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Topological partition based multi-energy flow calculation method for complex integrated energy systems

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  • Hu, Qinran
  • Liang, Yiheng
  • Ding, Haohui
  • Quan, Xiangjun
  • Wang, Qi
  • Bai, Linquan

Abstract

Multi-energy flow (MEF) calculation is essential for analyzing integrated energy systems (IES) with electricity, gas, and heat. However, for some hybrid-topology IES, conventional MEF calculation methods are hard to converge due to the complex topological structure. To this end, this paper proposes a topological partition based MEF calculation method. First, based on topological structure, the proposed method divides the original system into multiple blocks with only radial or looped topologies, and solves each block with suitable algorithms. This improvement can accelerate the calculation process and broaden the initial solutions range. Second, the proposed method sets the proper balance node of each block such that the convergence of each block becomes independent. This enables the non-convergent blocks can be identified easily. Third, the proposed method sets isobarometric nodes to get equivalent topology reconstruction, which makes the MEF calculation applicable for certain complex systems. Finally, a case study on the IES of Yangzhong City shows the effectiveness of the proposed method.

Suggested Citation

  • Hu, Qinran & Liang, Yiheng & Ding, Haohui & Quan, Xiangjun & Wang, Qi & Bai, Linquan, 2022. "Topological partition based multi-energy flow calculation method for complex integrated energy systems," Energy, Elsevier, vol. 244(PB).
  • Handle: RePEc:eee:energy:v:244:y:2022:i:pb:s036054422200055x
    DOI: 10.1016/j.energy.2022.123152
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    References listed on IDEAS

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    1. Liu, Xuezhi & Wu, Jianzhong & Jenkins, Nick & Bagdanavicius, Audrius, 2016. "Combined analysis of electricity and heat networks," Applied Energy, Elsevier, vol. 162(C), pages 1238-1250.
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    Cited by:

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    2. Wu, Huayi & Xu, Zhao, 2024. "Multi-energy flow calculation in integrated energy system via topological graph attention convolutional network with transfer learning," Energy, Elsevier, vol. 303(C).
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    4. Zhang, Yuanshi & Qian, Wenyan & Ye, Yujian & Li, Yang & Tang, Yi & Long, Yu & Duan, Meimei, 2023. "A novel non-intrusive load monitoring method based on ResNet-seq2seq networks for energy disaggregation of distributed energy resources integrated with residential houses," Applied Energy, Elsevier, vol. 349(C).

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