An integrated multi-objective optimization, evaluation, and decision-making method for ship energy system

Nianyuan Wu, Fang Zhang, Fuzheng Zhang, Chenxing Jiang, Jian Lin, Shan Xie, Rui Jing and Yingru Zhao

Applied Energy, 2024, vol. 373, issue C, No S030626192401300X

Abstract: With the rapid development of global shipping industry, the energy conservation and emission reduction issue of ships has received increasing attention from the international community. A series of regulations released by the International Maritime Organization (IMO) have greatly stimulated the related research. However, the mechanism of optimization design and evaluation of marine ship energy system at the whole ship level based on the comprehensive consideration of various performance of ships is still unclear. In the present study, an integrated modeling method of multi-objective optimization and evaluation for ship energy system are proposed to optimize the design of ship energy system. This paper constructs a technical selection, capacity allocation, and operational optimization model for ship energy systems using mixed-integer nonlinear programming (MINLP) method. Based on determining relevant constraints and multiple objective functions, the data envelopment analysis (DEA) method is introduced to evaluate and make decisions on the multi-objective optimization results, and compared with traditional decision-making method. The economic optimization results show that the net present cost of ship energy system can be reduced by 20%, while the NOx, SOx and CO2 emissions of the system are reduced by 41%, 20% and 32%, respectively. Moreover, the energy efficiency of the optimized ship energy system is improved by 9% compared to the conventional ship energy system. In summary, the proposed method can effectively identify the advantages and disadvantages of different solutions, therefore provide more design options of sub-optimal schemes for decision makers.

Keywords: Ship energy system; Mixed-integer nonlinear programming; Multi-objective optimization; Data envelopment analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123917

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