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Coordinated energy management strategy for multi-energy hub with thermo-electrochemical effect based power-to-ammonia: A multi-agent deep reinforcement learning enabled approach

Author

Listed:
  • Xiong, Kang
  • Hu, Weihao
  • Cao, Di
  • Li, Sichen
  • Zhang, Guozhou
  • Liu, Wen
  • Huang, Qi
  • Chen, Zhe

Abstract

Power-to-ammonia (P2A) technology has attracted more and more attention since ammonia is recognized as a natural zero-carbon fuel. In this context, this paper constructs a renewable energy powered multi-energy hub (MEH) system which integrates with a thermo-electrochemical effect based P2A facility. Subsequently, the energy management of proposed MEH system is casted to a multi-agent coordinated optimization problem, which aims to minimize operating cost and carbon dioxide emissions while satisfying constraints. Then, a novel multi-agent deep reinforcement learning method called CommNet is applied to solve this problem to obtain the optimal coordinated energy management strategy of each energy hub by achieving the distributed computation of global information. Finally, the simulation results show that the proposed method can achieve better performance on reducing operating cost and carbon emissions than other benchmark methods.

Suggested Citation

  • Xiong, Kang & Hu, Weihao & Cao, Di & Li, Sichen & Zhang, Guozhou & Liu, Wen & Huang, Qi & Chen, Zhe, 2023. "Coordinated energy management strategy for multi-energy hub with thermo-electrochemical effect based power-to-ammonia: A multi-agent deep reinforcement learning enabled approach," Renewable Energy, Elsevier, vol. 214(C), pages 216-232.
    • Handle: RePEc:eee:renene:v:214:y:2023:i:c:p:216-232
    DOI: 10.1016/j.renene.2023.05.067
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    as
    1. Zhang, Hanfei & Wang, Ligang & Van herle, Jan & Maréchal, François & Desideri, Umberto, 2020. "Techno-economic comparison of green ammonia production processes," Applied Energy, Elsevier, vol. 259(C).
    2. Zhang, Bin & Hu, Weihao & Xu, Xiao & Li, Tao & Zhang, Zhenyuan & Chen, Zhe, 2022. "Physical-model-free intelligent energy management for a grid-connected hybrid wind-microturbine-PV-EV energy system via deep reinforcement learning approach," Renewable Energy, Elsevier, vol. 200(C), pages 433-448.
    3. Bisengimana, Emmanuel & Zhou, Jinzhi & Binama, Maxime & Yuan, Yanping, 2022. "Numerical investigation on the factors influencing the temperature distribution of photovoltaic/thermal (PVT) evaporator/condenser for heat pump systems," Renewable Energy, Elsevier, vol. 194(C), pages 885-901.
    4. Zhou, Yanting & Ma, Zhongjing & Zhang, Jinhui & Zou, Suli, 2022. "Data-driven stochastic energy management of multi energy system using deep reinforcement learning," Energy, Elsevier, vol. 261(PA).
    5. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Yang, Shanlin, 2020. "A robust optimization approach for coordinated operation of multiple energy hubs," Energy, Elsevier, vol. 197(C).
    6. Zhu, Dafeng & Yang, Bo & Liu, Qi & Ma, Kai & Zhu, Shanying & Ma, Chengbin & Guan, Xinping, 2020. "Energy trading in microgrids for synergies among electricity, hydrogen and heat networks," Applied Energy, Elsevier, vol. 272(C).
    7. Magadley, Esther & Kabha, Ragheb & Yehia, Ibrahim, 2021. "Outdoor comparison of two organic photovoltaic panels: The effect of solar incidence angles and incident irradiance," Renewable Energy, Elsevier, vol. 173(C), pages 721-732.
    8. Fasihi, Mahdi & Weiss, Robert & Savolainen, Jouni & Breyer, Christian, 2021. "Global potential of green ammonia based on hybrid PV-wind power plants," Applied Energy, Elsevier, vol. 294(C).
    9. Zhu, Dafeng & Yang, Bo & Liu, Yuxiang & Wang, Zhaojian & Ma, Kai & Guan, Xinping, 2022. "Energy management based on multi-agent deep reinforcement learning for a multi-energy industrial park," Applied Energy, Elsevier, vol. 311(C).
    10. Mulleriyawage, U.G.K. & Shen, W.X., 2021. "Impact of demand side management on optimal sizing of residential battery energy storage system," Renewable Energy, Elsevier, vol. 172(C), pages 1250-1266.
    11. Behzadi, Amirmohammad & Habibollahzade, Ali & Ahmadi, Pouria & Gholamian, Ehsan & Houshfar, Ehsan, 2019. "Multi-objective design optimization of a solar based system for electricity, cooling, and hydrogen production," Energy, Elsevier, vol. 169(C), pages 696-709.
    12. Heidari, A. & Mortazavi, S.S. & Bansal, R.C., 2020. "Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies," Applied Energy, Elsevier, vol. 261(C).
    13. Zakaria, A. & Ismail, Firas B. & Lipu, M.S. Hossain & Hannan, M.A., 2020. "Uncertainty models for stochastic optimization in renewable energy applications," Renewable Energy, Elsevier, vol. 145(C), pages 1543-1571.
    14. Cao, Di & Zhao, Junbo & Hu, Weihao & Ding, Fei & Yu, Nanpeng & Huang, Qi & Chen, Zhe, 2022. "Model-free voltage control of active distribution system with PVs using surrogate model-based deep reinforcement learning," Applied Energy, Elsevier, vol. 306(PA).
    15. Lee, Joseph C.Y. & Draxl, Caroline & Berg, Larry K., 2022. "Evaluating wind speed and power forecasts for wind energy applications using an open-source and systematic validation framework," Renewable Energy, Elsevier, vol. 200(C), pages 457-475.
    16. Chen, Yuzhu & Hu, Xiaojian & Xu, Wentao & Xu, Qiliang & Wang, Jun & Lund, Peter D., 2022. "Multi-objective optimization of a solar-driven trigeneration system considering power-to-heat storage and carbon tax," Energy, Elsevier, vol. 250(C).
    17. Zhong, Like & Yao, Erren & Zou, Hansen & Xi, Guang, 2022. "Thermodynamic and economic analysis of a directly solar-driven power-to-methane system by detailed distributed parameter method," Applied Energy, Elsevier, vol. 312(C).
    18. Zhu, Dafeng & Yang, Bo & Ma, Chengbin & Wang, Zhaojian & Zhu, Shanying & Ma, Kai & Guan, Xinping, 2022. "Stochastic gradient-based fast distributed multi-energy management for an industrial park with temporally-coupled constraints," Applied Energy, Elsevier, vol. 317(C).
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