IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i2p929-d724846.html
   My bibliography  Save this article

Aquila Optimization Based Harmonic Elimination in a Modified H-Bridge Inverter

Author

Listed:
  • Md Reyaz Hussan

    (Department of Electrical Engineering, Zakir Husain College of Engineering and Technology (ZHCET), Aligarh Muslim University, Aligarh 202002, India)

  • Mohammad Irfan Sarwar

    (Grenoble Institute of Technology—Ense3, Université Grenoble Alpes, 38400 Grenoble, France)

  • Adil Sarwar

    (Department of Electrical Engineering, Zakir Husain College of Engineering and Technology (ZHCET), Aligarh Muslim University, Aligarh 202002, India)

  • Mohd Tariq

    (Department of Electrical Engineering, Zakir Husain College of Engineering and Technology (ZHCET), Aligarh Muslim University, Aligarh 202002, India)

  • Shafiq Ahmad

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Adamali Shah Noor Mohamed

    (Electrical Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Irfan A. Khan

    (Department of Marine Engineering Technology in a Joint Appointment with the Department of Electrical and Computer Engineering, Texas A & M University, Galveston, TX 77553, USA)

  • Mohammad Muktafi Ali Khan

    (Department of Electrical Engineering, Zakir Husain College of Engineering and Technology (ZHCET), Aligarh Muslim University, Aligarh 202002, India)

Abstract

Multilevel inverters (MLIs) are capable of producing high-quality output voltage and handling large amounts of power. This reduces the size of the filter while also simplifying the circuitry. As a result, they have a wide range of applications in industries, particularly in smart grids. The input voltage boosting feature is required to use the MLI with renewable energy. Moreover, many components are required to get higher output voltage levels that add weight and cost to the circuit. Numerous MLI topologies have been identified to minimize the losses, device count, and device ratings. A seven-level modified H-bridge inverter with a reduced component count, and reduced THD is presented in this paper. Two DC sources with six IGBTs have been used to generate a seven-level output voltage, and the Aquila Optimizer (AO) has been implemented to get the regulated output. MATLAB/Simulink environment has been used for designing the simulation model. Furthermore, the simulation result has been validated in the laboratory on a hardware setup using the DSP-TMS320F28335 Launchpad. With the reduced number of switching devices as well as the dc supply, the size of the inverter is compacted and becomes more economical.

Suggested Citation

  • Md Reyaz Hussan & Mohammad Irfan Sarwar & Adil Sarwar & Mohd Tariq & Shafiq Ahmad & Adamali Shah Noor Mohamed & Irfan A. Khan & Mohammad Muktafi Ali Khan, 2022. "Aquila Optimization Based Harmonic Elimination in a Modified H-Bridge Inverter," Sustainability, MDPI, vol. 14(2), pages 1-16, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:2:p:929-:d:724846
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/2/929/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/2/929/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ahmed A. Ewees & Fatma H. Ismail & Rania M. Ghoniem & Marwa A. Gaheen, 2022. "Enhanced Marine Predators Algorithm for Solving Global Optimization and Feature Selection Problems," Mathematics, MDPI, vol. 10(21), pages 1-21, November.
    2. Sushmita Kujur & Hari Mohan Dubey & Surender Reddy Salkuti, 2023. "Demand Response Management of a Residential Microgrid Using Chaotic Aquila Optimization," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    3. Mohammad H. Nadimi-Shahraki & Shokooh Taghian & Seyedali Mirjalili & Laith Abualigah, 2022. "Binary Aquila Optimizer for Selecting Effective Features from Medical Data: A COVID-19 Case Study," Mathematics, MDPI, vol. 10(11), pages 1-24, June.
    4. Khizer Mehmood & Naveed Ishtiaq Chaudhary & Zeshan Aslam Khan & Muhammad Asif Zahoor Raja & Khalid Mehmood Cheema & Ahmad H. Milyani, 2022. "Design of Aquila Optimization Heuristic for Identification of Control Autoregressive Systems," Mathematics, MDPI, vol. 10(10), pages 1-23, May.
    5. Sukanta Roy & Anjan Debnath & Mohd Tariq & Milad Behnamfar & Arif Sarwat, 2023. "Characterizing Current THD’s Dependency on Solar Irradiance and Supraharmonics Profiling for a Grid-Tied Photovoltaic Power Plant," Sustainability, MDPI, vol. 15(2), pages 1-22, January.

    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:gam:jsusta:v:14:y:2022:i:2:p:929-:d:724846. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.