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An Enhanced Continuation Power Flow Method Using Hybrid Parameterization

Author

Listed:
  • Haelee Kim

    (School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea)

  • Hyeon Woo

    (School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea)

  • Yeunggurl Yoon

    (School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea)

  • Hyun-Tae Kim

    (Korea Electric Power Corporation Research Institute, Naju 58277, Republic of Korea)

  • Yong Jung Kim

    (Korea Electric Power Corporation Research Institute, Naju 58277, Republic of Korea)

  • Moonho Kang

    (Korea Electric Power Corporation Research Institute, Naju 58277, Republic of Korea)

  • Xuehan Zhang

    (College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China)

  • Sungyun Choi

    (School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea)

Abstract

The rapid integration of renewable energy sources and the increasing complexity of modern power systems urge the development of advanced methods for ensuring power system stability. This paper presents a novel continuation power flow (CPF) method that combines two well-known parameterization techniques: natural parameterization and arc-length parameterization. The proposed hybrid approach significantly improves computational efficiency, reducing processing time by 32.76% compared to conventional methods while maintaining high accuracy. The method enables faster and more reliable stability assessments by efficiently managing the complexities and uncertainties, particularly in grids with high penetration of renewable energy.

Suggested Citation

  • Haelee Kim & Hyeon Woo & Yeunggurl Yoon & Hyun-Tae Kim & Yong Jung Kim & Moonho Kang & Xuehan Zhang & Sungyun Choi, 2024. "An Enhanced Continuation Power Flow Method Using Hybrid Parameterization," Sustainability, MDPI, vol. 16(17), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7595-:d:1469575
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    References listed on IDEAS

    as
    1. Hyeon Woo & Yongju Son & Jintae Cho & Sungyun Choi, 2022. "Stochastic Second-Order Conic Programming for Optimal Sizing of Distributed Generator Units and Electric Vehicle Charging Stations," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    2. Yoon, Myungseok & Cho, Namhun & Choi, Sungyun, 2023. "Analysis of temporary overvoltage due to inverter-based distributed generation in networked distribution systems," Applied Energy, Elsevier, vol. 341(C).
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