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Genetic research

Real-Time Power Optimization Strategy for Fuel Cell Ships Based on Improved Genetic Simulated Annealing Algorithm

Strategic Insights

— 1 min read

A recent study on the utilization of hydrogen fuel cells in shipboard vessels highlights the need for energy conservation and emission reduction in maritime applications. The study, conducted by researchers at Dalian Maritime University, proposes an innovative real-time energy management strategy (EMS) to mitigate the challenges associated with fuel cells and hydrogen fuel costs. This strategy employs a Nonlinear Autoregressive Neural Network model to forecast vessel load demands and optimize power allocation in real-time.

Key Takeaways:

  • The proposed real-time power optimization strategy achieves a 13% to 30% reduction in equivalent fuel consumption compared to the Equivalent Consumption Minimization Strategy (ECMS).
  • The strategy also leads to a 34% slowdown in the rate of performance degradation of fuel cells.
  • The Genetic Simulated Annealing Algorithm (G-SA) is improved to mitigate fuel cell degradation and enhance overall system cost-effectiveness by integrating the concept of Equivalent Hydrogen Consumption (EHC).
  • The research employs a Nonlinear Autoregressive Neural Network model to forecast vessel load demands and optimize power allocation in real-time.
  • The strategy is validated through peer-reviewed research, showing significant potential for improving the economic viability of fuel cell battery hybrid systems in maritime applications.
  • Researchers at Dalian Maritime University, including Liming Song, Qinjin Zhang, Yji Zeng, Yancheng Liu, Siyuan Liu, and Ning Wang, contributed to this study.

Statistics:

  • The proposed strategy achieves a 13% to 30% reduction in equivalent fuel consumption.
  • The slowdown in the rate of performance degradation of fuel cells is approximately 34%.
  • The study employs a Nonlinear Autoregressive Neural Network model to forecast vessel load demands.
  • The research is peer-reviewed and published in Electric Power Systems Research.

Sources:

  • Real-time Power Optimization Strategy for Fuel Cell Ships Based On Improved Genetic Simulated Annealing Algorithm. Electric Power Systems Research, 2025;245.
  • Elsevier Science Sa, PO Box 564, 1001 Lausanne, Switzerland. (www.elsevier.com; www.journals.elsevier.com/electric-power-systems-research/)
  • Data on Chemicals and Chemistry Discussed by Researchers at Dalian Maritime University (Real-time Power Optimization Strategy for Fuel Cell Ships Based On Improved Genetic Simulated Annealing Algorithm). Energy Weekly News. August 8, 2025; p 60.

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