Configuration size optimization of gas-electric hybrid power systems on ships considering energy density and engine load response

Wu, Shen; Li, Tie; Xu, Fuguo; Chen, Run; Zhou, Xinyi; Wang, Bing

doi:10.1016/j.enconman.2024.118069

Energy Conversion and Management

2024

DOI: 10.1016/j.enconman.2024.118069

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Configuration size optimization of gas-electric hybrid power systems on ships considering energy density and engine load response

Shen Wu,

Tie Li,

Fuguo Xu

et al.

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2024

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Cited by 3 publications

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Enhancing renewable energy utilization and energy management strategies for new energy yachts

Wang,

Li,

Cao

et al. 2024

Heliyon

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Enhancing renewable energy utilization and energy management strategies for new energy yachts

Wang,

Li,

Cao

et al. 2024

Heliyon

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Energy management system for hybrid ship: Status and perspectives

Guo,

Lang,

Yuan

et al. 2024

Ocean Engineering

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Machine Learning-Based Extraction Method for Marine Load Cycles with Environmentally Sustainable Applications

Sun,

Gao,

Zhang

et al. 2024

Sustainability

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The current lack of harmonized standard test conditions for marine shipping hinders the comparison of performance and compliance assessments for different types of ships. This article puts forward a method for extracting ship loading cycles using machine learning algorithms. Time-series data are extracted from real ships in operation, and a segmented linear approximation method and a data normalization technique are adopted. A hierarchical-clustering type of soft dynamic time-warping similarity analysis method is presented to efficiently analyze the similarity of different time-series data, using soft dynamic time warping (Soft-DTW) combined with hierarchical clustering algorithms from the field of machine learning. The problem of data bias caused by spatial and temporal offset characteristics is effectively solved in marine test condition data. The validity and reliability of the proposed method are validated through the analysis of case data. The results demonstrate that the hierarchically clustered soft dynamic time-warping similarity analysis method can be considered reliable for obtaining test cases with different characteristics. Furthermore, it provides input conditions for effectively identifying the operating conditions of different types of ships with high levels of energy consumption and high emissions, thus allowing for the establishment of energy-saving and emissions-reducing sailing strategies.

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Configuration size optimization of gas-electric hybrid power systems on ships considering energy density and engine load response

Cited by 3 publications

References 25 publications

Enhancing renewable energy utilization and energy management strategies for new energy yachts

Enhancing renewable energy utilization and energy management strategies for new energy yachts

Energy management system for hybrid ship: Status and perspectives

Machine Learning-Based Extraction Method for Marine Load Cycles with Environmentally Sustainable Applications

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