IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i11p4100-d830538.html
   My bibliography  Save this article

Predictive Control of PV/Battery System under Load and Environmental Uncertainty

Author

Listed:
  • Salem Batiyah

    (Department of Electrical and Electronics Engineering Technology, Yanbu Industrial College, Yanbu Industrial, Almadina 46452, Saudi Arabia
    Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762, USA
    These authors contributed equally to this work.)

  • Roshan Sharma

    (Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762, USA
    Smart Grid and Emerging Technology, Commonwealth Edison Company (ComEd), Chicago, IL 60181, USA
    These authors contributed equally to this work.)

  • Sherif Abdelwahed

    (Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA)

  • Waleed Alhosaini

    (Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia)

  • Obaid Aldosari

    (Department of Electrical Engineering, Prince Sattam Bin Abdulaziz University, Wadi Addawaser, Najd 11991, Saudi Arabia)

Abstract

The standalone microgrids with renewable energy resources (RERs) such as a photovoltaic (PV) system and fast changing loads face major challenges in terms of reliability and power management due to a lack of inherent inertial support from RERs and their intermittent nature. Thus, energy storage technologies such as battery energy storage (BES) are typically used to mitigate the power fluctuations and maintain a power balance in the system. This paper presents a model predictive control (MPC) based power management strategy (PMS) for such standalone PV/battery systems. The proposed method is equipped with an autoregressive integrated moving average (ARIMA) prediction method to forecast the load and environmental parameters. The proposed controller has the capabilities of (1) effective power management, (2) minimization of transients during disturbances, and (3) automatic switching of the operation of the PV between the maximum power point tracking (MPPT) mode and power-curtailed mode that prevents the overcharging of the battery and at the same time maximize the PV utilization. The effectiveness of the proposed method has been verified through a comprehensive simulation-based analysis.

Suggested Citation

  • Salem Batiyah & Roshan Sharma & Sherif Abdelwahed & Waleed Alhosaini & Obaid Aldosari, 2022. "Predictive Control of PV/Battery System under Load and Environmental Uncertainty," Energies, MDPI, vol. 15(11), pages 1-16, June.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:4100-:d:830538
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/11/4100/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/11/4100/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Roshan Sharma & Masoud Karimi-Ghartemani, 2020. "Addressing Abrupt PV Disturbances, and Mitigating Net Load Profile’s Ramp and Peak Demands, Using Distributed Storage Devices," Energies, MDPI, vol. 13(5), pages 1-21, February.
    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. Horrillo-Quintero, Pablo & García-Triviño, Pablo & Sarrias-Mena, Raúl & García-Vázquez, Carlos A. & Fernández-Ramírez, Luis M., 2023. "Model predictive control of a microgrid with energy-stored quasi-Z-source cascaded H-bridge multilevel inverter and PV systems," Applied Energy, Elsevier, vol. 346(C).

    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. Marco Pasetti, 2021. "Assessing the Effectiveness of the Energy Storage Rule-Based Control in Reducing the Power Flow Uncertainties Caused by Distributed Photovoltaic Systems," Energies, MDPI, vol. 14(8), pages 1-25, April.
    2. Handrea Bernando Tambunan & Dzikri Firmansyah Hakam & Iswan Prahastono & Anita Pharmatrisanti & Andreas Putro Purnomoadi & Siti Aisyah & Yonny Wicaksono & I Gede Ryan Sandy, 2020. "The Challenges and Opportunities of Renewable Energy Source (RES) Penetration in Indonesia: Case Study of Java-Bali Power System," Energies, MDPI, vol. 13(22), pages 1-22, November.

    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:15:y:2022:i:11:p:4100-:d:830538. 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.