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A Reactive Power Partitioning Method Considering Source–Load Correlation and Regional Coupling Degrees

Author

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  • Jiazheng Ding

    (School of Electric Power, South China University of Technology, Guangzhou 510640, China)

  • Xiaoyang Xu

    (School of Electric Power, South China University of Technology, Guangzhou 510640, China)

  • Fengqiang Deng

    (School of Electric Power, South China University of Technology, Guangzhou 510640, China)

Abstract

To address the enhanced coupling characteristics in reactive power partitioning of power grids with high-penetration renewable energy integration, this paper proposes an optimized reactive power partitioning method that integrates dynamic source–load correlation characteristics and regional coupling degree evaluation. Conventional static electrical distance-based partitioning methods struggle to adapt to dynamic coupling effects caused by renewable energy output fluctuations, leading to degraded partition decoupling performance. This study innovatively constructs a Copula function-based joint probability distribution model for source–load correlation. By employing non-parametric estimation and undetermined coefficient methods to solve marginal distribution parameters, and utilizing the K-means clustering algorithm to generate typical scenario sets, a comprehensive source–load coupling evaluation framework is established, incorporating the renewable energy output proportion and time-varying correlation index. For electrical distance calculation, a generalized construction method for extended sensitivity matrices is proposed, featuring dynamic weight adjustment through regional coupling degree correction factors. Simulation results demonstrate that in practical case studies, compared with traditional partitioning schemes, the proposed method reduces the regional coupling degree metric by 4.216% and enhances the regional reactive power imbalance index suppression by 11.082%, validating its effectiveness in achieving reactive power local balance and reactive power partitioning. This research breaks through the theoretical limitations of static partitioning and provides theoretical support for dynamic zonal control in modern power systems with high renewable penetration.

Suggested Citation

  • Jiazheng Ding & Xiaoyang Xu & Fengqiang Deng, 2025. "A Reactive Power Partitioning Method Considering Source–Load Correlation and Regional Coupling Degrees," Energies, MDPI, vol. 18(8), pages 1-16, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:1960-:d:1632717
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    References listed on IDEAS

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    1. Chuanliang Xiao & Lei Sun & Ming Ding, 2020. "Multiple Spatiotemporal Characteristics-Based Zonal Voltage Control for High Penetrated PVs in Active Distribution Networks," Energies, MDPI, vol. 13(1), pages 1-21, January.
    2. Jaehyun Yoo & Yongju Son & Myungseok Yoon & Sungyun Choi, 2023. "A Wind Power Scenario Generation Method Based on Copula Functions and Forecast Errors," Sustainability, MDPI, vol. 15(23), pages 1-15, December.
    3. Yuezhong Wu & Yujie Xiong & Xiaowei Peng & Cheng Cai & Xiangming Zheng, 2024. "Research on a Three-Stage Dynamic Reactive Power Optimization Decoupling Strategy for Active Distribution Networks with Carbon Emissions," Energies, MDPI, vol. 17(11), pages 1-21, June.
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