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A Coordination Optimization Method for Load Shedding Considering Distribution Network Reconfiguration

Author

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  • Kai Wang

    (Department of Chemical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Lixia Kang

    (Department of Chemical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
    Engineering Research Centre of New Energy System Engineering and Equipment, University of Shaanxi Province, Xi’an 710049, China)

  • Songhao Yang

    (Department of Electric Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

Load shedding control is an emergency control measure to maintain the frequency stability of the power system. Most of the existing load shedding methods use the extensive form of directly cutting off the outlet of the substation, featuring low control accuracy and high control cost. A network reconfiguration technique can adjust the topology of the distribution network and offers more optimization space for load shedding control. Therefore, this paper proposes a reconfiguration–load shedding coordination optimization scheme to reduce the power loss caused by load shedding control. In the proposed method, a load shedding mathematical optimization model based on distribution network reconfiguration is first established. The tie switches and segment switches in the distribution network are used to perform the reconfiguration of the distribution network, and the load switches are adopted to realize the load shedding. To improve the solving efficiency of the model, a solving strategy that combined a minimum spanning tree algorithm with an improved genetic algorithm is trailed to address the nonlinear and nonconvex terms. The application of the proposed method and model are finally verified via the IEEE 33 bus system, and the advantages in reducing the loss cost and the number of outage users are accordingly proven.

Suggested Citation

  • Kai Wang & Lixia Kang & Songhao Yang, 2022. "A Coordination Optimization Method for Load Shedding Considering Distribution Network Reconfiguration," Energies, MDPI, vol. 15(21), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8178-:d:961038
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    References listed on IDEAS

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    1. Li, Rui & Wang, Wei & Wu, Xuezhi & Tang, Fen & Chen, Zhe, 2019. "Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis," Energy, Elsevier, vol. 168(C), pages 30-42.
    2. Haitao Liu & Yu Ji & Huaidong Zhuang & Hongbin Wu, 2015. "Multi-Objective Dynamic Economic Dispatch of Microgrid Systems Including Vehicle-to-Grid," Energies, MDPI, vol. 8(5), pages 1-20, May.
    3. Jafar Jallad & Saad Mekhilef & Hazlie Mokhlis & Javed Laghari & Ola Badran, 2018. "Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation," Energies, MDPI, vol. 11(5), pages 1-25, May.
    4. Yeongho Choi & Yujin Lim & Hak-Man Kim, 2017. "Optimal Load Shedding for Maximizing Satisfaction in an Islanded Microgrid," Energies, MDPI, vol. 10(1), pages 1-13, January.
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    Cited by:

    1. Florin-Constantin Baiceanu & Ovidiu Ivanov & Razvan-Constantin Beniuga & Bogdan-Constantin Neagu & Ciprian-Mircea Nemes, 2023. "A Continuous Multistage Load Shedding Algorithm for Industrial Processes Based on Metaheuristic Optimization," Mathematics, MDPI, vol. 11(12), pages 1-19, June.
    2. Paweł Pijarski & Piotr Kacejko, 2023. "Elimination of Line Overloads in a Power System Saturated with Renewable Energy Sources," Energies, MDPI, vol. 16(9), pages 1-19, April.

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