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Transactive energy framework in multi-carrier energy hubs: A fully decentralized model

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  • Javadi, Mohammad Sadegh
  • Esmaeel Nezhad, Ali
  • Jordehi, Ahmad Rezaee
  • Gough, Matthew
  • Santos, Sérgio F.
  • Catalão, João P.S.

Abstract

This paper investigates a fully decentralized model for electricity trading within a transactive energy market. The proposed model presents a peer-to-peer (P2P) trading framework between the clients. The model is incorporated for industrial, commercial, and residential energy hubs to serve their associated demands in a least-cost paradigm. The alternating direction method of multipliers (ADMM) is implemented to address the decentralized power flow in this study. The optimal operation of the energy hubs is modeled as a standard mixed-integer linear programming (MILP) optimization problem. The corresponding decision variables of the energy hubs operation are transferred to the peer-to-peer (P2P) market, and ADMM is applied to ensure the minimum data exchange and address the data privacy issue. Two different scenarios have been studied in this paper to show the effectiveness of the electricity trading model between peers, called integrated and coordinated operation modes. In the integration mode, there is no P2P energy trading while in the coordinated framework, the P2P transactive energy market is taken into account. The proposed model is simulated on the modified IEEE 33-bus distribution network. The obtained results confirm that the coordinated model can efficiently handle the P2P transactive energy trading for different energy hubs, addressing the minimum data exchange issue, and achieving the least-cost operation of the energy hubs in the system. The obtained results show that the total operating cost of the hubs in the coordinated model is lower than that of the integrated model by $590.319, i.e. 11.75 % saving in the costs. In this regard, the contributions of the industrial, commercial, and residential hubs in the total cost using the integrated model are $3441.895, $596.600, and $988.789, respectively. On the other hand, these energy hubs contribute to the total operating cost in the coordinated model by $2932.645, $590.155, and $914.165 respectively. The highest decrease relates to the industrial hub by 14.8 % while the smallest decrease relates to the residential hub by 1 %. Furthermore, the load demand in the integrated and coordinated models is mitigated by 13 % and 17 %, respectively. These results indicate that the presented framework could effectively and significantly reduce the total load demand which in turn leads to reducing the total cost and power losses.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:238:y:2022:i:pb:s0360544221019654
    DOI: 10.1016/j.energy.2021.121717
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    References listed on IDEAS

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    2. Alizadeh, Ali & Esfahani, Moein & Dinar, Farid & Kamwa, Innocent & Moeini, Ali & Mohseni-Bonab, Seyed Masoud & Busvelle, Eric, 2024. "A cooperative transactive multi-carrier energy control mechanism with P2P energy + reserve trading using Nash bargaining game theory under renewables uncertainty," Applied Energy, Elsevier, vol. 353(PB).
    3. Mansouri, S.A. & Ahmarinejad, A. & Nematbakhsh, E. & Javadi, M.S. & Esmaeel Nezhad, A. & Catalão, J.P.S., 2022. "A sustainable framework for multi-microgrids energy management in automated distribution network by considering smart homes and high penetration of renewable energy resources," Energy, Elsevier, vol. 245(C).
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    6. Li, Li & Dong, Mi & Song, Dongran & Yang, Jian & Wang, Qibing, 2022. "Distributed and real-time economic dispatch strategy for an islanded microgrid with fair participation of thermostatically controlled loads," Energy, Elsevier, vol. 261(PB).
    7. Hua, Zhihao & Li, Jiayong & Zhou, Bin & Or, Siu Wing & Chan, Ka Wing & Meng, Yunfan, 2022. "Game-theoretic multi-energy trading framework for strategic biogas-solar renewable energy provider with heterogeneous consumers," Energy, Elsevier, vol. 260(C).
    8. Mehdinejad, Mehdi & Shayanfar, Heidarali & Mohammadi-Ivatloo, Behnam, 2022. "Decentralized blockchain-based peer-to-peer energy-backed token trading for active prosumers," Energy, Elsevier, vol. 244(PA).
    9. Hussain, Sadam & Azim, M. Imran & Lai, Chunyan & Eicker, Ursula, 2023. "New coordination framework for smart home peer-to-peer trading to reduce impact on distribution transformer," Energy, Elsevier, vol. 284(C).
    10. Liu, Zhouding & Nazari-Heris, Morteza, 2023. "Optimal bidding strategy of multi-carrier systems in electricity markets using information gap decision theory," Energy, Elsevier, vol. 280(C).
    11. Neeraj Gupta & B Rajanarayan Prusty & Omar Alrumayh & Abdulaziz Almutairi & Talal Alharbi, 2022. "The Role of Transactive Energy in the Future Energy Industry: A Critical Review," Energies, MDPI, vol. 15(21), pages 1-24, October.
    12. Noorollahi, Younes & Golshanfard, Aminabbas & Hashemi-Dezaki, Hamed, 2022. "A scenario-based approach for optimal operation of energy hub under different schemes and structures," Energy, Elsevier, vol. 251(C).
    13. Lee, Won-Poong & Han, Dongjun & Won, Dongjun, 2022. "Grid-Oriented Coordination Strategy of Prosumers Using Game-theoretic Peer-to-Peer Trading Framework in Energy Community," Applied Energy, Elsevier, vol. 326(C).
    14. Zhou, Yanting & Ma, Zhongjing & Shi, Xingyu & Zou, Suli, 2024. "Multi-agent optimal scheduling for integrated energy system considering the global carbon emission constraint," Energy, Elsevier, vol. 288(C).
    15. Zhong, Xiaoqing & Zhong, Weifeng & Liu, Yi & Yang, Chao & Xie, Shengli, 2023. "A communication-efficient coalition graph game-based framework for electricity and carbon trading in networked energy hubs," Applied Energy, Elsevier, vol. 329(C).
    16. Qiu, Dawei & Xue, Juxing & Zhang, Tingqi & Wang, Jianhong & Sun, Mingyang, 2023. "Federated reinforcement learning for smart building joint peer-to-peer energy and carbon allowance trading," Applied Energy, Elsevier, vol. 333(C).
    17. 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).
    18. Alizadeh, Ali & Kamwa, Innocent & Moeini, Ali & Mohseni-Bonab, Seyed Masoud, 2023. "Energy management in microgrids using transactive energy control concept under high penetration of Renewables; A survey and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).

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