, 1 (2018) 58-64 DOI: 10.1515/jee-2018-0008

On-line determination of transient stability status using multilayer perceptron neural network

Emmanuel Asuming Frimpong – Philip Yaw Okyere – Johnson Asumadu

   A scheme to predict transient stability status following a disturbance is presented. The scheme is activated upon the tripping of a line or bus and operates as follows: Two samples of frequency deviation values at all generator buses are obtained. At each generator bus, the maximum frequency deviation within the two samples is extracted. A vector is then constructed from the extracted maximum frequency deviations. The Euclidean norm of the constructed vector is calculated and then fed as input to a trained multilayer perceptron neural network which predicts the stability status of the system. The scheme was tested using data generated from the New England test system. The scheme successfully predicted the stability status of all two hundred and five disturbance test cases.

Keywords: power system stability, stability prediction, transient stability, out-of-step, neural network, Euclidean norm


[full-paper]


© 1997-2019  FEI STU Bratislava