IDEAS home Printed from https://ideas.repec.org/a/epw/ejeng0/v7y2022i5id62720.html

Real-Time Harmonic Optimization in Multilevel Inverter Using Artificial Neural Network (ANN)

Author

Listed:
  • Ismail Adeyemi Adeyemo

    (Ladoke Akintola University of Technology, Nigeria.)

  • Olabode Moses Ola

    (Bowen University, Nigeria.)

  • Demilade Olujide Babajide

    (Ikeja Electricity Distribution Company, Nigeria.)

Abstract

Multilevel inverters (MLIs) are increasingly used in real time applications. Among several pulse width modulation (PMW) techniques currently deployed for the control of MLIs, selective harmonic elimination PWM (SHEPWM) technique arguably gives the best performance due to its direct harmonic mitigation capability. However, real time application of SHEPWM technique is presently infeasible due to the heavy computational cost involved in solving the transcendental nonlinear equations known as selective harmonic elimination (SHE) equations, which characterize the harmonics that are selected for elimination or mitigation. This paper presents a twostage approach to the online generation of switching angles that mitigate selected lower-order harmonics in multilevel inverters. The first stage involves an offline solution of SHE equations using ant colony optimisation (ACO). In the second stage, ACO computed results are used to train an artificial neural network (ANN) predictive model. The results obtained from the simulation of the proposed method in MATLAB/SIMULINK environment show that the method is highly efficient and accurate.

Suggested Citation

  • Ismail Adeyemi Adeyemo & Olabode Moses Ola & Demilade Olujide Babajide, 2022. "Real-Time Harmonic Optimization in Multilevel Inverter Using Artificial Neural Network (ANN)," European Journal of Engineering and Technology Research, European Open Science, vol. 7(5), pages 12-17, September.
    • Handle: RePEc:epw:ejeng0:v:7:y:2022:i:5:id:62720
    DOI: 10.24018/ejeng.2022.7.5.2720
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejeng/article/view/62720
    File Function: Abstract page
    Download Restriction: no
    File URL: https://eu-opensci.org/index.php/ejeng/article/download/62720/12851
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.24018/ejeng.2022.7.5.2720?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:ejeng0:v:7:y:2022:i:5:id:62720. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejeng .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.