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Optimal operation of multi-micro energy grids under distribution network in Southwest China

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  • An, Su
  • Wang, Honglei
  • Leng, Xiaoxia

Abstract

The rapid growth of distributed photovoltaic and wind power installed capacity in Southwest China has reduced the operation safety margin of the power grid. Power grid dispatchers face the dilemma of ensuring security of the power grid and the output curtailment of renewable energy. To achieve the full consumption of renewable energy, it is an effective way to make use of the space-time complementary characteristics of different energies by forming micro energy grids. By connecting to the distribution network, the energy among the micro energy grids can be transferred and distributed in the form of electricity. Therefore, this study builds collaborative operation optimisation models of distribution networks with multi-micro energy grids and proposes an adaptive dynamic real-time optimisation algorithm based on pre-training and online deep learning techniques for the joint system. A test system was constructed based on the actual equipment parameters and data from the Guizhou power grid. Through the calculation and simulation in the test system, the overload of the distribution network equipment and the network loss were effectively reduced while ensuring the full consumption of wind and photovoltaic power. In addition, the accuracy and effectiveness of the model and algorithm were verified. The results obtained in the case studies suggest that the method proposed in this paper can be applied to southwest China and similar regions.

Suggested Citation

  • An, Su & Wang, Honglei & Leng, Xiaoxia, 2022. "Optimal operation of multi-micro energy grids under distribution network in Southwest China," Applied Energy, Elsevier, vol. 309(C).
    • Handle: RePEc:eee:appene:v:309:y:2022:i:c:s030626192101686x
    DOI: 10.1016/j.apenergy.2021.118461
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    3. Hang Liu & Yongcheng Wang & Shilin Nie & Yi Wang & Yu Chen, 2022. "Multistage Economic Scheduling Model of Micro-Energy Grids Considering Flexible Capacity Allocation," Sustainability, MDPI, vol. 14(15), pages 1-29, July.

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