Stochastic Model Predictive Energy Management in Hybrid Emission-Free Modern Maritime Vessels

Increasing concerns related to fossil fuels have led to the introducing the concept of emission-free ships (EF-Ships) in marine industry. One of the well-known combinations of green energy resources in EF-Ships is the hybridization of fuel cells (FCs) with energy storage systems (ESSs) and cold-ironing (CI). Due to the high investment cost of FCs and ESSs, the aging factors of these resources should be considered in the energy management of EF-Ships. This article proposes a nonlinear model for optimal energy management of EF-Ships with hybrid FC/ESS/CI as energy resources considering the aging factors of the FCs and ESSs. Total operation costs and aging factors of FCs and ESSs are chosen as problem objectives. Moreover, a stochastic model predictive control method is adapted to the model to consider the uncertainties during the optimization horizon. The proposed model is applied to an actual case test system and the results are discussed.

Automated summary

This article introduces a nonlinear model for optimal energy management of emission-free ships, taking into account the aging factors of fuel cells and energy storage systems. The model considers total operation costs and aging factors of fuel cells and energy storage systems as problem objectives, and utilizes a stochastic model predictive control method to address uncertainties during the optimization process. The proposed model is applied to an actual case test system and the results are analyzed.