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A Local Control Strategy for Distributed Energy Fluctuation Suppression Based on Soft Open Point

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  • Guo Xinming

    (Institute of Electrical Engineering of the Chinese Academy of Sciences, Beijing 100190, China
    School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Huo Qunhai

    (Institute of Electrical Engineering of the Chinese Academy of Sciences, Beijing 100190, China)

  • Wei Tongzhen

    (Institute of Electrical Engineering of the Chinese Academy of Sciences, Beijing 100190, China)

  • Yin Jingyuan

    (Institute of Electrical Engineering of the Chinese Academy of Sciences, Beijing 100190, China)

Abstract

This paper proposes a local control strategy applied in the soft open point (SOP) to suppress voltage fluctuation when adding a renewable energy source into the system. The mathematic model of the grid connected to SOP is established based on the characteristics of a low-voltage distribution network. Combined with the mathematic model and local voltage information, the local control strategy is proposed to optimize the active and reactive power distribution and consume the minimum apparent power of the converter. The local control strategy can effectively suppress the voltage fluctuation caused by renewable energy access, which was testified by MATLAB/Simulink simulation. In addition, the local control strategy can deduce the communication resource and increase the response speed compared to global optimization. This paper is meaningful for renewable energy source distribution and voltage balance in low-voltage distribution systems.

Suggested Citation

  • Guo Xinming & Huo Qunhai & Wei Tongzhen & Yin Jingyuan, 2020. "A Local Control Strategy for Distributed Energy Fluctuation Suppression Based on Soft Open Point," Energies, MDPI, vol. 13(6), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:6:p:1520-:d:336116
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    References listed on IDEAS

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    1. Narayan, Seema & Doytch, Nadia, 2017. "An investigation of renewable and non-renewable energy consumption and economic growth nexus using industrial and residential energy consumption," Energy Economics, Elsevier, vol. 68(C), pages 160-176.
    2. Long, Chao & Wu, Jianzhong & Thomas, Lee & Jenkins, Nick, 2016. "Optimal operation of soft open points in medium voltage electrical distribution networks with distributed generation," Applied Energy, Elsevier, vol. 184(C), pages 427-437.
    3. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Wu, Jianzhong, 2018. "Quantified flexibility evaluation of soft open points to improve distributed generator penetration in active distribution networks based on difference-of-convex programming," Applied Energy, Elsevier, vol. 218(C), pages 338-348.
    4. Cao, Wanyu & Wu, Jianzhong & Jenkins, Nick & Wang, Chengshan & Green, Timothy, 2016. "Operating principle of Soft Open Points for electrical distribution network operation," Applied Energy, Elsevier, vol. 164(C), pages 245-257.
    5. Li, Peng & Ji, Haoran & Yu, Hao & Zhao, Jinli & Wang, Chengshan & Song, Guanyu & Wu, Jianzhong, 2019. "Combined decentralized and local voltage control strategy of soft open points in active distribution networks," Applied Energy, Elsevier, vol. 241(C), pages 613-624.
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    Cited by:

    1. Yuriy Bilan & Marcin Rabe & Katarzyna Widera, 2022. "Distributed Energy Resources: Operational Benefits," Energies, MDPI, vol. 15(23), pages 1-7, November.
    2. Zbigniew Olczykowski & Zbigniew Łukasik, 2021. "Evaluation of Flicker of Light Generated by Arc Furnaces," Energies, MDPI, vol. 14(13), pages 1-23, June.
    3. Javier Solano & Diego Jimenez & Adrian Ilinca, 2020. "A Modular Simulation Testbed for Energy Management in AC/DC Microgrids," Energies, MDPI, vol. 13(16), pages 1-23, August.

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