IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i10p4240-d1152712.html
   My bibliography  Save this article

Enhanced Power Quality in Single-Phase Grid-Connected Photovoltaic Systems: An Experimental Study

Author

Listed:
  • Abdellah Benabdelkader

    (Smart Grids & Renewable Energies Laboratory, Faculty of Technology, University of Tahri Mohammed Bechar, Bechar 08000, Algeria)

  • Azeddine Draou

    (Department of Electrical Engineering, College of Engineering, Islamic University of Madinah, Madinah 42351, Saudi Arabia)

  • Abdulrahman AlKassem

    (Department of Electrical Engineering, College of Engineering, Islamic University of Madinah, Madinah 42351, Saudi Arabia)

  • Toufik Toumi

    (Smart Grids & Renewable Energies Laboratory, Faculty of Technology, University of Tahri Mohammed Bechar, Bechar 08000, Algeria)

  • Mouloud Denai

    (School of Physics, Engineering & Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK)

  • Othmane Abdelkhalek

    (Smart Grids & Renewable Energies Laboratory, Faculty of Technology, University of Tahri Mohammed Bechar, Bechar 08000, Algeria)

  • Marwa Ben Slimene

    (Department of Computer Science and Engineering, College of Computer Science and Engineering, University of Ha’il, Ha’il 55436, Saudi Arabia
    SIME Laboratory, ENSIT, University of Tunis, 05 Ave Taha Hussein, Tunis 1008, Tunisia)

Abstract

The main aim of the research work presented in this paper consists of proposing an effective control scheme for a grid-connected single-phase photovoltaic (PV) system to enhance not only the power quality at the point of common coupling (PCC) but also to operate with a maximum power point tracking (MPPT) controller. Moreover, an orthogonal signal generator (OSG) module for effective grid synchronization, a current reference generation controller, and a PWM generating block have also been designed and included in this paper. The proposed control strategy allows the MPPT controller to switch to faulty mode and maintains the voltage according to network requirements using an adaptive neuro-fuzzy inference system (ANFIS)-based control whenever a fault occurs at the PCC. The performance of the analyzed control strategy, which is based on the static compensation of the DC-link voltage fluctuations in a grid-connected inverter powered by PV, is further explored through simulations in MATLAB, and the results are included in this paper. Moreover, the control scheme is implemented experimentally using a dSPACE DS 1104 control board and then assessed on a small laboratory-scale single-phase PV system that is subjected to some fault scenarios. The simulation and experimental results have shown improved power quality and robustness against grid fluctuations, resulting in better dynamic performance.

Suggested Citation

  • Abdellah Benabdelkader & Azeddine Draou & Abdulrahman AlKassem & Toufik Toumi & Mouloud Denai & Othmane Abdelkhalek & Marwa Ben Slimene, 2023. "Enhanced Power Quality in Single-Phase Grid-Connected Photovoltaic Systems: An Experimental Study," Energies, MDPI, vol. 16(10), pages 1-23, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:4240-:d:1152712
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/10/4240/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/10/4240/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Amini Toosi, Hashem & Del Pero, Claudio & Leonforte, Fabrizio & Lavagna, Monica & Aste, Niccolò, 2023. "Machine learning for performance prediction in smart buildings: Photovoltaic self-consumption and life cycle cost optimization," Applied Energy, Elsevier, vol. 334(C).
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Gerardo de J. Martínez-Figueroa & Santiago Bogarra & Felipe Córcoles, 2023. "Smart Switching in Single-Phase Grid-Connected Photovoltaic Power Systems for Inrush Current Elimination," Energies, MDPI, vol. 16(20), pages 1-19, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi, Jun & Qi, ZhongLi & Li, XiangChengZhen & Liu, Hong & Zhou, Wei, 2024. "Spatial correlation-based machine learning framework for evaluating shale gas production potential: A case study in southern Sichuan Basin, China," Applied Energy, Elsevier, vol. 357(C).
    2. Dongli Tan & Yao Wu & Zhiqing Zhang & Yue Jiao & Lingchao Zeng & Yujun Meng, 2023. "Assessing the Life Cycle Sustainability of Solar Energy Production Systems: A Toolkit Review in the Context of Ensuring Environmental Performance Improvements," Sustainability, MDPI, vol. 15(15), pages 1-37, July.
    3. He, Zhiyue & Tang, Yong & He, Youwei & Qin, Jiazheng & Hu, Shilai & Yan, Bicheng & Tang, Liangrui & Sepehrnoori, Kamy & Rui, Zhenhua, 2024. "Wellbore salt-deposition risk prediction of underground gas storage combining numerical modeling and machine learning methodology," Energy, Elsevier, vol. 305(C).
    4. Ren, Haoshan & Gao, Dian-ce & Ma, Zhenjun & Zhang, Sheng & Sun, Yongjun, 2024. "Data-driven surrogate optimization for deploying heterogeneous multi-energy storage to improve demand response performance at building cluster level," Applied Energy, Elsevier, vol. 356(C).

    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:jeners:v:16:y:2023:i:10:p:4240-:d:1152712. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.