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Distributed Control Strategy of Single-Phase Battery Systems for Compensation of Unbalanced Active Powers in a Three-Phase Four-Wire Microgrid

Author

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  • Watcharakorn Pinthurat

    (School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney 2052, Australia)

  • Branislav Hredzak

    (School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney 2052, Australia)

Abstract

Unbalanced active powers can affect power quality and system reliability due to high penetration and uneven allocation of single-phase photovoltaic (PV) rooftop systems and load demands in a three-phase four-wire microgrid. This paper proposes a distributed control strategy to alleviate the unbalanced active powers using distributed single-phase battery storage systems. In order to balance the unbalanced active powers at the point of common coupling (PCC) in a distributed manner, the agents (households’ single-phase battery storage systems) must have information on the active powers and phases. Inspired by supervised learning, a clustering approach was developed to use labels in order to match the three-phase active powers at the PCC with the agents’ phases. This enables the agent to select the correct active power data from the three-phase active powers. Then, a distributed power balancing control strategy is applied by all agents to compensate the unbalanced active powers. Each agent calculates the average grid power based on information received from its neighbours so that all agents can then cooperatively operate in either charging or discharging modes to achieve the compensation. As an advantage, the proposed distributed control strategy offers the battery owners flexibility to participate in the strategy. Case studies comparing performance of local, centralized, and the proposed distributed strategy on a modified IEEE-13-bus test system with real household PV powers and load demands are provided.

Suggested Citation

  • Watcharakorn Pinthurat & Branislav Hredzak, 2021. "Distributed Control Strategy of Single-Phase Battery Systems for Compensation of Unbalanced Active Powers in a Three-Phase Four-Wire Microgrid," Energies, MDPI, vol. 14(24), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8287-:d:698374
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    References listed on IDEAS

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    1. Rafi, Fida Hasan Md & Hossain, M.J. & Rahman, Md Shamiur & Taghizadeh, Seyedfoad, 2020. "An overview of unbalance compensation techniques using power electronic converters for active distribution systems with renewable generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 125(C).
    2. Watcharakorn Pinthurat & Branislav Hredzak, 2020. "Decentralized Frequency Control of Battery Energy Storage Systems Distributed in Isolated Microgrid," Energies, MDPI, vol. 13(11), pages 1-18, June.
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    Cited by:

    1. Sane Lei Lei Wynn & Watcharakorn Pinthurat & Boonruang Marungsri, 2022. "Multi-Objective Optimization for Peak Shaving with Demand Response under Renewable Generation Uncertainty," Energies, MDPI, vol. 15(23), pages 1-19, November.
    2. Nonthawat Khortsriwong & Promphak Boonraksa & Terapong Boonraksa & Thipwan Fangsuwannarak & Asada Boonsrirat & Watcharakorn Pinthurat & Boonruang Marungsri, 2023. "Performance of Deep Learning Techniques for Forecasting PV Power Generation: A Case Study on a 1.5 MWp Floating PV Power Plant," Energies, MDPI, vol. 16(5), pages 1-21, February.

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