A nested optimization framework for ship hybrid propulsion systems considering equivalent CO2 emissions

The growing demand for decarbonization of the shipping sector calls for integrated design strategies that simultaneously address energy management and propulsion system sizing. This paper presents a nested optimization framework for designing ship hybrid propulsion systems that identifies the Pareto-optimal front balancing economic and Well-to-Wake environmental performance. The framework utilizes a multi-objective genetic algorithm (NSGA-II) in the outer layer to efficiently explore the design space for battery capacity and generator sizing. For each candidate design, an inner optimization layer determines the minimum achievable greenhouse gas emissions through optimal power resource management. This nested approach ensures that each point on the resulting Pareto frontier represents a design in which both sizing and operation are simultaneously optimized. The methodological accuracy is validated by benchmarking NSGA-II against an exhaustive grid search, while its effectiveness is demonstrated in a small ferry case study by comparing results with a standard requirement-based design (RBD) approach. The results demonstrate that the optimized framework can achieve up to a 27% reduction in emissions at the same investment cost, or a 6% reduction in investment cost at the same level of emissions, compared to the RBD baseline. A sensitivity analysis is conducted to assess the method’s robustness to realistic variations in power demand and to evaluate the impact of component cost fluctuations on the resulting Pareto frontier. The proposed optimization framework serves as a decision-support tool for ship designers, enabling them to make informed, consistent choices when designing marine hybrid propulsion systems. The proposed structure is generalizable to a wide range of vessel types and operational scenarios.