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Optimal Reactive Power Dispatch under Transmission and Distribution Coordination Based on an Accelerated Augmented Lagrangian Algorithm

Author

Listed:
  • Bin Zhou

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Xiaodong Shen

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Caimei Pan

    (Sichuan Energy Investment Integrated Energy Co., Ltd., Chengdu 611130, China)

  • Yuanbao Bai

    (Sichuan Energy Investment Integrated Energy Co., Ltd., Chengdu 611130, China)

  • Tian Wu

    (Sichuan Energy Investment Integrated Energy Co., Ltd., Chengdu 611130, China)

Abstract

As many distributed power sources flood into the distribution network, the relationship between transmission and distribution grids in reactive power and voltage is becoming closer and closer. The traditional way of independent reactive power optimization in transmission and distribution grids is no longer appropriate. In this study, a collaborative and distributed reactive power optimization method for transmission and distribution grids based on the accelerated augmented Lagrangian (AAL) algorithm is proposed to adapt to the independence of the transmission and distribution grids in operation and management. The global reactive power optimization problem is decomposed into the transmission network subproblem and several distribution network subproblems. According to AAL, subproblems are solved in a distributed manner until the optimal global solution is finally reached after several iterations, and coordination between transmission and distribution grids is achieved only through the interaction of information on coordinating variables. For better convergence, a linearized and convergence-guaranteed optimal power flow model (OPF) with reactive power and voltage magnitude was applied to model the transmission grid optimization subproblem, while the second-order cone programming (SOCP) technique is used in the distribution network subproblems. The simulation results confirm that the method in this paper can effectively reduce network losses and achieve better economic performance, and converges better when compared to other algorithms.

Suggested Citation

  • Bin Zhou & Xiaodong Shen & Caimei Pan & Yuanbao Bai & Tian Wu, 2022. "Optimal Reactive Power Dispatch under Transmission and Distribution Coordination Based on an Accelerated Augmented Lagrangian Algorithm," Energies, MDPI, vol. 15(11), pages 1-22, May.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:3867-:d:822899
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    Citations

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    Cited by:

    1. Tian Mao & Shan He & Yingcong Guan & Mingbo Liu & Wenmeng Zhao & Tao Wang & Wenjun Tang, 2023. "A Novel Allocation Strategy Based on the Model Predictive Control of Primary Frequency Regulation Power for Multiple Distributed Energy Storage Aggregators," Energies, MDPI, vol. 16(17), pages 1-21, August.
    2. Umar Waleed & Abdul Haseeb & Muhammad Mansoor Ashraf & Faisal Siddiq & Muhammad Rafiq & Muhammad Shafique, 2022. "A Multiobjective Artificial-Hummingbird-Algorithm-Based Framework for Optimal Reactive Power Dispatch Considering Renewable Energy Sources," Energies, MDPI, vol. 15(23), pages 1-23, December.

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