Show simple item record

dc.contributor.authorMuyeen, S.M.
dc.contributor.authorHasanien, H.
dc.contributor.authorAl-Durra, A.
dc.date.accessioned2017-01-30T10:33:15Z
dc.date.available2017-01-30T10:33:15Z
dc.date.created2016-10-05T19:30:22Z
dc.date.issued2014
dc.identifier.citationMuyeen, S.M. and Hasanien, H. and Al-Durra, A. 2014. Transient stability enhancement of wind farms connected to a multi-machine power system by using an adaptive ANN-controlled SMES. Energy Conversion and Management. 78: pp. 412-420.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/3676
dc.identifier.doi10.1016/j.enconman.2013.10.039
dc.description.abstract

This paper presents a novel adaptive artificial neural network (ANN)-controlled superconducting magnetic energy storage (SMES) system to enhance the transient stability of wind farms connected to a multi-machine power system during network disturbances. The control strategy of SMES depends mainly on a sinusoidal pulse width modulation (PWM) voltage source converter (VSC) and an adaptive ANN-controlled DC-DC converter using insulated gate bipolar transistors (IGBTs). The effectiveness of the proposed adaptive ANN-controlled SMES is then compared with that of proportional-integral (PI)-controlled SMES optimized by response surface methodology and genetic algorithm (RSM-GA) considering both of symmetrical and unsymmetrical faults. For realistic responses, real wind speed data and two-mass drive train model of wind turbine generator system is considered in the analyses. The validity of the proposed system is verified by the simulation results which are performed using the laboratory standard dynamic power system simulator PSCAD/EMTDC. Notably, the proposed adaptive ANN-controlled SMES enhances the transient stability of wind farms connected to a multi-machine power system.

dc.publisherElsevier
dc.titleTransient stability enhancement of wind farms connected to a multi-machine power system by using an adaptive ANN-controlled SMES
dc.typeJournal Article
dcterms.source.volume78
dcterms.source.startPage412
dcterms.source.endPage420
dcterms.source.issn0196-8904
dcterms.source.titleEnergy Conversion and Management
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusOpen access


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record