MPC Framework for the Energy Management of Hybrid Ships with an Energy Storage System

Abstract

This paper proposes an advanced shipboard energy management strategy (EMS) based on model predictive control (MPC). This EMS aims to reduce mission-scale fuel consumption of ship hybrid power plants, taking into account constraints introduced by the shipboard battery system. Such constraints are present due to the boundaries on the battery capacity and state of charge (SoC) values, aiming to ensure safe seagoing operation and long-lasting battery life. The proposed EMS can be used earlier in the propulsion design process and requires no tuning of parameters for a specific operating profile. The novelties of the study reside in (i) studying the impact of mission-scale effects and integral constraints on optimal fuel consumption and controller robustness, (ii) benchmarking the performance of the proposed MPC framework. A case study carried out on a naval vessel demonstrates near-optimal and robust behaviour of the controller for several loading sequences. The application of the proposed MPC framework can lead to up to 3.5% consumption reduction due to utilisation of long term information, considering specific loading sequences and charge depleting (CD) battery operation.

Nonlinear Model Predictive Control of Shipboard Boom Cranes Based on Moving Horizon State Estimation

“…Prior knowledge of states is vital and decisive for estimating system evolution, which can further affect the overall control performance in MPC [5]. Unfortunately, the accuracy of system evolution is almost always degraded by disturbances and noises in practice.…”