Stochastic model predictive energy management in hybrid emission-free modern maritime vessels
M Banaei, J Boudjadar… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
M Banaei, J Boudjadar, MH Khooban
IEEE Transactions on Industrial Informatics, 2020•ieeexplore.ieee.orgIncreasing 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 …
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 …
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.
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