Application of artificial neural network for automatic contingency analysis in power security assessment / Ismail Musirin and Titik Khawa Abdul Rahman

Musirin, Ismail and Abdul Rahman, Titik Khawa (2006) Application of artificial neural network for automatic contingency analysis in power security assessment / Ismail Musirin and Titik Khawa Abdul Rahman. Scientific Research Journal, 3 (1). pp. 11-25. ISSN 1675-7009

Official URL: https://srj.uitm.edu.my/

Abstract

Several incidents that occurred around the world involving power failure caused by unscheduled line outages were identified as one of the main contributors to power failure and cascading blackout in electric power environment. With the advancement of computer technologies, artificial
intelligence (AI) has been widely accepted as one method that can be applied to predict the occurrence of unscheduled disturbance. This paper presents the development of automatic contingency analysis and ranking algorithm for the application in the Artificial Neural Network (ANN). The ANN is developed in order to predict the post-outage severity index from a set of preoutage data set. Data were generated using the newly developed automatic
contingency analysis and ranking (ACAR) algorithm. Tests were conducted on the 24-bus IEEE Reliability Test Systems. Results showed that the developed technique is feasible to be implemented practically and an agreement was achieved in the results obtained from the tests. The developed ACAR can be utilised for further testing and implementation in other IEEE RTS test systems particularly in the system, which required fast computation time. On the other hand, the developed ANN can be used for predicting the post-outage severity index and hence system stability can be evaluated.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Musirin, Ismail
UNSPECIFIED
Abdul Rahman, Titik Khawa
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science)
Divisions:
Journal or Publication Title: Scientific Research Journal
UiTM Journal Collections: UiTM Journal > Scientific Research Journal (SRJ)
ISSN: 1675-7009
Volume: 3
Number: 1
Page Range: pp. 11-25
Keywords: Artificial Neural Network, contingency analysis and ranking, voltage stability
Date: 2006
URI: https://ir.uitm.edu.my/id/eprint/12808
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12808

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