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Reactive Power Optimization Model for Distribution Networks Based on the Second-Order Cone and Interval Optimization

Author

Listed:
  • Minsheng Yang

    (College of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, China
    Key Laboratory of Hunan Province for Control Technology of Distributed Electric Propulsion Air Vehicle, Changde 415000, China)

  • Jianqi Li

    (College of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, China
    Key Laboratory of Hunan Province for Control Technology of Distributed Electric Propulsion Air Vehicle, Changde 415000, China)

  • Rui Du

    (College of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, China
    Key Laboratory of Hunan Province for Control Technology of Distributed Electric Propulsion Air Vehicle, Changde 415000, China)

  • Jianying Li

    (College of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, China
    Key Laboratory of Hunan Province for Control Technology of Distributed Electric Propulsion Air Vehicle, Changde 415000, China)

  • Jian Sun

    (College of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, China)

  • Xiaofang Yuan

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

  • Jiazhu Xu

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

  • Shifu Huang

    (Changde Guoli Transformer Co., Ltd., Changde 415000, China)

Abstract

Traditional reactive power optimization mainly considers the constraints of active management elements and ignores the randomness and volatility of distributed energy sources, which cannot meet the actual demand. Therefore, this paper establishes a reactive power optimization model for active distribution networks, which is solved by a second-order cone relaxation method and interval optimization theory. On the one hand, the second-order cone relaxation technique transforms the non-convex optimal dynamic problem into a convex optimization model to improve the solving efficiency. On the other hand, the interval optimization strategy can solve the source–load uncertainty problem in the distribution network and obtain the interval solution of the optimization problem. Specially, we use confidence interval estimation to shorten the interval range, thereby improving the accuracy of the interval solution. The model takes the minimum economy as the objective function and considers a variety of active management elements. Finally, the modified IEEE 33 node arithmetic example verifies the feasibility and superiority of the interval optimization algorithm.

Suggested Citation

  • Minsheng Yang & Jianqi Li & Rui Du & Jianying Li & Jian Sun & Xiaofang Yuan & Jiazhu Xu & Shifu Huang, 2022. "Reactive Power Optimization Model for Distribution Networks Based on the Second-Order Cone and Interval Optimization," Energies, MDPI, vol. 15(6), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2235-:d:774452
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    References listed on IDEAS

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    Cited by:

    1. Yi Zhang & Pengtao Liu, 2023. "Research on Reactive Power Optimization Based on Hybrid Osprey Optimization Algorithm," Energies, MDPI, vol. 16(20), pages 1-20, October.

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