Cart (Loading....) | Create Account
Close category search window

A novel feature selection and extraction method for neural network based transfer capability assessment of power systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
3 Author(s)
Othman, M.M. ; Fac. of Electr. Eng., MARA Univ. of Technol., Malaysia ; Mohamed, A. ; Hussain, A.

A new feature selection and extraction method is presented in this paper for the neural network (NN) based available transfer capability assessment in the deregulated power system. The objective of feature selection and extraction is to speed up the NN training process and to achieve a more accurate NN results. The proposed method is known as the SDFT method in which it is a combination of the sensitivity and discrete Fourier transform methods. The sensitivity analysis is first used in selecting the input features and then followed by the discrete Fourier transform (DFT) method for extracting NN input features. The hypothesis set of pre-selected data performed by the sensitivity method only offers no improvement in the NN training performance in such cases where many features are highly correlated. Thus, the DFT method is considered so as to extract the pre-selected data to a set of meaningful extracted data. To illustrate the effectiveness of the proposed method, a comparative study of the SDFT, DFT and sensitivity methods is made so as to investigate the effectiveness of the methods in extracting and selecting the NN features. In this study, the NN based available transfer capability assessment has been performed on the Malaysian power system.

Published in:

Research and Development, 2003. SCORED 2003. Proceedings. Student Conference on

Date of Conference:

25-26 Aug. 2003

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.