Degradation-aware Predictive Energy Management for Fuel Cell-Battery Ship Power System with Data-driven Load Forecasting

TL;DR

This paper presents a degradation-aware predictive energy management strategy for fuel cell-battery ship power systems that reduces hydrogen consumption and cell degradation using data-driven load forecasting.

Contribution

It introduces a novel load forecasting-based control approach that explicitly considers cell degradation and operational costs in maritime fuel cell systems.

Findings

Load predictions over 15 minutes are accurate using onboard measurements.

The proposed control reduces hydrogen consumption by up to 5.8%.

Cell degradation is reduced by up to 36.4% with the new strategy.

Abstract

Hydrogen-based zero-emission ships are a key element in the decarbonization of the maritime sector. To strengthen these their economic competitiveness, it is key to drive their costs to a minimum. Current literature mainly focuses on fuel consumption minimization, but there is a lack of explicit consideration of costs arising from cell degradation and optimization-based approaches that leverage information on future load trajectories. This work aims at minimizing the operational cost of fuel cell-battery hybrid shipboard power systems, accounting for hydrogen consumption and cell degradation as the main cost drivers. A degradation-aware predictive energy management strategy utilizing data-driven load forecasting is designed and showcased at the example of a virtually retrofitted harbor tug. This work shows that the real onboard measurements of the vessel can be utilized to make accurate load predictions over 15min. Results indicate that the degradation-aware, predictive control simultaneously reduces the hydrogen consumption by up to 5.8% and the cell degradation by up to 36.4% with an aged fuel cell system when compared to a filter-based benchmark applied to real operating data of the harbor tug. With an increased prediction horizon of 1h, further significant reductions of 3.8% and 14.0% could be shown.