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Available transfer capability evaluation in electricity-dominated integrated hybrid energy systems with uncertain wind power: An interval optimization solution

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  • Jiang, Tao
  • Li, Xue
  • Kou, Xiao
  • Zhang, Rufeng
  • Tian, Guoda
  • Li, Fangxing

Abstract

Available transfer capability (ATC) is widely used in the deregulated electricity market to ensure secure and reliable power trading among market participants. However, most conventional ATC calculation methods do not fully consider the impacts of renewable energy integration and the close interdependency among electricity, natural gas, and district heating networks. To overcome these challenges, this work evaluates the ATC in an electricity-gas-heating integrated hybrid energy system (IHES) in a more practical manner by considering renewable energy uncertainties. In the proposed approach, the detailed models of electricity, natural gas, and district heating infrastructures are provided and their operational constraints are fully respected. To reduce input data requirements, the wind power uncertainty is modeled as interval bounds instead of detailed probability distribution functions (PDFs). Consequently, this interval optimization-based ATC model is converted to two sub-problems to solve the lower and upper boundaries of the objective function value. The proposed approach provides a quantitative approach to numerically calculate the impact on ATC from various components in an IHES. Simulation results on the IHES 5–7-6 and the IHES 118–96-6 + 32 systems validate its effectiveness.

Suggested Citation

  • Jiang, Tao & Li, Xue & Kou, Xiao & Zhang, Rufeng & Tian, Guoda & Li, Fangxing, 2022. "Available transfer capability evaluation in electricity-dominated integrated hybrid energy systems with uncertain wind power: An interval optimization solution," Applied Energy, Elsevier, vol. 314(C).
  • Handle: RePEc:eee:appene:v:314:y:2022:i:c:s030626192200410x
    DOI: 10.1016/j.apenergy.2022.119001
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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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    Citations

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    Cited by:

    1. Duan, Jiandong & Liu, Fan & Yang, Yao, 2022. "Optimal operation for integrated electricity and natural gas systems considering demand response uncertainties," Applied Energy, Elsevier, vol. 323(C).
    2. Lei Su & Wenxiang Wu & Wanli Feng & Junda Qin & Yuqi Ao, 2024. "Collaborative Planning of Distribution Network, Data Centres and Renewable Energy in the Power Distribution IoT via Interval Optimization," Energies, MDPI, vol. 17(15), pages 1-26, July.
    3. Zeng, Bo & Zhang, Weixiang & Hu, Pinduan & Sun, Jing & Gong, Dunwei, 2023. "Synergetic renewable generation allocation and 5G base station placement for decarbonizing development of power distribution system: A multi-objective interval evolutionary optimization approach," Applied Energy, Elsevier, vol. 351(C).
    4. Mingguang Zhang & Shuai Yu & Hongyi Li, 2023. "Inter-Zone Optimal Scheduling of Rural Wind–Biomass-Hydrogen Integrated Energy System," Energies, MDPI, vol. 16(17), pages 1-15, August.
    5. Tostado-Véliz, Marcos & Liang, Yingqi & Hasanien, Hany M. & Turky, Rania A. & Martínez-Moreno, Juan & Jurado, Francisco, 2023. "Robust optimal coordination of active distribution networks and energy communities with high penetration of renewables," Renewable Energy, Elsevier, vol. 218(C).
    6. Zhao, Bingxu & Cao, Xiaodong & Duan, Pengfei, 2024. "Cooperative operation of multiple low-carbon microgrids: An optimization study addressing gaming fraud and multiple uncertainties," Energy, Elsevier, vol. 297(C).

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