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A novel bi-level optimization model-based optimal energy scheduling for hybrid ship power system

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Abstract

With the rapid growth of energy consumption and greenhouse gas emissions, the application of traditional ships brings more and more serious pollution problems to the marine environment. For this reason, this paper aims at developing a novel optimal energy scheduling for hybrid ship power system based on bi-level optimization model to reduce fossil fuel consumption and protect the environment. Firstly, a hybrid ship power system model including the diesel generator system, energy storage system, propulsion system, service load system, and photovoltaic generation system is established. Taking the nonlinear and non-convex constraints in solving power generation scheduling and speed scheduling problems into account, an improved genetic algorithm-based bi-level energy optimization strategy is developed. Considering the mileage constraints in coupling constraints, an upper level model for ship energy scheduling is established with the objective of reducing fuel consumption; a lower level optimization model with the goal of minimizing mileage deviation is established through constraint decomposition and fed back to the upper level optimization model. Considering the normal and fault navigation conditions, simulation results verify that the proposed method can significantly minimize operating costs and greenhouse gas emissions by 5.33% and 2.46%, respectively.

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Acknowledgments

This work is supported by National Nature Science Foundation of China under 61873228 and 62103357, and by the Science and Technology Plan of Hebei Education Department under QN2021139, and by the Nature Science Foundation of Hebei Province under F2021203043, and by the Open Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing Institute of Technology No.XTCX202203.

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Authors and Affiliations

  1. School of Electrical and Control Engineering, Yanshan University, Qinhuangdao, 066003, China

    Xinyu Wang, Zibin Li, Xiaoyuan Luo, Shaoping Chang & Hongyu Zhu

  2. Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing, 210000, China

    Xinyu Wang & Shuzheng Wang

  3. School of Electronic and Electric Engineering, Shanghai Jiaotong University, Shanghai, 200240, China

    Xinping Guan

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  1. Xinyu Wang
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  2. Zibin Li
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  4. Shaoping Chang
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  5. Hongyu Zhu
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Contributions

XW contributed toward conceptualization (equal); data curation (equal); formal analysis (equal); investigation (equal); methodology (equal); resources (equal); software (equal); supervision (equal); validation (equal); visualization (equal); writing – original draft (equal); and writing – review & editing (equal). ZL contributed toward conceptualization (equal); data curation (equal); formal analysis (equal); investigation (equal); methodology (equal); resources (equal); software (equal); supervision (equal); writing – original draft (equal); and writing – review & editing (equal). XL contributed toward conceptualization (equal); data curation (equal); formal analysis (equal); investigation (equal); methodology (equal); and resources (equal). SC contributed toward software (equal); supervision (equal); and validation (equal). HZ contributed toward software (equal); supervision (equal); and validation (equal). XG contributed toward supervision (equal) and writing – review & editing (equal). SW contributed toward formal analysis (equal); and investigation (equal).

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Correspondence to Xinyu Wang.

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Wang, X., Li, Z., Luo, X. et al. A novel bi-level optimization model-based optimal energy scheduling for hybrid ship power system. MRS Energy & Sustainability 10, 247–260 (2023). https://doi.org/10.1557/s43581-023-00068-w

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