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A novel optimal energy-management strategy for a maritime hybrid energy system based on large-scale global optimization

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  • Tang, Ruoli
  • Li, Xin
  • Lai, Jingang

Abstract

In the hybrid energy system of large green ships, different types of energy sources are employed to feed the electricity demand. An optimal energy-management model and control methodology must be developed to obtain operational safety and efficiency. In this study, optimal power-flow dispatching of maritime photovoltaic/battery/diesel/cold-ironing hybrid energy systems is proposed to sufficiently explore solar energy and minimize the ship’s electricity cost. By modelling the constraints (such as power balance, solar output, diesel output, battery capacity, and regulations from the port) as penalty functions, the optimal energy-management is described as an unconstrained, large-scale, global optimization problem, which can be effectively solved by the proposed adaptive multi-context cooperatively coevolving particle swarm optimization algorithm. The proposed approach is verified by simulation for different cases. Results of the simulation show that the optimal energy-management of the evaluated system can be obtained with great electricity cost savings and robust control performance.

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  • Tang, Ruoli & Li, Xin & Lai, Jingang, 2018. "A novel optimal energy-management strategy for a maritime hybrid energy system based on large-scale global optimization," Applied Energy, Elsevier, vol. 228(C), pages 254-264.
    • Handle: RePEc:eee:appene:v:228:y:2018:i:c:p:254-264
    DOI: 10.1016/j.apenergy.2018.06.092
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    8. Yin, He & Wu, Jinghu & Zhang, Gang & Lan, Hai & Hong, Ying-Yi & Li, Dan, 2024. "Variable time-scale power scheduling of a River-Sea going renewable energy ship considering coupling variations in all-electric propulsion," Applied Energy, Elsevier, vol. 374(C).
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    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).
    20. Yi’an Wang & Zhe Wu & Dong Ni, 2024. "Large-Scale Optimization among Photovoltaic and Concentrated Solar Power Systems: A State-of-the-Art Review and Algorithm Analysis," Energies, MDPI, vol. 17(17), pages 1-38, August.
    21. Tang, Ruoli & Zhang, Shangyu & Zhang, Shihan & Zhang, Yan & Lai, Jingang, 2023. "Parameter identification for lithium batteries: Model variable-coupling analysis and a novel cooperatively coevolving identification algorithm," Energy, Elsevier, vol. 263(PB).
    22. Bagherabadi, Kamyar Maleki & Skjong, Stian & Bruinsma, Jogchum & Pedersen, Eilif, 2023. "Investigation of hybrid power plant configurations for an offshore vessel with co-simulation approach," Applied Energy, Elsevier, vol. 343(C).
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