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Enhancing the performance of cascaded three-level VSC STATCOM by ANN controller with SVPWM integegration

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 5 (2019)

DOI
10.11591/ijece.v9i5.pp3880-3890
ISSN
2722-2578, 2088-8708
Published
2019-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This article presents a cascaded three-level voltage source converter (VSC) based STATCOM employing an artificial neuron network (ANN) controller with a new simple circuit of space vector pulse width modulation (SVPWM) technique. The main aim of utilizing ANN controller and SVPWM technique is to minimize response time (RT) of STATCOM and improve its performance regard to PF amplitude, and total harmonic distortion (THD) of VSC output current during the period of lagging/leading PF loads (inductive/capacitive loads). The performance of STATCOM is tested using MATLAB/SIMULINK in IEEE 3-bus system. The simulation results clearly proved that the STATCOM with intelligent controller is more efficient compared to a conventional controller (PI controller), where ANN enables the voltage and current to be in the same phase rapidly (during 1.5 cycles) with THD less than 5%.

Collaboration network of the authors

40 authors · 112 co-authorship links · 43 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Technology Malaysia
  • Universiti Teknikal Malaysia Melaka
  • Universiti Malaysia Pahang Al-Sultan Abdullah
  • Universitas Ahmad Dahlan
  • Islamic Azad University, Tehran
  • Universiti Malaysia Perlis
  • Universiti Sains Malaysia
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Auzani JidinUniversiti Teknikal Malaysia Melaka34
Nik Rumzi Nik IdrisUniversity of Technology Malaysia18
Mohammad JannatiUniversity of Technology Malaysia16
Nik Rumzi Nik IdrisAffiliation unknown16
Mohd Hatta JopriUniversiti Teknikal Malaysia Melaka15
Ibrahim AlhamrouniAffiliation unknown15
Mohd Junaidi Abdul AzizUniversity of Technology Malaysia10
Mustafa ManapUniversiti Teknikal Malaysia Melaka10
Kasrul Abdul KarimAffiliation unknown9
Lina HandayaniUniversitas Ahmad Dahlan8
Mahmoud ZadehbagheriIslamic Azad University, Tehran8
Muhammad AdoUniversity of Technology Malaysia8
Abdul Rahim AbdullahUniversiti Teknikal Malaysia Melaka6
Mochammad FactaDiponegoro University6
Mohammad Javad KianiIslamic Azad University, Tehran5
Shahreen KasimAffiliation unknown5
Watra ArsadiandoAffiliation unknown5
Mohammad Faridun Naim TajuddinUniversiti Malaysia Perlis5
Mohd Junaidi Abdul AzizAffiliation unknown5
Imam Much Ibnu SubrotoSultan Agung Islamic University4
M. Rahimi YusoffUniversiti Teknikal Malaysia Melaka4
Hendril Satrian PurnamaAffiliation unknown4
Anggit PamungkasAffiliation unknown4
Vahdat NazerianUniversity of Mazandaran4
Muhammad Zaid AihsanUniversiti Malaysia Perlis4
Chibuike Peter OhanuUniversity of Nigeria4
Tri WahonoAffiliation unknown4
Rahim IldarabadiAffiliation unknown4
Azralmukmin AzmiAffiliation unknown4
Shahrin Md AyobAffiliation unknown4
Siti Azura Ahmad TarusanAffiliation unknown4
Aiman Zakwan JidinAffiliation unknown4
Deris StiawanSriwijaya University3

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 Oct 2026, last seen 8 Nov 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>Enhancing the performance of cascaded three-level VSC STATCOM by ANN controller with SVPWM integegration</dc:title><dc:creator>Almelian, Mohamad Milood</dc:creator><dc:creator>Mohd, Izzeldin. I.</dc:creator><dc:creator>Ahmad, Abu Zaharin</dc:creator><dc:creator>Salem, Mohamed</dc:creator><dc:creator>Omran, Mohamed A.</dc:creator><dc:creator>Jusoh, Awang</dc:creator><dc:creator>Sutikno, Tole</dc:creator><dc:description>&lt;jats:p&gt;This article presents a cascaded three-level voltage source converter (VSC) based STATCOM employing an artificial neuron network (ANN) controller with a new simple circuit of space vector pulse width modulation (SVPWM) technique. The main aim of utilizing ANN controller and SVPWM technique is to minimize response time (RT) of STATCOM and improve its performance regard to PF amplitude, and total harmonic distortion (THD) of VSC output current during the period of lagging/leading PF loads (inductive/capacitive loads). The performance of STATCOM is tested using MATLAB/SIMULINK in IEEE 3-bus system. The simulation results clearly proved that the STATCOM with intelligent controller is more efficient compared to a conventional controller (PI controller), where ANN enables the voltage and current to be in the same phase rapidly (during 1.5 cycles) with THD less than 5%.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2019-10-01</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.v9i5.pp3880-3890</dc:identifier><dc:identifier>10.11591/ijece.v9i5.pp3880-3890</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 9 No 5 (2019); 3880</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/20236/13031</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>