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Optimal operation of photovoltaic/battery/diesel/cold-ironing hybrid energy system for maritime application

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  • Tang, Ruoli
  • Wu, Zhou
  • Li, Xin

Abstract

Due to emission regulations, the ship is sometimes restricted or even prohibited to use diesel when berthing in port, and the shore power (called the “cold-ironing”) takes part as power supplier. For a green ship with onboard photovoltaic (PV) systems, energy management for maritime PV/battery/diesel/cold-ironing hybrid energy system (HES) can significantly reduce the electricity cost of a ship. In this paper, the optimal operation of HES on a ship is modelled as an optimization problem subject to a number of constraints, including emission regulations of ports. Optimal control and model predictive control (MPC) methods are developed to dispatch the power flow when the ship is in port. Finally, the proposed approaches are tested by simulation experiments for different cases of cold-ironing service prices and emission regulations. Experimental results show that the optimal operation of maritime HES can bring promising electricity cost savings and robustness.

Suggested Citation

  • Tang, Ruoli & Wu, Zhou & Li, Xin, 2018. "Optimal operation of photovoltaic/battery/diesel/cold-ironing hybrid energy system for maritime application," Energy, Elsevier, vol. 162(C), pages 697-714.
  • Handle: RePEc:eee:energy:v:162:y:2018:i:c:p:697-714
    DOI: 10.1016/j.energy.2018.08.048
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    9. Tang, Ruoli & Lin, Qiao & Zhou, Jinxiang & Zhang, Shangyu & Lai, Jingang & Li, Xin & Dong, Zhengcheng, 2020. "Suppression strategy of short-term and long-term environmental disturbances for maritime photovoltaic system," Applied Energy, Elsevier, vol. 259(C).
    10. Inal, Omer Berkehan & Charpentier, Jean-Frédéric & Deniz, Cengiz, 2022. "Hybrid power and propulsion systems for ships: Current status and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
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    12. Trivyza, Nikoletta L. & Rentizelas, Athanasios & Theotokatos, Gerasimos & Boulougouris, Evangelos, 2022. "Decision support methods for sustainable ship energy systems: A state-of-the-art review," Energy, Elsevier, vol. 239(PC).
    13. Carlos A. Reusser & Joel R. Pérez, 2020. "Evaluation of the Emission Impact of Cold-Ironing Power Systems, Using a Bi-Directional Power Flow Control Strategy," Sustainability, MDPI, vol. 13(1), pages 1-16, December.
    14. Al-Falahi, Monaaf D.A. & Jayasinghe, Shantha D.G. & Enshaei, Hossein, 2019. "Hybrid algorithm for optimal operation of hybrid energy systems in electric ferries," Energy, Elsevier, vol. 187(C).
    15. Mewafy, Abdelrahman & Ismael, Islam & Kaddah, Sahar S. & Hu, Weihao & Chen, Zhe & Abulanwar, Sayed, 2024. "Optimal design of multiuse hybrid microgrids power by green hydrogen–ammonia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    16. Xu, Xiao & Hu, Weihao & Cao, Di & Liu, Wen & Huang, Qi & Hu, Yanting & Chen, Zhe, 2021. "Enhanced design of an offgrid PV-battery-methanation hybrid energy system for power/gas supply," Renewable Energy, Elsevier, vol. 167(C), pages 440-456.
    17. He Yin & Hai Lan & Ying-Yi Hong & Zhuangwei Wang & Peng Cheng & Dan Li & Dong Guo, 2023. "A Comprehensive Review of Shipboard Power Systems with New Energy Sources," Energies, MDPI, vol. 16(5), pages 1-44, February.
    18. Muhammad Umair Mutarraf & Yacine Terriche & Kamran Ali Khan Niazi & Fawad Khan & Juan C. Vasquez & Josep M. Guerrero, 2019. "Control of Hybrid Diesel/PV/Battery/Ultra-Capacitor Systems for Future Shipboard Microgrids," Energies, MDPI, vol. 12(18), pages 1-23, September.
    19. Xing, Hui & Spence, Stephen & Chen, Hua, 2020. "A comprehensive review on countermeasures for CO2 emissions from ships," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
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    21. Hossam A. Gabbar & Otavio Lopes Alves Esteves, 2023. "Planning and Evaluation of Nuclear-Renewable Hybrid Energy Penetration for Marine and Waterfront Applications," Energies, MDPI, vol. 16(14), pages 1-16, July.
    22. Tang, Ruoli & Zhang, Shihan & Zhang, Shangyu & Lai, Jingang & Zhang, Yan, 2023. "Semi-online parameter identification methodology for maritime power lithium batteries," Applied Energy, Elsevier, vol. 339(C).

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