NDLI: Online Learning Neural Network based PSS with Adaptive Training Parameters

Content Provider	IEEE Xplore Digital Library
Author	Tulpule, P. Feliachi, A.
Copyright Year	2007
Description	Author affiliation: Adv. Power & Electr. Res. Center (APERC), West Virginia Univ., Morgantown, WV (Tulpule, P.; Feliachi, A.)
Abstract	This paper provides a new method to improve power system stability using recurrent neural network with adaptive training parameters. Power system generators are equipped with automatic voltage regulator, power system stabilizer, and governor to control and stabilize the system. The controller parameters are tuned using mathematical methods, or heuristic search methods such as genetic algorithm. Therefore these control parameters are often fixed and are set for particular system configurations or operating points. Artificial neural network can be tuned for changing system conditions and thus provide better control. Artificial neural network is used in this paper in parallel with the existing PSS to effectively damp the oscillations and improve overall system performance. Online training method is employed with multilayer recurrent neural network. Training is based on back propagation with adaptive training parameters. This controller is tested on two different systems and simulation results are presented to illustrate the proposed approach.
Starting Page	1
Ending Page	5
File Size	404595
Page Count	5
File Format	PDF
ISBN	142441296X
ISSN	19325517
DOI	10.1109/PES.2007.386143
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Power system stability Control systems Recurrent neural networks Power system control Power systems Automatic control Artificial neural networks Adaptive systems Power generation
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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