Journal
ELECTRIC POWER SYSTEMS RESEARCH
Volume 76, Issue 12, Pages 1047-1054Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2005.12.026
Keywords
feature selection; neural networks; transient stability analysis
Categories
Ask authors/readers for more resources
This paper describes an approach where an artificial neural network is used to predict the stability status of the power system. This efficient and robust approach combines the advantages of the time-domain integration schemes and artificial neural network for on-line transient stability assessment of the power system. The transient stability index has been obtained by the extended equal area criterion method and is used as an output of the neural network. Two feature selection techniques have been used to identify the input variables best suitable for training. The proposed technique predicts the transient stability index correctly, without any false alarm. In addition, the transient stability index as an output of the neural network helps to implement possible control actions. The results obtained demonstrate the potential for neural network to be a part of any on-line dynamic security assessment tool. (c) 2006 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available