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Optimal and distributed energy management in interconnected energy hubs

Author

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  • Azimi, Maryam
  • Salami, Abolfazl
  • Javadi, Mohammad S.
  • Catalão, João P.S.

Abstract

Recently, multi-carrier energy systems (MCESs) have been rapidly developed as flexible multi-generation systems aiming to satisfy load demands by purchasing, converting, and storing different energy carriers. This study specifically focuses on the optimal and robust large-scale coordination of interconnected energy hubs (IEHs) in an iterative consensus-based procedure considering distribution network losses. Furthermore, a new robust-based hybrid IGDT/consensus algorithm is introduced to achieve risk-averse optimal energy management in IEHs under uncertainty. The fast convergence, needless to collect the total information from all hubs, minimal computational burden, and more robust communication system are the most important features of the proposed distributed consensus algorithm in this study. The effectiveness of the proposed consensus algorithm is verified by simulation results considering various energy trading structures in IEHs at different scales. The obtained results highlight the scalability capability of the proposed method. Regarding an IEHS of 30 energy hubs, the computation burden is lightened by 0.53 (s) and 0.1917 (s), respectively with and without uncertainty. Considering distribution network losses, the total purchasing costs can be increased by 8%. The simulation results also reveal an increase of 11% in the total power trading under the uncertainty.

Suggested Citation

  • Azimi, Maryam & Salami, Abolfazl & Javadi, Mohammad S. & Catalão, João P.S., 2024. "Optimal and distributed energy management in interconnected energy hubs," Applied Energy, Elsevier, vol. 365(C).
    • Handle: RePEc:eee:appene:v:365:y:2024:i:c:s0306261924006652
    DOI: 10.1016/j.apenergy.2024.123282
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    References listed on IDEAS

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    1. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    2. Javadi, Mohammad Sadegh & Esmaeel Nezhad, Ali & Jordehi, Ahmad Rezaee & Gough, Matthew & Santos, Sérgio F. & Catalão, João P.S., 2022. "Transactive energy framework in multi-carrier energy hubs: A fully decentralized model," Energy, Elsevier, vol. 238(PB).
    3. Esmaeil Valipour & Ramin Nourollahi & Kamran Taghizad-Tavana & Sayyad Nojavan & As’ad Alizadeh, 2022. "Risk Assessment of Industrial Energy Hubs and Peer-to-Peer Heat and Power Transaction in the Presence of Electric Vehicles," Energies, MDPI, vol. 15(23), pages 1-24, November.
    4. Zhang, XiaoWei & Yu, Xiaoping & Ye, Xinping & Pirouzi, Sasan, 2023. "Economic energy managementof networked flexi-renewable energy hubs according to uncertainty modeling by the unscented transformation method," Energy, Elsevier, vol. 278(PB).
    5. Lin, Wei & Jin, Xiaolong & Jia, Hongjie & Mu, Yunfei & Xu, Tao & Xu, Xiandong & Yu, Xiaodan, 2021. "Decentralized optimal scheduling for integrated community energy system via consensus-based alternating direction method of multipliers," Applied Energy, Elsevier, vol. 302(C).
    6. Yining Zhang & Yubin He & Mingyu Yan & Chuangxin Guo & Yi Ding, 2018. "Linearized Stochastic Scheduling of Interconnected Energy Hubs Considering Integrated Demand Response and Wind Uncertainty," Energies, MDPI, vol. 11(9), pages 1-23, September.
    7. Wei, Zhenbo & Wei, Pingan & Chen, Chiyao & Gao, Hongjun & Luo, Zihang & Xiang, Yue, 2023. "Two-stage stochastic decentralized low-carbon economic dispatch of integrated electricity-gas networks," Energy, Elsevier, vol. 282(C).
    8. Mu, Chenlu & Ding, Tao & Qu, Ming & Zhou, Quan & Li, Fangxing & Shahidehpour, Mohammad, 2020. "Decentralized optimization operation for the multiple integrated energy systems with energy cascade utilization," Applied Energy, Elsevier, vol. 280(C).
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