IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v347y2026ics0360544226004469.html

A novel fuel consumption optimization strategy for the wind-assisted hybrid power ship considering sea conditions

Author

Listed:
  • Liang, Hongzhi
  • Wang, Kai
  • Liu, Xing
  • Xing, Hui
  • Li, Zhongwei
  • Jing, Zesheng
  • Wang, Yapeng
  • Cao, Jianlin

Abstract

With increasingly rigorous emission regulations, the shipping industry urgently needs to advance clean energy technologies to reduce greenhouse gas (GHG) emissions. The wind-assisted hybrid power (WAHP) ship can achieve effective reduction in fuel consumption and carbon emissions by using wind energy. However, the fuel consumption status of the WAHP ship is not only influenced by complex navigational environments, but also closely related to the operational status of the hybrid system. In order to improve the ship energy efficiency, the influencing factors for the fuel consumption of the WAHP ship are firstly analyzed. Then, an integrated fuel consumption model of the hybrid system is established. On these foundations, a rule-based optimization control strategy for the hybrid system that combines main engine, shaft generator, and energy storage device is proposed to reduce the ship fuel consumption. The analysis results show that the proposed optimization strategy can effectively enhance the energy efficiency of the WAHP ship, which can reduce fuel consumption by approximately 2.7% compared with the original operational mode of the WAHP ship.

Suggested Citation

  • Liang, Hongzhi & Wang, Kai & Liu, Xing & Xing, Hui & Li, Zhongwei & Jing, Zesheng & Wang, Yapeng & Cao, Jianlin, 2026. "A novel fuel consumption optimization strategy for the wind-assisted hybrid power ship considering sea conditions," Energy, Elsevier, vol. 347(C).
    • Handle: RePEc:eee:energy:v:347:y:2026:i:c:s0360544226004469
    DOI: 10.1016/j.energy.2026.140343
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544226004469
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2026.140343?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Leloup, R. & Roncin, K. & Behrel, M. & Bles, G. & Leroux, J.-B. & Jochum, C. & Parlier, Y., 2016. "A continuous and analytical modeling for kites as auxiliary propulsion devoted to merchant ships, including fuel saving estimation," Renewable Energy, Elsevier, vol. 86(C), pages 483-496.
    2. Yan, Ran & Yang, Dong & Wang, Tianyu & Mo, Haoyu & Wang, Shuaian, 2024. "Improving ship energy efficiency: Models, methods, and applications," Applied Energy, Elsevier, vol. 368(C).
    3. Luo, Xi & Yan, Ran & Xu, Lang & Wang, Shuaian, 2024. "Accuracy and applicability of ship's fuel consumption prediction models: A comprehensive comparative analysis," Energy, Elsevier, vol. 310(C).
    4. Marcin Kolodziejski & Mariusz Sosnowski, 2025. "Review of Wind-Assisted Propulsion Systems in Maritime Transport," Energies, MDPI, vol. 18(4), pages 1-33, February.
    5. Lan, Tian & Huang, Lianzhong & Cao, Jianlin & Ma, Ranqi & Zhao, Haoyang & Ruan, Zhang & Wu, Jianyi & Li, Xiaowu & Wang, Kai, 2025. "A pioneering approach for improving ship operational energy efficiency: The quantitative application of deep learning interpretable results," Applied Energy, Elsevier, vol. 400(C).
    6. Zhu, Jianyun & Chen, Li, 2023. "A probabilistic multi-objective design method of sail-photovoltaic-hybrid power system for an unmanned ocean surveillance trimaran," Applied Energy, Elsevier, vol. 350(C).
    7. Lan, Tian & Huang, Lianzhong & Ruan, Zhang & Cao, Jianlin & Ma, Ranqi & Wu, Jianyi & Li, Xiaowu & Chen, Li & Wang, Kai, 2025. "Multilevel parallel integration framework for enhancing energy efficiency of wing-assisted ships based on deep learning and intelligent algorithms: Towards a smarter and greener shipping," Applied Energy, Elsevier, vol. 394(C).
    8. Wang, Kai & Li, Zhongwei & Liu, Xing & Hu, Zhiqiang & Huang, Lianzhong & Song, Qiushi & Liang, Hongzhi & Jiang, Xiaoli, 2025. "Wind-assisted propulsion system for shipping decarbonization: Technologies, applications and challenges," Energy, Elsevier, vol. 336(C).
    9. Jingang Han & Jean-Frederic Charpentier & Tianhao Tang, 2014. "An Energy Management System of a Fuel Cell/Battery Hybrid Boat," Energies, MDPI, vol. 7(5), pages 1-22, April.
    10. Yang, Qi & Zhang, Shengchao & Zhao, Wenhai & Tao, Jie & Lu, Xiqun & Meng, Chao & Zhao, Yingru & Zhang, Hengcheng & Zhao, Guofeng & Jiang, Chenxing & Li, Wanyou, 2025. "A two-stage energy management strategy for hybrid ship power systems considering the dynamic output characteristics of batteries," Applied Energy, Elsevier, vol. 396(C).
    11. Patrizia Serra & Gianfranco Fancello, 2020. "Towards the IMO’s GHG Goals: A Critical Overview of the Perspectives and Challenges of the Main Options for Decarbonizing International Shipping," Sustainability, MDPI, vol. 12(8), pages 1-32, April.
    12. 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).
    13. Tan, Xianlin & Tuo, Xiaoyu & Huang, Guanhua & Ouyang, Tiancheng, 2026. "Model predictive control-based energy management strategy for ocean-going ship direct current microgrid considering waste heat utilization," Applied Energy, Elsevier, vol. 402(PB).
    14. Wang, Kai & Li, Zhongwei & Zhang, Rui & Ma, Ranqi & Huang, Lianzhong & Wang, Zhuang & Jiang, Xiaoli, 2025. "Computational fluid dynamics-based ship energy-saving technologies: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    15. Wang, Zhuang & Chen, Li & Huang, Lianzhong & Wang, Kai & Ma, Ranqi & Wang, Bin, 2025. "A novel multivariable coupling optimization method of wind-assisted propulsion system for a large crude carrier," Energy, Elsevier, vol. 322(C).
    16. Yilmaz, Naz & Bordogna, Giovanni & Aktas, Batuhan, 2026. "Numerical investigations of aerodynamic performance for flettner rotors in the presence of full-scale ship-rotor interaction," Renewable Energy, Elsevier, vol. 256(PF).
    17. Geertsma, R.D. & Negenborn, R.R. & Visser, K. & Hopman, J.J., 2017. "Design and control of hybrid power and propulsion systems for smart ships: A review of developments," Applied Energy, Elsevier, vol. 194(C), pages 30-54.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Kai & Li, Zhongwei & Liu, Xing & Hu, Zhiqiang & Huang, Lianzhong & Song, Qiushi & Liang, Hongzhi & Jiang, Xiaoli, 2025. "Wind-assisted propulsion system for shipping decarbonization: Technologies, applications and challenges," Energy, Elsevier, vol. 336(C).
    2. Lan, Tian & Huang, Lianzhong & Ruan, Zhang & Cao, Jianlin & Ma, Ranqi & Wu, Jianyi & Li, Xiaowu & Chen, Li & Wang, Kai, 2025. "Multilevel parallel integration framework for enhancing energy efficiency of wing-assisted ships based on deep learning and intelligent algorithms: Towards a smarter and greener shipping," Applied Energy, Elsevier, vol. 394(C).
    3. Lu, Wenyi & Xu, Huijin & Yu, Guojun, 2025. "Advances in modelling and optimization of thermoelectric generators for harvesting waste heat in hybrid-powered marine vessels: From materials to energy management systems," Energy, Elsevier, vol. 341(C).
    4. Du, Zhipeng & Chen, Xiaolong & Zheng, Xin & Chen, Mengshan & Chen, Hui, 2026. "Adaptive dual-layer MPC for real-time energy management of an inland diesel–LNG–battery vessel on the Yangtze River," Energy, Elsevier, vol. 344(C).
    5. Sun, Xiaojun & Yao, Chong & Song, Enzhe & Yang, Qidong & Yang, Xuchang, 2022. "Optimal control of transient processes in marine hybrid propulsion systems: Modeling, optimization and performance enhancement," Applied Energy, Elsevier, vol. 321(C).
    6. Orestis Schinas & Niklas Bergmann, 2021. "The Short-Term Cost of Greening the Global Fleet," Sustainability, MDPI, vol. 13(16), pages 1-32, August.
    7. Guarnieri, Massimo & Bovo, Angelo & Zatta, Nicolò & Trovò, Andrea, 2024. "Design, construction and operation of a special electric vessel for water-city utilities service," Energy, Elsevier, vol. 309(C).
    8. Zhang, Rui & Huang, Lianzhong & Chen, Jijun & Peng, Guisheng & Ma, Ranqi & Cao, Jianlin & Wang, Cong & Wu, Jianyi & Li, Xiaowu, 2025. "A novel energy conservation method for wind-assisted propulsion ships based on sails thrust optimization," Energy, Elsevier, vol. 340(C).
    9. Tino Vidović & Jakov Šimunović & Gojmir Radica & Željko Penga, 2023. "Systematic Overview of Newly Available Technologies in the Green Maritime Sector," Energies, MDPI, vol. 16(2), pages 1-26, January.
    10. Mir Md Ashfaque Sumon & Hyungju Kim & Børge Rokseth, 2025. "Hazard analysis of autonomous vessel operation during the interaction and execution between remote operation centre controller and onboard controllers," Journal of Shipping and Trade, Springer, vol. 10(1), pages 1-30, December.
    11. Chiara Dall’Armi & Davide Pivetta & Rodolfo Taccani, 2023. "Hybrid PEM Fuel Cell Power Plants Fuelled by Hydrogen for Improving Sustainability in Shipping: State of the Art and Review on Active Projects," Energies, MDPI, vol. 16(4), pages 1-34, February.
    12. Chen, Hui & Zhang, Zehui & Guan, Cong & Gao, Haibo, 2020. "Optimization of sizing and frequency control in battery/supercapacitor hybrid energy storage system for fuel cell ship," Energy, Elsevier, vol. 197(C).
    13. Nuchturee, Chalermkiat & Li, Tie & Xia, Hongpu, 2020. "Energy efficiency of integrated electric propulsion for ships – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    14. Wang, Kai & Li, Zhongwei & Zhang, Rui & Ma, Ranqi & Huang, Lianzhong & Wang, Zhuang & Jiang, Xiaoli, 2025. "Computational fluid dynamics-based ship energy-saving technologies: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    15. Ruan, Zhang & Huang, Lianzhong & Li, Daize & Ma, Ranqi & Wang, Kai & Zhang, Rui & Zhao, Haoyang & Wu, Jianyi & Li, Xiaowu, 2025. "A novel dual-stage grey-box stacking method for significantly improving the extrapolation performance of ship fuel consumption prediction models," Energy, Elsevier, vol. 318(C).
    16. Lan, Tian & Huang, Lianzhong & Cao, Jianlin & Ma, Ranqi & Zhao, Haoyang & Ruan, Zhang & Wu, Jianyi & Li, Xiaowu & Wang, Kai, 2025. "A pioneering approach for improving ship operational energy efficiency: The quantitative application of deep learning interpretable results," Applied Energy, Elsevier, vol. 400(C).
    17. Feng, Longxiang & Sun, Yuwei & Tang, Xujing & Yuan, Chengqing & Yin, Huabing & Luo, Wenjun, 2026. "Review on the development and challenges of clean energy sources for ships," Renewable and Sustainable Energy Reviews, Elsevier, vol. 225(C).
    18. Barone, Giovanni & Buonomano, Annamaria & Del Papa, Gianluca & Giuzio, Giovanni Francesco & Maka, Robert & Palombo, Adolfo & Russo, Giuseppe, 2026. "Pathways to maritime decarbonisation: analysing alternative fuels across vessel classes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 229(C).
    19. Rashed Kaiser & Ayesha Munira Chowdhury, 2025. "Hydrogen-Powered Marine Vessels: A Rewarding yet Challenging Route to Decarbonization," Clean Technol., MDPI, vol. 7(3), pages 1-29, August.
    20. 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).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:347:y:2026:i:c:s0360544226004469. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.