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  • 标题:Optimisation of a Diesel-Electric Ship Propulsion and Power Generation System Using a Genetic Algorithm
  • 本地全文:下载
  • 作者:Raphael Zaccone ; Ugo Campora ; Michele Martelli
  • 期刊名称:Journal of Marine Science and Engineering
  • 电子版ISSN:2077-1312
  • 出版年度:2021
  • 卷号:9
  • 期号:6
  • 页码:587
  • DOI:10.3390/jmse9060587
  • 语种:English
  • 出版社:MDPI AG
  • 摘要:In recent decades, the design of ship propulsion systems has been focusing on energy efficiency and low pollutant emissions. In this framework, diesel–electric propulsion has become a standard for many ship types and has proven its worth for flexible propulsion design and management. This paper presents an approach to the optimal design of diesel–electric propulsion systems, minimising the fuel consumption while meeting the power and speed requirements. A genetic algorithm performs the optimisation, used to determine the number and type of engines installed on-board and the engines’ design speed and power, selecting within a dataset of four-stroke diesel engines. The same algorithm is then adapted and applied to determine the optimal load sharing strategy in off-design conditions, taking advantage of the high flexibility of the diesel–electric propulsion plants. In order to apply the algorithm, the propulsion layout design is formulated as an optimisation problem, translating the system requirements into a cost function and a set of linear and non-linear constraints. Eventually, the method is applied to a case study vessel: first, the optimal diesel–electric propulsion plants are determined, then the optimal off-design load sharing and working conditions are computed. AC and DC network solutions are compared and critically discussed in both design and off-design conditions.
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