IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v187y2019ics0360544219315531.html
   My bibliography  Save this article

New intelligent control strategy by robust neural network algorithm for real time detection of an optimized maximum power tracking control in photovoltaic systems

Author

Listed:
  • Issaadi, Salim
  • Issaadi, Wassila
  • Khireddine, Abdelkrim

Abstract

To increase the power output of a PV module or a field of PV modules, an electronic controller is incorporated between the PV generator and the load, whose role and main objective is the continuous monitoring of the maximum power point of the PV generator commonly known as MPPT (Maximum Power Point Tracking) and this in general per action on a DC-DC conversion device.

Suggested Citation

  • Issaadi, Salim & Issaadi, Wassila & Khireddine, Abdelkrim, 2019. "New intelligent control strategy by robust neural network algorithm for real time detection of an optimized maximum power tracking control in photovoltaic systems," Energy, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:energy:v:187:y:2019:i:c:s0360544219315531
    DOI: 10.1016/j.energy.2019.115881
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219315531
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.115881?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Abdelmalek, Samir & Dali, Ali & Bakdi, Azzeddine & Bettayeb, Maamar, 2020. "Design and experimental implementation of a new robust observer-based nonlinear controller for DC-DC buck converters," Energy, Elsevier, vol. 213(C).
    2. Zhou, Xiaoyan & Zhang, Ying & Ma, Xun & Li, Guoliang & Wang, Yunfeng & Hu, Chengzhi & Liang, Junyu & Li, Ming, 2022. "Performance characteristics of photovoltaic cold storage under composite control of maximum power tracking and constant voltage per frequency," Applied Energy, Elsevier, vol. 305(C).
    3. Aatabe, Mohamed & El Guezar, Fatima & Vargas, Alessandro N. & Bouzahir, Hassane, 2021. "A novel stochastic maximum power point tracking control for off-grid standalone photovoltaic systems with unpredictable load demand," Energy, Elsevier, vol. 235(C).
    4. Waleed Al Abri & Rashid Al Abri & Hassan Yousef & Amer Al-Hinai, 2021. "A Simple Method for Detecting Partial Shading in PV Systems," Energies, MDPI, vol. 14(16), pages 1-12, August.

    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:eee:energy:v:187:y:2019:i:c:s0360544219315531. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.