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Improvement of Fuzzy Newton Power Flow Convergence

Author

Listed:
  • Ligang Zhao

    (CSG Electric Power Research Institute China Southern Power Grid, Guangzhou 510663, China)

  • Hua Zheng

    (School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Hongyue Zhen

    (CSG Electric Power Research Institute China Southern Power Grid, Guangzhou 510663, China)

  • Li Xie

    (School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Yuan Xu

    (CSG Electric Power Research Institute China Southern Power Grid, Guangzhou 510663, China)

  • Xianchao Huang

    (School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China)

Abstract

In order to address the convergence issue in fuzzy power flow calculations, this paper proposes an analytical approach based on the Levenberg–Marquardt method, aiming to improve the convergence of the fuzzy Newton power flow method. Firstly, a detailed analysis is conducted on the convergence theorem and convergence behavior of the fuzzy Newton method, revealing its poor convergence when the initial values are not properly selected. The Levenberg–Marquardt method is then selected as a means to enhance the convergence of the fuzzy Newton power flow calculations, specifically to tackle the problem of initial value deviation. Since the Jacobian matrix has a significant impact on the convergence region of the power flow, this paper reconstructs the Jacobian matrix based on the Levenberg–Marquardt method, effectively enlarging the convergence region. Through validation experiments on the IEEE 118 standard nodes and simulation comparative analysis, the results confirm the method’s effectiveness in resolving the problem of initial value deviation and notably enlarging the convergence region, thereby improving the convergence of power flow calculations.

Suggested Citation

  • Ligang Zhao & Hua Zheng & Hongyue Zhen & Li Xie & Yuan Xu & Xianchao Huang, 2023. "Improvement of Fuzzy Newton Power Flow Convergence," Energies, MDPI, vol. 16(24), pages 1-14, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:8044-:d:1299406
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    References listed on IDEAS

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    1. Rudy Gianto & Purwoharjono & Fitri Imansyah & Rudi Kurnianto & Danial, 2023. "Steady-State Load Flow Model of DFIG Wind Turbine Based on Generator Power Loss Calculation," Energies, MDPI, vol. 16(9), pages 1-14, April.
    2. Stennikov, Valery & Barakhtenko, Evgeny & Mayorov, Gleb & Sokolov, Dmitry & Zhou, Bin, 2022. "Coordinated management of centralized and distributed generation in an integrated energy system using a multi-agent approach," Applied Energy, Elsevier, vol. 309(C).
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