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Energy Storage System Event-Driven Frequency Control Using Neural Networks to Comply with Frequency Grid Code

Author

Listed:
  • Soseul Jeong

    (School of Electrical Engineering, Korea University, Seoul 02841, Korea)

  • Junghun Lee

    (School of Electrical Engineering, Korea University, Seoul 02841, Korea)

  • Minhan Yoon

    (Department of Electrical Engineering, Kwangwoon University, Seoul 01897, Korea)

  • Gilsoo Jang

    (School of Electrical Engineering, Korea University, Seoul 02841, Korea)

Abstract

As the penetration of renewable energy sources (RESs) increases, the rate of conventional generators and the power system inertia are reduced accordingly, resulting in frequency-stability concerns. As one of the solutions, the battery-type energy storage system (ESS), which can rapidly charge and discharge energy, is utilized for frequency regulation. Typically, it is based on response-driven frequency control (RDFC), which adjusts its output according to the measured frequency. In contrast, event-driven frequency control (EDFC) involves a determined frequency support scheme corresponding to a particular event. EDFC has the advantage that control action is promptly performed compared to RDFC. This study proposes an ESS EDFC strategy that involves estimating the required operating point of the ESS according to a specific disturbance through neural-network training. When a disturbance occurs, the neural networks can estimate the proper magnitude and duration of the ESS output to comply with the frequency grid code. A simulation to validate the proposed control method was performed for an IEEE 39 bus system. The simulation results indicate that a neural-network estimation offers sufficient accuracy for practical use, and frequency response can be adjusted as intended by the system operator.

Suggested Citation

  • Soseul Jeong & Junghun Lee & Minhan Yoon & Gilsoo Jang, 2020. "Energy Storage System Event-Driven Frequency Control Using Neural Networks to Comply with Frequency Grid Code," Energies, MDPI, vol. 13(7), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1657-:d:340705
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    References listed on IDEAS

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    1. Xing Luo & Jihong Wang & Jacek D. Wojcik & Jianguo Wang & Decai Li & Mihai Draganescu & Yaowang Li & Shihong Miao, 2018. "Review of Voltage and Frequency Grid Code Specifications for Electrical Energy Storage Applications," Energies, MDPI, vol. 11(5), pages 1-26, April.
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    Cited by:

    1. Md. Shafiul Alam & Tanzi Ahmed Chowdhury & Abhishak Dhar & Fahad Saleh Al-Ismail & M. S. H. Choudhury & Md Shafiullah & Md. Ismail Hossain & Md. Alamgir Hossain & Aasim Ullah & Syed Masiur Rahman, 2023. "Solar and Wind Energy Integrated System Frequency Control: A Critical Review on Recent Developments," Energies, MDPI, vol. 16(2), pages 1-31, January.
    2. Józef Borkowski & Mirosław Szmajda & Janusz Mroczka, 2021. "The Influence of Power Network Disturbances on Short Delayed Estimation of Fundamental Frequency Based on IpDFT Method with GMSD Windows," Energies, MDPI, vol. 14(20), pages 1-26, October.
    3. Amer S. Alsalman & Talal Alharbi & Ahmed A. Mahfouz, 2023. "Enhancing the Stability of an Isolated Electric Grid by the Utilization of Energy Storage Systems: A Case Study on the Rafha Grid," Sustainability, MDPI, vol. 15(17), pages 1-24, September.

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