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Fuzzy Logic Control of a Battery Energy Storage System for Stability Improvement in an Islanded Microgrid

Author

Listed:
  • Naowarat Tephiruk

    (Department of Electrical Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand
    These authors contributed equally to this work.)

  • Weerawoot Kanokbannakorn

    (Department of Electrical Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand)

  • Thongchart Kerdphol

    (Department of Electrical and Electronic Engineering, Kyushu Institute of Technology, Kitakyushu, Fukuoka 804-8550, Japan)

  • Yasunori Mitani

    (Department of Electrical and Electronic Engineering, Kyushu Institute of Technology, Kitakyushu, Fukuoka 804-8550, Japan)

  • Komsan Hongesombut

    (Department of Electrical Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand
    These authors contributed equally to this work.)

Abstract

In this study, the active and reactive power control of a battery energy storage system (BESS) using fuzzy logic control to maintain the voltage and frequency stability of the islanded Mae Sariang microgrid is presented. The main scope of the presented study is to cogitate the effectiveness of the BESS controller in view of fluctuations of frequency/voltage subjected to a disturbance occurring in the islanded microgrid. In the Mae Sariang microgrid system, the electricity is produced from two renewable energy resources (RESs), i.e., hydro and solar PV. The use of these clean energy sources has become a main problem, envisaging the output power uncertainties from RESs. Further, such power uncertainty raises power quality problems and leads to power failure. To overcome such problems, the proposed fuzzy logic control (FLC) approach is applied for the BESS controller to improve the stability of the islanded Mae Sariang microgrid. The proposed FLC is intended to provide the BESS with well-established attributes of dynamical response to disturbance, which is analyzed by a predictive model. The proposed FLC has been investigated and compared with the robust control method, which is analyzed by a mathematical model using the system identification technique. The modeling of the microgrid system with BESS is implemented and verified on the DIgSILENT PowerFactory software. The simulation result illustrates that both of the control approaches allow the dynamic stability of the microgrid and the maintenance of frequency and voltage within acceptable ranges. However, the proposed BESS fuzzy logic control is less prone to uncertainty than the BESS robust control. Furthermore, in the proposed BESS fuzzy logic control, the microgrid frequency and voltage rapidly return to their normal steady-state condition and the size of the BESS is smaller than the BESS robust control.

Suggested Citation

  • Naowarat Tephiruk & Weerawoot Kanokbannakorn & Thongchart Kerdphol & Yasunori Mitani & Komsan Hongesombut, 2018. "Fuzzy Logic Control of a Battery Energy Storage System for Stability Improvement in an Islanded Microgrid," Sustainability, MDPI, vol. 10(5), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1645-:d:147993
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    References listed on IDEAS

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    Cited by:

    1. Hui Wang & Jun Wang & Zailin Piao & Xiaofang Meng & Chao Sun & Gang Yuan & Sitong Zhu, 2020. "The Optimal Allocation and Operation of an Energy Storage System with High Penetration Grid-Connected Photovoltaic Systems," Sustainability, MDPI, vol. 12(15), pages 1-22, July.
    2. Omer Faruk Goksu & Ahmet Yigit Arabul & Revna Acar Vural, 2020. "Low Voltage Battery Management System with Internal Adaptive Charger and Fuzzy Logic Controller," Energies, MDPI, vol. 13(9), pages 1-15, May.
    3. Seyedmahdi Izadkhast & Rafael Cossent & Pablo Frías & Pablo García-González & Andrea Rodríguez-Calvo, 2022. "Performance Evaluation of a BESS Unit for Black Start and Seamless Islanding Operation," Energies, MDPI, vol. 15(5), pages 1-20, February.
    4. Grzegorz Dec & Grzegorz Drałus & Damian Mazur & Bogdan Kwiatkowski, 2021. "Forecasting Models of Daily Energy Generation by PV Panels Using Fuzzy Logic," Energies, MDPI, vol. 14(6), pages 1-16, March.

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