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Control action based on steady-state security assessment using an artificial neural network


Citation

Al-Masri, Ahmed Naufal A. and Ab Kadir, Mohd Zainal Abidin and Hizam, Hashim and Mariun, Norman and Yusof, Sallehhudin (2010) Control action based on steady-state security assessment using an artificial neural network. In: 2010 IEEE International Conference on Power and Energy (PECon 2010), 29 Nov.-1 Dec. 2010, Kuala Lumpur, Malaysia. (pp. 706-711).

Abstract

In this paper, the application of an Artificial Neural Network (ANN) for remedial action of a power system is presented. The aims of this study are to find the significant control action that alleviates a bus voltage violation of a power system and to demonstrate the ability of a neural network in terms of evaluating the generation re-dispatch and load shedding amounts. The remedial action is based on a steady-state security assessment of the power system. The proposed algorithm has been successfully tested on a 9-bus test system. The results are compared with other conventional methods and it reveals that an ANN can provide the required amount of generation re-dispatch and load shedding accurately and instantaneously compared to other methods. On average, remedial actions were shown to have a positive effect for reducing the number of bus voltage violations and improving system security.


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1109/PECON.2010.5697671
Publisher: IEEE
Keywords: Steady-state security assessment; Artificial neural network; Back-propagation; Remedial control action; Contingency analysis
Depositing User: Nabilah Mustapa
Date Deposited: 12 Jun 2019 02:06
Last Modified: 12 Jun 2019 02:06
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/PECON.2010.5697671
URI: http://psasir.upm.edu.my/id/eprint/68936
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