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Robust coordinated optimization for multi-energy systems based on multiple thermal inertia numerical simulation and uncertainty analysis

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  • Sun, Peng
  • Teng, Yun
  • Chen, Zhe

Abstract

The heat system has the larger inertia in the multi-energy system (MES) integrated electricity, heat and gas, and its uncertainty caused by the heating parameters variation of the practical project, which will make the scheduling and operation of the MES more difficult and complicated. In order to improve the energy efficiency and flexibility of MES, it is essential to explore the quantitative impact of thermal inertia on the regulation capacity of the MES. To tackle this problem, this paper proposes a robust coordinated optimization method for MES considering thermal inertia uncertainty (TIU). First, the multiple thermal inertia (MTI) of solid thermal storage electric boiler (STSEB), heating network (HN) and buildings (BD) are modeled, and the thermal inertia of physical models are simulated based on ANSYS finite element software. The quantitative method of the difference between the monitoring data of the heating network operation status and the thermal energy flow model is studied, and the TIU model is established. By discretizing the uncertainty domain, an improved two-stage robust optimal scheduling model for MES considering TIU is constructed. Finally, part of real MES in the Northeastern China is used in the case study. Simulation results show that the operating cost of the MES considering the uncertainty of wind power will increase by 26.9%. On this basis, the operating cost considering TIU is reduced by 16.3%. It can be seen that considering the TIU will enhance heat storage capacity of heating network and has positive benefits for MES regulation, which can balance the operating cost and robustness of the system, and promote wind power integration.

Suggested Citation

  • Sun, Peng & Teng, Yun & Chen, Zhe, 2021. "Robust coordinated optimization for multi-energy systems based on multiple thermal inertia numerical simulation and uncertainty analysis," Applied Energy, Elsevier, vol. 296(C).
    • Handle: RePEc:eee:appene:v:296:y:2021:i:c:s0306261921004530
    DOI: 10.1016/j.apenergy.2021.116982
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