Wind generator stability enhancement by using an adaptive artificial neural network-controlled superconducting magnetic energy storage

Hasanien, H.; Ali, S.; Muyeen, S.M.

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Access Status

Open access

Authors

Hasanien, H.

Ali, S.

Muyeen, S.M.

Date

2012

Type

Conference Paper

Metadata

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Citation

Hasanien, H. and Ali, S. and Muyeen, S.M. 2012. Wind generator stability enhancement by using an adaptive artificial neural network-controlled superconducting magnetic energy storage, in Proceedings of the 15th International Conference on Electrical Machines and Systems (ICEMS), Oct 21-24 2012, Sapporo, Japan: IEEE.

Source Title

ICEMS 2012 - Proceedings: 15th International Conference on Electrical Machines and Systems

ISBN

9784886860774

School

Department of Electrical and Computer Engineering

Remarks

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

URI

http://hdl.handle.net/20.500.11937/7614

Collection

Curtin Research Publications

Abstract

This paper presents a novel adaptive artificial neural network (ANN)-controlled superconducting magnetic energy storage (SMES) to enhance the transient stability of a grid-connected wind generator system. The control strategy of the SMES unit is developed based on cascaded control scheme of a voltage source converter and a two-quadrant DC-DC chopper using insulated gate bipolar transistors (IGBTs). The proposed controller is used to control the duty cycle of the DC-DC chopper. Detailed modeling and control strategies of the system are presented. The effectiveness of the proposed adaptive ANN-controlled SMES is then compared with that of a conventional proportional-integral (PI)-controlled SMES. The validity of the proposed system is verified with the simulation results which are performed using the standard dynamic power system simulator PSCAD/EMTDC.