Capacity Optimization for Energy Storage Device of Fuel Cell Train using Co-optimization Method

To reduce carbon emissions in the field of rail transportation, hydrogen fuel cell hybrid trains (FCHT) have been widely studied due to its zero emission with water being its only product of hydrogen consumption. A co-optimization model based on mixed integer linear programming model considering the dynamic power limits of ESD is established to minimize hydrogen consumption, and the energy storage device (ESD) capacity, the speed trajectory of the train and energy management strategy of the on-board power sources are optimized simultaneously. The results show that the net hydrogen consumption can be saved up to 30.07% compared to optimization result of the case without ESD and for the saved hydrogen, 24.65% is realized through regenerative braking. When the maintenance and operation cost is considered, the maximum number of charge and discharge cycles within the lifetime of ESD has an impact on value of optimal capital cost of ESD resulting the maximum net benefits. It is found that when the number of cycles is 10000, the net benefit is achieved at a capital cost of, and when the number of cycles increases to more than 40000, the optimal capital cost will remain at 15.15k$. The studies show that the optimal capital cost plays a key role in achieving the net benefits in a lifecycle of ESD.