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Grid-Following Mode Operation of Small-Scale Distributed Battery Energy Storages for Fast Frequency Regulation in a Mixed-Source Microgrid

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  • Amir Hussain

    (Department of Electrical and Computer Engineering, College of Technology, University of Houston, Houston, TX 77004, USA)

  • Wajiha Shireen

    (Department of Electrical and Computer Engineering, College of Technology, University of Houston, Houston, TX 77004, USA)

Abstract

As the share of power converter-based renewable energy sources (RESs) is high, a microgrid, in islanded mode, is more vulnerable to frequency instability due to (1) sudden power imbalance and (2) low inertia. One of the most common approaches to address this issue is to provide virtual inertia to the system by appropriately controlling the grid-side converter of the RESs. However, the primary frequency controller (PFC) presented in this paper focuses on the fast compensation of power imbalance without adding inertia to the system. The proposed method is based on estimating the real-time power imbalance caused by a disturbance and compensating it using multiple small-scale distributed battery energy storage systems (BESSs). The power imbalance is estimated by observing the initial rate of change of frequency (RoCoF) following a disturbance. Based on the estimated power imbalance and the rating of the BESSs, the reference power for the BESSs is determined. The BESSs are controlled in grid-following mode to compensate for the power imbalance. The performance of the proposed PFC is verified using a Typhoon real-time simulator for various scenarios and is compared with the conventional virtual synchronous generator (VSG) controller.

Suggested Citation

  • Amir Hussain & Wajiha Shireen, 2021. "Grid-Following Mode Operation of Small-Scale Distributed Battery Energy Storages for Fast Frequency Regulation in a Mixed-Source Microgrid," Energies, MDPI, vol. 14(22), pages 1-15, November.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:22:p:7710-:d:681476
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    References listed on IDEAS

    as
    1. Ting-Hsuan Chien & Yu-Chuan Huang & Yuan-Yih Hsu, 2020. "Neural Network-Based Supplementary Frequency Controller for a DFIG Wind Farm," Energies, MDPI, vol. 13(20), pages 1-15, October.
    2. Iván Pazmiño & Sergio Martinez & Danny Ochoa, 2021. "Analysis of Control Strategies Based on Virtual Inertia for the Improvement of Frequency Stability in an Islanded Grid with Wind Generators and Battery Energy Storage Systems," Energies, MDPI, vol. 14(3), pages 1-18, January.
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