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Bi-level energy co-optimization of regional integrated energy system with electric vehicle to generalized-energy conversion framework and flexible hydrogen-blended gas strategy

Author

Listed:
  • Liu, Zhi-Feng
  • Liu, You-Yuan
  • Jia, Hong-Jie
  • Jin, Xiao-Long
  • Liu, Tong-Hui
  • Wu, Yu-Ze

Abstract

The Regional Integrated Energy System (RIES) plays a pivotal role in integrating clean energy sources and advancing the low-carbon transition of energy structures. However, large-scale electric vehicles (EVs) and clean energy sources poses significant challenges to the optimal operation of RIES. Consequently, this study developed a novel RIES energy dispatching model, which comprehensively considers the complementary allocation of EVs and a hydrogen-blending natural gas system within the RIES. First, a novel V2X (vehicle to everything) generalized energy conversion framework was established. Through the incorporation of an interaction index, the scheduling of EV charging and discharging is rendered more flexible and orderly. Second, a hydrogen-doped-gas (H-G) flexible blending strategy was introduced to achieve the efficient coupling and utilization of hydrogen and natural gas, maximizing the effectiveness of hydrogen utilization. Finally, a multi-objective mountaineering team-based optimization (MMTBO) algorithm based on the altitude controller search strategy and the non-dominated solution fine division mechanism was proposed. Simulation results have demonstrated that the method proposed in this study contributes to enhancing the management capability of electric vehicle charging and discharging, as well as improving the utilization efficiency of hydrogen energy. Numerical results revealed that the proposed MMBTO algorithm outperformed two traditional evolutionary algorithms by optimizing the energy producer (EP) yields by 10.1 % and 10.4 % more, respectively, highlighting its superior competitiveness. After the introduction of the “V2X” framework, the comprehensive economic cost of the RIES decreased by 5 %. Additionally, the RIES orderly transferred the electric load during the peak charging period of EVs, averaging 677.2 kW, effectively alleviating the surge in electric load caused by the disorderly charging of EVs. Under the H-G flexible blending strategy, the average carbon emissions of RIES decreased by 44.4 %, improving the system's environmental benefits.

Suggested Citation

  • Liu, Zhi-Feng & Liu, You-Yuan & Jia, Hong-Jie & Jin, Xiao-Long & Liu, Tong-Hui & Wu, Yu-Ze, 2025. "Bi-level energy co-optimization of regional integrated energy system with electric vehicle to generalized-energy conversion framework and flexible hydrogen-blended gas strategy," Applied Energy, Elsevier, vol. 390(C).
    • Handle: RePEc:eee:appene:v:390:y:2025:i:c:s0306261925005987
    DOI: 10.1016/j.apenergy.2025.125868
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    1. Xin Ma & Yubing Liu & Chongyi Tian & Bo Peng, 2025. "A Multi-Temporal Regulation Strategy for EV Aggregators Enabling Bi-Directional Energy Interactions in Ancillary Service Markets for Sustainable Grid Operation," Sustainability, MDPI, vol. 17(16), pages 1-29, August.
    2. He, Junqiang & Zhao, Haiyan & Yin, Jingyuan & Shi, Changli, 2026. "A hierarchical game-based price-demand-energy hub operation coordinated optimization strategy for near-carbon-neutral hydrogen industrial parks," Renewable Energy, Elsevier, vol. 258(C).
    3. Pang, Xinfu & Wang, Xinyuan & Yu, Yang & Jiang, He & Zheng, Zedong, 2025. "Optimal scheduling for electric vehicle charging and discharging via double Q-learning-based multi-objective particle swarm optimization," Energy, Elsevier, vol. 339(C).
    4. Peng, Shi-Tao & Qi, Zhao-Yu & Liu, You-Yuan & Liu, Zhi-Feng & Li, Ling-Ling, 2025. "Improving the energy efficiency and economic benefits of port integrated energy systems: A multi-objective optimization model for wind-storage-charging-discharging power stations with green efficiency factors-driven multilateral response strategy," Energy, Elsevier, vol. 339(C).

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