Abstract
Reefers and propulsion load consume 90% of the total power in electrified container ships (ECSs). However, the inherent complexities in coordinating high-quantity, low-capacity reefers and low-quantity, high-capacity propulsion loads make efficient diesel generator (DG) operation a challenge. This article presents a model predictive control (MPC)-based bilevel strategy to optimize DG efficiency in ECSs. Focused on real-time tracking of DGs' optimal efficiency points, the scheme addresses economic dispatch and navigational reliability under complex maritime conditions. Furthermore, we propose an aggregated reefer cluster (RC) model and a refrigeration efficiency consensus algorithm. The RC model streamlines reefer flexibilities into an additive, thermal-balance-based representation, thus avoiding temporal coupling issues. The algorithm ensures rapid, constraint-compliant optimization of loads. A case study on a 3000-TEU ECS validates the method's efficacy in reducing operational costs and emissions while maintaining computational efficiency and solution accuracy.
Original language | English |
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Pages (from-to) | 7709-7719 |
Number of pages | 11 |
Journal | IEEE Transactions on Transportation Electrification |
Volume | 10 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2024 |
Keywords
- Computational efficiency
- electrified container ships (ECSs)
- load management
- refrigerated containers
- refrigerating efficiency consensus
ASJC Scopus subject areas
- Automotive Engineering
- Transportation
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering