IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i11p9100-d1164074.html
   My bibliography  Save this article

Review of Power Control Methods for a Variable Average Power Load Model Designed for a Microgrid with Non-Controllable Renewable Energy Sources

Author

Listed:
  • Mantas Zelba

    (Department of Electric Power Systems, Kaunas University of Technology, Studentu Street 48, LT-51367 Kaunas, Lithuania)

  • Tomas Deveikis

    (Department of Electric Power Systems, Kaunas University of Technology, Studentu Street 48, LT-51367 Kaunas, Lithuania)

  • Saulius Gudžius

    (Department of Electric Power Systems, Kaunas University of Technology, Studentu Street 48, LT-51367 Kaunas, Lithuania)

  • Audrius Jonaitis

    (Department of Electric Power Systems, Kaunas University of Technology, Studentu Street 48, LT-51367 Kaunas, Lithuania)

  • Almantas Bandza

    (Department of Electric Power Systems, Kaunas University of Technology, Studentu Street 48, LT-51367 Kaunas, Lithuania)

Abstract

Microgrid systems may employ various combinations of system designs to connect generating units, and the number of different system designs increases exponentially upon adding different brands of inverters to a system. Each of the different microgrid system designs must be set up in a way that it works in balance. An example of an unbalanced microgrid system is given in this paper, with the main issue being the non-predictive excess power, which causes a frequency rise and faulty conditions in the microgrid system. There are many simple options for controlling excess power in a microgrid system; however, none of these options solve the issue permanently while ensuring excess power control without affecting the system’s accumulated energy—the battery state-of-charge (SOC) level. Therefore, there is a need to create a variable average power load (VAPL) device to utilize the excess power at a rate it is changing to avoid a reduction in accumulated energy. The main goal of this study is to review average power control methods for the VAPL device and provide guidance to researchers in selecting the most suitable method for controlling excess power. A key finding of the paper is a suggested optimal average power control method ensuring that the VAPL device is versatile to implement, economically attractive, and not harmful to other devices in a microgrid system.

Suggested Citation

  • Mantas Zelba & Tomas Deveikis & Saulius Gudžius & Audrius Jonaitis & Almantas Bandza, 2023. "Review of Power Control Methods for a Variable Average Power Load Model Designed for a Microgrid with Non-Controllable Renewable Energy Sources," Sustainability, MDPI, vol. 15(11), pages 1-15, June.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:9100-:d:1164074
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/11/9100/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/11/9100/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mantas Zelba & Tomas Deveikis & Justinas Barakauskas & Artūras Baronas & Saulius Gudžius & Audrius Jonaitis & Andreas Giannakis, 2022. "A Grid-Tied Inverter with Renewable Energy Source Integration in an Off-Grid System with a Functional Experimental Prototype," Sustainability, MDPI, vol. 14(20), pages 1-15, October.
    2. Ming Zhang & Yanshuo Liu & Dezhi Li & Xiaoli Cui & Licheng Wang & Liwei Li & Kai Wang, 2023. "Electrochemical Impedance Spectroscopy: A New Chapter in the Fast and Accurate Estimation of the State of Health for Lithium-Ion Batteries," Energies, MDPI, vol. 16(4), pages 1-16, February.
    Full references (including those not matched with items on IDEAS)

    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. Zizhen Cheng & Li Wang & Yumeng Yang, 2023. "A Hybrid Feature Pyramid CNN-LSTM Model with Seasonal Inflection Month Correction for Medium- and Long-Term Power Load Forecasting," Energies, MDPI, vol. 16(7), pages 1-18, March.
    2. Giuliana Vinci & Sabrina Antonia Prencipe & Ada Abbafati & Matteo Filippi, 2022. "Environmental Impact Assessment of an Organic Wine Production in Central Italy: Case Study from Lazio," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    3. Julan Chen & Guangheng Qi & Kai Wang, 2023. "Synergizing Machine Learning and the Aviation Sector in Lithium-Ion Battery Applications: A Review," Energies, MDPI, vol. 16(17), pages 1-22, August.
    4. Shigui Dong & Na Wang & Xueyan Wang & Zihao Lu, 2023. "Extended Recursive Three-Step Filter for Linear Discrete-Time Systems with Dual-Unknown Inputs," Energies, MDPI, vol. 16(15), pages 1-18, July.
    5. Chuanyu Zhang & Chuanxu Cao & Ruiqi Chen & Jiahui Jiang, 2023. "Three-Leg Quasi-Z-Source Inverter with Input Ripple Suppression for Renewable Energy Application," Energies, MDPI, vol. 16(11), pages 1-28, May.
    6. Ming Zhang & Dongfang Yang & Jiaxuan Du & Hanlei Sun & Liwei Li & Licheng Wang & Kai Wang, 2023. "A Review of SOH Prediction of Li-Ion Batteries Based on Data-Driven Algorithms," Energies, MDPI, vol. 16(7), pages 1-28, March.
    7. Gabriele Sordi & Claudio Rabissi & Andrea Casalegno, 2023. "Reliable Thermal-Physical Modeling of Lithium-Ion Batteries: Consistency between High-Frequency Impedance and Ion Transport," Energies, MDPI, vol. 16(12), pages 1-17, June.
    8. Imanol Landa-Medrano & Idoia Urdampilleta & Iker Castrillo & Hans-Jürgen Grande & Iratxe de Meatza & Aitor Eguia-Barrio, 2024. "Making Room for Silicon: Including SiO x in a Graphite-Based Anode Formulation and Harmonization in 1 Ah Cells," Energies, MDPI, vol. 17(7), pages 1-21, March.
    9. Xinwei Sun & Yang Zhang & Yongcheng Zhang & Licheng Wang & Kai Wang, 2023. "Summary of Health-State Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy," Energies, MDPI, vol. 16(15), pages 1-19, July.
    10. Ali Jawad Alrubaie & Mohamed Salem & Khalid Yahya & Mahmoud Mohamed & Mohamad Kamarol, 2023. "A Comprehensive Review of Electric Vehicle Charging Stations with Solar Photovoltaic System Considering Market, Technical Requirements, Network Implications, and Future Challenges," Sustainability, MDPI, vol. 15(10), pages 1-26, May.
    11. Ning Ma & Huaixian Yin & Kai Wang, 2023. "Prediction of the Remaining Useful Life of Supercapacitors at Different Temperatures Based on Improved Long Short-Term Memory," Energies, MDPI, vol. 16(14), pages 1-14, July.
    12. Peng Liu & Cheng Liu & Zhenpo Wang & Qiushi Wang & Jinlei Han & Yapeng Zhou, 2023. "A Data-Driven Comprehensive Battery SOH Evaluation and Prediction Method Based on Improved CRITIC-GRA and Att-BiGRU," Sustainability, MDPI, vol. 15(20), pages 1-15, October.

    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:15:y:2023:i:11:p:9100-:d:1164074. 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.