Robust Optimal Power Scheduling for Fuel Cell Electric Ships Under Marine Environmental Uncertainty
Gabin Kim,
Minji Lee and
Il-Yop Chung ()
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Gabin Kim: Hyosung Corporation, 74 Simin-daero, Dongan-gu, Anyang-si 14080, Republic of Korea
Minji Lee: School of Electrical Engineering, Kookmin University, 77 Jeongneung-ro, Seongbuk-gu, Seoul 02707, Republic of Korea
Il-Yop Chung: School of Electrical Engineering, Kookmin University, 77 Jeongneung-ro, Seongbuk-gu, Seoul 02707, Republic of Korea
Energies, 2025, vol. 18, issue 11, 1-26
Abstract:
This paper presents a robust optimization-based approach for voyage and power generation scheduling to enhance the economic efficiency and reliability of electric propulsion ships powered by polymer electrolyte membrane fuel cells (PEMFCs) and battery energy storage systems (BESSs). The scheduling method is formulated considering generation cost curves of PEMFCs with mixed-integer linear programming (MILP) and is extended to a robust optimization framework that accounts for marine environmental uncertainties. The robust optimization approach, implemented via the column-and-constraint generation (C&CG) method, ensures stable operation under various uncertainty scenarios, such as wave speed and direction influenced by wind and tidal currents. To validate the proposed method, a simulation was conducted under realistic operational conditions, followed by a case study comparing the MILP and robust optimization approaches in terms of economic efficiency and reliability. Additionally, the optimization model incorporated degradation costs associated with PEMFCs and BESSs to account for long-term operational efficiency. The case study assessed the performance of both methods under load variation scenarios across different marine environmental uncertainties.
Keywords: robust optimization; optimal power scheduling; fuel cell electric ships; battery energy storage system; shipboard power system; marine environmental uncertainty; economic efficiency (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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