NDLI: Artificial neural network PI controlled superconducting magnetic energy storage, SMES for augmentation of power systems stability

Content Provider	IEEE Xplore Digital Library
Author	Hemeida, A.M.
Copyright Year	2008
Description	Author affiliation: E.E. Dept, South Valley Univ., Aswan (Hemeida, A.M.)
Abstract	This paper aimed to apply artificial neural network proportional, plus integral, PI controlled superconducting magnetic energy storage SMES to improve the transient stability of power systems. The PI controller parameters is firstly determined based on eigenvalue assignment approach. The artificial neural network, ANN is used to determine the optimum gains of the PI controller at different load values. The ANN is trained off line using Matlab software to obtain the optimum parameters of the PI controller. The speed deviation, Deltaomega and load angle deviation Deltadelta are used as input signal to the PI controller. The studied power system consists of single machine connected to an infinite bus via double transmission lines. The studied system is modeled by a set of nonlinear differential and algebraic equations and simulated by the Matlab software. The simulation results indicates the effect of the proposed ANN PI controlled SMES.
Starting Page	187
Ending Page	191
File Size	460780
Page Count	5
File Format	PDF
ISBN	9781424419333
DOI	10.1109/MEPCON.2008.4562332
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-12
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	PI controller - Superconducting magnetic energy storage Power system transients Artificial neural networks Power system stability SMES - Power systems stability Control systems Power system modeling Artificial neural network - Proportional plus integral Proportional control Power system simulation Pi control Samarium Superconducting magnetic energy storage
Content Type	Text
Resource Type	Article

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