CRITICAL TRAJECTORY - EXTREME LEARNING MACHINE TECHNIQUE FOR COMPUTING CRITICAL CLEARING TIME

  • Irrine Budi Sulistiawati Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember ITS, Surabaya Indonesia
  • Ardyono Priyadi Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya
  • Adi Soepriyanto Department of Electrical Engineering, Institut Teknologi Nasional Malang

Abstract

Electric power system is called reliable if the system is able to provide power
supply without interrupted. However, in large systems changing on the system or
disturbance may affect the power supply. Critical clearing time is the time for
deciding the system is a stable or an unstable condition. Critical clearing time has
also relationship with setting relay protection to keep the system in the stable
condition. Prediction of critical real time for online assessment is expected to be
used for preventive action system. That’s why critical clearing time still an
interesting topic to be investigated.This paper calculating time of Extreme
Learning Machine to predict critical clearing tim on system. Before predicted by
Extreme Learning Machine, critical clearing time calculated using numerical
calculation critical trajectory method with load changing and different fault
occuring. Tested by Java-Bali 500 kv 54 machine 25 bus give result that Extreme
learning machine is able to perform faster prediction of neural network.

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Published
2015-07-28
How to Cite
SULISTIAWATI, Irrine Budi; PRIYADI, Ardyono; SOEPRIYANTO, Adi. CRITICAL TRAJECTORY - EXTREME LEARNING MACHINE TECHNIQUE FOR COMPUTING CRITICAL CLEARING TIME. Jurnal Ilmiah Kursor, [S.l.], v. 8, n. 1, july 2015. ISSN 2301-6914. Available at: <http://kursorjournal.org/index.php/kursor/article/view/73>. Date accessed: 30 nov. 2021. doi: https://doi.org/10.28961/kursor.v8i1.73.
Section
Articles

Keywords

Critical Clearing Time; Neural Network; Extreme Learning Machine