The electrification of shipboard power systems (SPSs), combined with the introduction of heterogeneous power sources and energy storage technologies, is driving a need for more advanced and structured control strategies. This review examines control methods and architectures for DC ships, with a specific interest in power systems integrating energy storage systems and zero-emission power generation. Control methods are categorized based on both their functionality and architecture, evaluating their resilience, adaptability, and scalability. Different hierarchical layers are reviewed, distinguishing local control, coordinated control, and energy management methods. Key challenge in the coordinated control arise due to large load fluctuations, constant-power loads, low inertia, and diverse dynamic capabilities of power sources and storage systems. These characteristics complicate voltage stability, dynamic power sharing, and state-of-charge management. Decentralized, centralized, and distributed control architectures are reviewed with respect to scalability, communication requirements, and fault tolerance. At the high-level layer, energy management strategies are discussed in terms of operational efficiency and resiliency, with predictive and distributed methods forming key trends in shipboard power system control. The review highlights the need for resilient, adaptive, and scalable control solutions tailored to future DC SPSs, particularly those integrating fuel cells and energy storage technologies.

Electrification of ship power systems plays a central role in the mobility transition towards sustainable transportation. The integration of a large number of components with distinct characteristics into a shipboard microgrid benefits from a modular design and standardized interfaces. Key challenges lie in the variety of component characteristics, and an evolution of parameters during the power system operation. Further, topology alterations can occur over time, requiring a reformulation of the optimal power dispatch problem. Accordingly, a modular energy management strategy must be adaptive to these changes. This work explores a distributed energy management architecture with a central coordinating agent, realized via Lagrangian dual decomposition and a gradient-based solver. This architecture ensures both local feasibility while reaching global optimality and a power balance through a consensus mechanism. Parameter changes are incorporated in local cost functions, making extensive data exchange with a central unit obsolete. Handling a variable number of power system components, this approach is resilient to component faults, topology re-designs, and component degradation. The method is applied to a fuel-cell battery hybrid harbor tug equipped with multiple parallel modules with unique ratings and state-of-health. The energy management strategy minimizes total operating costs, based on hydrogen fuel consumption and cell degradation. Extensive mission simulations show similar performance for the distributed approach and a centralized equivalent. The predictive strategy is demonstrably superior to instantaneous optimization, yielding a cost reduction of 18.3% with a 15min prediction horizon. The model predictive control (MPC) performance increases with the horizon length, reducing operation costs by an additional 6.0% at 60min. In addition, a local decision-making heuristic shows promising potential for the cell degradation via optimized timing of on- and off switching. At 15min, this reduces operation costs by 3.0% and at 60min by 12.7%. Finally, the distributed optimization is deployed on real-time target machines to showcase the applicability of the approach on actual controller and communication hardware.

The path to zero-emission shipping is deeply connected to full-electric vessels. One major challenge to enable this technology for broader application is the design of optimal energy management (EM). The flexibility of operating load sharing in hybrid energy systems could lead to suboptimal solutions using rule-based control. Advanced control strategies can be used to find optimal solutions for the EM problem. In addition, the use of advanced control allows for the incorporation of multiple objectives. An important compromise is the decision between minimizing cost and emissions. A promising approach for EM is the Equivalent Consumption Minimization Strategy (ECMS), which allows for instantaneous optimization of the problem and is suitable for dealing with fast system dynamics. The strategy assigns equivalent factors in the objective function, leading to an easily expandable multi-objective control approach.This paper presents a novel ECMS-based control strategy for health-aware EM of a full-electric vessel, incorporating diesel internal combustion engines, fuel cells, and batteries with flexible changing operation conditions. To this aim, firstly, we introduce our innovative formulation of the multi-objective problem, considering fuel and electricity expenditures and CO₂ and NO_x emissions, alongside the degradation of batteries and fuel cells. Subsequently, we determine the equivalent factors by employing a Pareto Front approach. Lastly, our developed controllers are assessed against a benchmark derived from state-of-the-art strategies. A case study of a full-electric vessel showcase the potential of our proposed solution. The results demonstrate the control's effectiveness in optimizing the operation considering a variety of objectives, such as fuel consumption or emission production, under variable operational conditions.

Hydrogen-based shipboard power systems (SPS) are gaining prominence as a zero-emission alternative to conventional diesel-fueled systems for reducing the carbon footprint in the maritime sector. Typical designs incorporate fuel cells (FCs) as the main power supply combined with batteries in a DC distribution network. However, the efficient coordination of power generation and storage systems with different characteristics remains a challenge, particularly in topologies with multiple parallel FCs and batteries. This aspect has received limited attention in existing research. To address this challenge, this paper presents a modular approach to the hierarchical control of power generation and storage systems. Dynamic power sharing is achieved using a decentralized strategy that employs bandwidth separation, accounting for the opposing capabilities of each device. Additionally, an energy management strategy (EMS) based on equivalent consumption minimization is realized in this modular framework using a low-bandwidth communication network. The proposed architecture's modular character allows for a flexible power system reconfiguration and extension. The methodology is showcased through simulations using a short-sea cargo vessel as a case study. The results demonstrate that the bandwidth separation ensures the operation of the different technologies within their specified bandwidths, limiting the potential degradation of the FC systems. The addition of the modular EMS shows a fuel-efficient operation of the FC-battery DC SPS and a decrease in the FCs' power gradients, and thereby their aging effect.