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PSO-backstepping controller of a grid connected DFIG based wind turbine

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 1 (2020)

DOI
10.11591/ijece.v10i1.pp856-867
ISSN
2088-8708, 2088-8708
Published
2020-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

The paper demonstrates the feasibility of an optimal backstepping controller for doubly fed induction generator based wind turbine (DFIG). The main purpose is the extract of maximum energy and the control of active and reactive power exchanged between the generator and electrical grid in presence of uncertainty. The maximum energy is obtained by applying an algorithm based on artificial bee colony approach. Particle swarm optimization is used to select optimal value of backstepping’s parameters. The simulation is carried out on 2.4 MW DFIG based wind turbine system. The optimized performance of the proposed control technique under uncertainty parameters is established by simulation results.

Collaboration network of the authors

19 authors · 45 co-authorship links

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  • University of Hassan II Casablanca
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Abdennaceur BaghdadUniversity of Hassan II Casablanca7
Ilham El MourabitUniversity of Hassan II Casablanca4
Abdelhakim BalloukUniversity of Hassan II Casablanca3
Redouane MajdoulAffiliation unknown2
Ayoub AbidaUniversity of Hassan II Casablanca2
Btissam BoustaniUniversity of Hassan II Casablanca2
Imane AssiniUniversity of Hassan II Casablanca2
Jihane OuchrifUniversity of Hassan II Casablanca2
Abdelhadi Eloudrhiri HassaniUniversity of Hassan II Casablanca2
Hicham QaboucheUniversity of Hassan II Casablanca2
Abir ZaidiUniversity of Hassan II Casablanca1
Nourdine HerbazUniversity of Hassan II Casablanca1
Hassan El IdrissiUniversity of Hassan II Casablanca1
Hamza SabirUniversity of Hassan II Casablanca1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>PSO-backstepping controller of a grid connected DFIG based wind turbine</dc:title><dc:creator>Hassan, Salmi</dc:creator><dc:creator>Abdelmajid, Badri</dc:creator><dc:creator>Mourad, Zegrari</dc:creator><dc:creator>Aicha, Sahel</dc:creator><dc:creator>Abdenaceur, Baghdad</dc:creator><dc:description>&lt;jats:p&gt;The paper demonstrates the feasibility of an optimal backstepping controller for doubly fed induction generator based wind turbine (DFIG). The main purpose is the extract of maximum energy and the control of active and reactive power exchanged between the generator and electrical grid in presence of uncertainty. The maximum energy is obtained by applying an algorithm based on artificial bee colony approach. Particle swarm optimization is used to select optimal value of backstepping’s parameters. The simulation is carried out on 2.4 MW DFIG based wind turbine system. The optimized performance of the proposed control technique under uncertainty parameters is established by simulation results.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v10i1.pp856-867</dc:identifier><dc:identifier>10.11591/ijece.v10i1.pp856-867</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 1 (2020); 856</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/18399/pdf</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>