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Bi-Level Resilience-Oriented Sitting and Sizing of Energy Hubs in Electrical, Thermal and Gas Networks Considering Energy Management System

Author

Listed:
  • Dhafer M. Dahis

    (Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz 61357-85311, Iran)

  • Seyed Saeedallah Mortazavi

    (Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz 61357-85311, Iran)

  • Mahmood Joorabian

    (Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz 61357-85311, Iran)

  • Alireza Saffarian

    (Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz 61357-85311, Iran)

Abstract

In this article, the planning and energy administration of energy hubs in electric, thermal and gas networks are presented, considering the resilience of the system against natural phenomena like floods and earthquakes. Each hub consists of bio-waste, wind and solar renewable units. These include non-renewable units such as boilers and combined heat and power (CHP) units. Compressed air and thermal energy storage are used in each hub. The design is formed as a bi-level optimization framework. In the upper level of the scheme, the energy management of networks bound to system resiliency is provided. This considers the minimization of annual operating and resilience costs based on optimal power flow equations in networks. In the lower-level model, the planning (placement and sizing) of hubs is considered. This minimizes the total building and operation costs of hubs based on the operation-planning equations for power supplies and storages. Scenario-based stochastic optimization models are used to determine the uncertainties of demand, the power of renewable systems, energy price and the accessibility of distribution networks’ elements against natural disasters. In this study, the Karush–Kuhn–Tucker technique is used to extract the single-level formulation. A numerical report for case studies verifies the potential of the plan to enhance the economic, operation and resilience status of networks with energy administration and the optimal planning of hubs in the mentioned networks. By determining the optimal capacity for resources and storage in the hubs located in the optimal places and the optimal energy administration of the hubs, the economic, exploitation and resilience situation of the networks are improved by about 27.1%, 97.7% and 23–50%, respectively, compared to load flow studies.

Suggested Citation

  • Dhafer M. Dahis & Seyed Saeedallah Mortazavi & Mahmood Joorabian & Alireza Saffarian, 2025. "Bi-Level Resilience-Oriented Sitting and Sizing of Energy Hubs in Electrical, Thermal and Gas Networks Considering Energy Management System," Energies, MDPI, vol. 18(10), pages 1-26, May.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:10:p:2569-:d:1656695
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    References listed on IDEAS

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    1. Abdulnasser, Ghada & Ali, Abdelfatah & Shaaban, Mostafa F. & Mohamed, Essam E.M., 2024. "Optimal resource allocation and operation for smart energy hubs considering hydrogen storage systems and electric vehicles," Energy, Elsevier, vol. 295(C).
    2. Sina Parhoudeh & Pablo Eguía López & Abdollah Kavousi Fard, 2023. "Stochastic Coordinated Management of Electrical–Gas–Thermal Networks in Flexible Energy Hubs Considering Day-Ahead Energy and Ancillary Markets," Sustainability, MDPI, vol. 15(13), pages 1-26, July.
    3. Liang, Hejun & Pirouzi, Sasan, 2024. "Energy management system based on economic Flexi-reliable operation for the smart distribution network including integrated energy system of hydrogen storage and renewable sources," Energy, Elsevier, vol. 293(C).
    4. AkbaiZadeh, MohammadReza & Niknam, Taher & Kavousi-Fard, Abdollah, 2021. "Adaptive robust optimization for the energy management of the grid-connected energy hubs based on hybrid meta-heuristic algorithm," Energy, Elsevier, vol. 235(C).
    5. Tiwari, Shubham & Singh, Jai Govind & Garg, Ankit, 2024. "A static robust energy management approach for modelling low emission multi-vectored energy hub including emission markets and power-to-gas units," Energy, Elsevier, vol. 294(C).
    6. Xu, Sheng & Tu, Haicheng & Xia, Yongxiang, 2023. "Resilience enhancement of renewable cyber–physical power system against malware attacks," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    7. Zafarani, Hamidreza & Taher, Seyed Abbas & Shahidehpour, Mohammad, 2020. "Robust operation of a multicarrier energy system considering EVs and CHP units," Energy, Elsevier, vol. 192(C).
    8. Norouzi, Mohammadali & Aghaei, Jamshid & Niknam, Taher & Alipour, Mohammadali & Pirouzi, Sasan & Lehtonen, Matti, 2023. "Risk-averse and flexi-intelligent scheduling of microgrids based on hybrid Boltzmann machines and cascade neural network forecasting," Applied Energy, Elsevier, vol. 348(C).
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