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Two-Stage Optimal Scheduling Strategy of Microgrid Distribution Network Considering Multi-Source Agricultural Load Aggregation

Author

Listed:
  • Guozhen Ma

    (State Grid Hebei Electric Power Co., Ltd., Economic and Technological Research Institute, Shijiazhuang 050021, China)

  • Ning Pang

    (State Grid Hebei Electric Power Co., Ltd., Economic and Technological Research Institute, Shijiazhuang 050021, China)

  • Yunjia Wang

    (State Grid Hebei Electric Power Co., Ltd., Economic and Technological Research Institute, Shijiazhuang 050021, China)

  • Shiyao Hu

    (State Grid Hebei Electric Power Co., Ltd., Economic and Technological Research Institute, Shijiazhuang 050021, China)

  • Xiaobin Xu

    (State Grid Hebei Electric Power Co., Ltd., Economic and Technological Research Institute, Shijiazhuang 050021, China)

  • Zeya Zhang

    (State Grid Hebei Electric Power Co., Ltd., Economic and Technological Research Institute, Shijiazhuang 050021, China)

  • Changhong Wang

    (College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China)

  • Liai Gao

    (College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
    Baoding Key Laboratory of Precision Control and Clean Energy Supply for Facility Agriculture Environment, Baoding 071000, China)

Abstract

With the proposed “double carbon” target for the power system, large-scale distributed energy access poses a major challenge to the way the distribution grid operates. The rural distribution network (DN) will transform into a new local power system primarily driven by distributed renewable energy sources and energy storage, while also being interconnected with the larger power grid. The development of the rural DN will heavily rely on the construction and efficient planning of the microgrid (MG) within the agricultural park. Based on this, this paper proposes a two-stage optimal scheduling model and solution strategy for the microgrid distribution network with multi-source agricultural load aggregation. First, in the first stage, considering the flexible agricultural load and the market time-of-use electricity price, the economic optimization is realized by optimizing the operation of the schedulable resources of the park. The linear model in this stage is solved by the Lingo algorithm with fast solution speed and high accuracy. In the second stage, the power interaction between the MG and the DN in the agricultural park is considered. By optimising the output of the reactive power compensation device, the operating state of the DN is optimised. At this stage, the non-linear and convex optimization problems are solved by the particle swarm optimization algorithm. Finally, the example analysis shows that the proposed method can effectively improve the feasible region of safe operation of the distribution network in rural areas and improve the operating income of a multi-source agricultural load aggregation agricultural park.

Suggested Citation

  • Guozhen Ma & Ning Pang & Yunjia Wang & Shiyao Hu & Xiaobin Xu & Zeya Zhang & Changhong Wang & Liai Gao, 2024. "Two-Stage Optimal Scheduling Strategy of Microgrid Distribution Network Considering Multi-Source Agricultural Load Aggregation," Energies, MDPI, vol. 17(21), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5429-:d:1510574
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    References listed on IDEAS

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    1. Dong, Lei & Lin, Hao & Qiao, Ji & Zhang, Tao & Zhang, Shiming & Pu, Tianjiao, 2024. "A coordinated active and reactive power optimization approach for multi-microgrids connected to distribution networks with multi-actor-attention-critic deep reinforcement learning," Applied Energy, Elsevier, vol. 373(C).
    2. Sharifian, Yeganeh & Abdi, Hamdi, 2023. "Solving multi-area economic dispatch problem using hybrid exchange market algorithm with grasshopper optimization algorithm," Energy, Elsevier, vol. 267(C).
    Full references (including those not matched with items on IDEAS)

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