Hierarchical Load Management of Propulsion and Reefers for Large Electrified Container Ships

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 DG operation a challenge. This paper presents a Model Predictive Control (MPC)-based bilevel strategy to optimize diesel generator (DG) efficiency in electrified container ships (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.