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A Fuzzy Logic Energy Management Strategy for a Photovoltaic/Diesel/Battery Hybrid Ship Based on Experimental Database

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  • Yupeng Yuan

    (Reliability Engineering Institute, School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China
    Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK
    National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China)

  • Tianding Zhang

    (Reliability Engineering Institute, School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China)

  • Boyang Shen

    (Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK)

  • Xinping Yan

    (National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China)

  • Teng Long

    (Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK)

Abstract

Energy management strategy is a key technology of hybrid power ships. In recent years, renewable energy ship technologies have become a popular research field and one promising development direction to realize reasonable utilization of energy resource, as well as energy conservation and emission reduction. Among these technologies, the solar energy hybrid ship technology is currently attracting attention all over the word. In this paper, a 5000-car space solar energy hybrid ship is used as the research objective, and an energy management strategy that is based on fuzzy logic is proposed to distribute the ship power generation, solar energy, and battery output power according to the ship’s electrical load demand, and the fuzzification and stochasticity of solar energy. By comparing the simulation results with real ship testing results, it is identified that the proposed fuzzy logic energy management strategy can optimize the operation conditions of individual power generation sources, improve the overall performance of power system, and reduce the ship’s overall fuel consumption.

Suggested Citation

  • Yupeng Yuan & Tianding Zhang & Boyang Shen & Xinping Yan & Teng Long, 2018. "A Fuzzy Logic Energy Management Strategy for a Photovoltaic/Diesel/Battery Hybrid Ship Based on Experimental Database," Energies, MDPI, vol. 11(9), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2211-:d:165427
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    References listed on IDEAS

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    Cited by:

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    4. 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).
    5. Yuan, Yupeng & Wang, Jixiang & Yan, Xinping & Shen, Boyang & Long, Teng, 2020. "A review of multi-energy hybrid power system for ships," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    6. Xie, Peilin & Tan, Sen & Bazmohammadi, Najmeh & Guerrero, Josep. M. & Vasquez, Juan. C. & Alcala, Jose Matas & Carreño, Jorge El Mariachet, 2022. "A distributed real-time power management scheme for shipboard zonal multi-microgrid system," Applied Energy, Elsevier, vol. 317(C).
    7. 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).
    8. Park, Chybyung & Jeong, Byongug & Zhou, Peilin & Jang, Hayoung & Kim, Seongwan & Jeon, Hyeonmin & Nam, Dong & Rashedi, Ahmad, 2022. "Live-Life cycle assessment of the electric propulsion ship using solar PV," Applied Energy, Elsevier, vol. 309(C).
    9. Basit Ali & Muhammad Waseem Ashraf & Shahzadi Tayyaba, 2019. "Simulation, Fuzzy Analysis and Development of ZnO Nanostructure-based Piezoelectric MEMS Energy Harvester," Energies, MDPI, vol. 12(5), pages 1-15, February.
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