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Distributed Photovoltaic Generation Aggregation Approach Considering Distribution Network Topology

Author

Listed:
  • Yajie Tang

    (State Grid Zhejiang Electric Power Research Institute, Hangzhou 310014, China)

  • Sikai Sun

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Bo Zhao

    (State Grid Zhejiang Electric Power Research Institute, Hangzhou 310014, China)

  • Chouwei Ni

    (State Grid Zhejiang Electric Power Research Institute, Hangzhou 310014, China)

  • Liang Che

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Junhao Li

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

Abstract

Distributed photovoltaics (DPVs) are widely distributed and the output is random, which brings challenges to the safe operation of the distribution network, so the construction of photovoltaic aggregations can effectively participate in the flexible regulation of the power system. At present, the extraction of DPV clustering features is not sufficient, only considering the output characteristics of PVs. Certain PVs under some nodes may have a more pronounced regulation effect, but they may be ignored in the clustering process. To address the above problems, this paper proposes a DPV aggregation approach considering the distribution network topology. It combines the voltage sensitivity and the power curve and regards them as clustering features to form the DPV aggregation with the highest average voltage sensitivity participating in voltage regulation. The simulation on the IEEE 33-node system verifies that the proposed aggregation approach can select DPV aggregation more suitable for voltage regulation, and make full use of the aggregation to realize the optimal voltage regulation effect.

Suggested Citation

  • Yajie Tang & Sikai Sun & Bo Zhao & Chouwei Ni & Liang Che & Junhao Li, 2024. "Distributed Photovoltaic Generation Aggregation Approach Considering Distribution Network Topology," Energies, MDPI, vol. 17(12), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2990-:d:1416788
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    Cited by:

    1. Arkadiusz Małek & Andrzej Marciniak & Tomasz Bednarczyk, 2024. "Probabilistic Analysis of Electricity Production from a Photovoltaic–Wind Energy Mix for Sustainable Transport Needs," Sustainability, MDPI, vol. 16(23), pages 1-23, November.

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