This paper proposes a multi-time scale scheduling strategy for a practical port coupled hydrogen-electricity energy system (CHEES) to optimize the integration of renewable energy and manage the stochasticity of port power demand. An optimization framework based on day-ahead, intra-day and real-time scheduling is designed. The framework allows coordinating adjustable resources with different rates to reduce the impact of forecast errors and system disturbances, thus improving the flexibility and reliability of the system. The effectiveness of the proposed strategy is verified by a case study of the actual CHEES in the Ningbo Zhoushan Port, and the impact of equipment anomalies on the port power system operation is studied through simulation of different scenarios. The results show that compared with a scheduling scheme without energy management strategy, CHEES with multi-time scale scheduling can save 25.42% of costs and reduce 14.78% of CO 2 emissions. A sensitivity analysis is performed to highlight the impact of hydrogen price and soft open points (SOP) rated power on the system economy. This study not only provides a new perspective for the optimal scheduling of port energy systems, but also provides a practical framework for managing port energy systems to achieve green transformation and sustainable development.
Wind Propulsion Systems (WPS) have gained significant attention as a means of decarbonizing shipping. Limitations in available deck space, emissions reduction targets, and regulatory compliance have led to a wide array of potential WPS configurations, each exhibiting distinct aerodynamic performance and requiring unique optimum sail trims for each unit due to complex interactions. This variability challenges existing aerodynamic models and optimization efforts for maximizing fuel savings. To address this, we present a novel methodology that, for the first time in WPS aerodynamic performance prediction, combines Computational Fluid Dynamics (CFD), independent sail trim optimization, and Machine Learning (ML) to develop surrogate models — Gaussian Process Regression and Feedforward Neural Networks — that rapidly predict aerodynamic performance with CFD-equivalent accuracy. These surrogates capture aerodynamic interactions across various WPS configurations, including unit number, deck arrangement, independent sail trim, hull characteristics, and wind conditions. While employing established ML techniques, our approach is novel in its resource-efficient generation of a comprehensive aerodynamic database, derived from the first in-depth independent trim optimization of a DynaRig case study. Our approach enables the modeling of complex, non-linear interactions that traditional interpolation methods fail to capture. Results show that the developed surrogate models achieve CFD-level accuracy, with an average error below 1 while significantly reducing computational time. This ML-enhanced framework facilitates extensive, rapid WPS design optimizations, supporting efficient integration into performance prediction programs (PPPs) and maximizing fuel savings and emissions reductions tailored to specific routes and wind conditions.Machine Learning; CFD-Simulations; Aerodynamic Performance; Wind Propulsion Systems; Green Shipping; Independent Sail Trim Optimization.
This paper presents a detailed risk assessment framework tailored for retrofitting ship structures towards eco-friendliness. Addressing a critical gap in current research, it proposes a comprehensive strategy integrating technical, environmental, economic, and regulatory considerations. The framework, grounded in the Failure Mode, Effects, and Criticality Analysis (FMECA) approach, adeptly combines quantitative and qualitative methodologies to assess the feasibility and impact of retrofitting technologies. A case study on ferry electrification, highlighting options like fully electric and hybrid propulsion systems, illustrates the application of this framework. Fully Electric Systems pose challenges such as ensuring ample battery capacity and establishing the requisite charging infrastructure, despite offering significant emission reductions. Hybrid systems present a flexible alternative, balancing electric operation with conventional fuel to reduce emissions without compromising range. This study emphasizes a holistic risk mitigation strategy, aligning advanced technological applications with environmental and economic viability within a strict regulatory context. It advocates for specific risk control measures that refine retrofitting practices, guiding the maritime industry towards a more sustainable future within an evolving technological and regulatory landscape.
This paper investigates the significance of ports in the energy transition (ET) and decarbonisation. Ports, being vital in energy value chains, play a critical role in curbing energy use and emissions. The paper draws from the MAGPIE project, funded by the Horizon 2020 programme, which showcases energy and digital solutions in a real-world setting. The paper focuses on sustainable initiatives in 12 European sea- and inland- ports, analysed through interviews and secondary data. Findings reveal that while many ports discuss ET, few have transformed their plans into significant actions due to technological, regulatory, and financial challenges. Three core themes emerge from the review: ET infrastructure, seagoing ships and hinterland transport, and governance. Ports need more actionable strategies for ET, with port authorities spearheading the adoption of sustainable technologies through collaboration.
This paper explores the potential of using green, autonomous ships in revitalizing inland shipping in Europe against the backdrop of declining market share and the dominance of "economy-of-scale" in waterborne freight transportation. It assesses the economic and environmental viability of converting freight from road to waterborne modalities in broader business ecosystems, specifically along the Rotterdam-Ghent corridor. The analysis leverages operational and commercial insights from logistics firms, ports and terminal operators, combined with data on European goods flows by road, and accounts for operational, financial and environmental variables including realistic scenario building and ecosystem implications. Findings indicate that inland shipping in general and green, autonomous shipping in particular offer both economically and environmentally viable alternatives to road transport. The study calls for further research into green, autonomous ships from an ecosystem perspective as a potential solution to current challenges in sustainable freight transportation.
Driven by regulatory mandates, International Maritime Organization (IMO) decarbonization targets, market pressure, and evolving societal expectations, the maritime industry is undergoing a fundamental transition towards full decarbonization. This shift has renewed interest in Wind Propulsion Systems (WPSs) as viable propulsion alternatives, reflected in their increasing adoption. However, widespread implementation remains challenging. Each WPS installation design excels under specific conditions, which makes selecting the most cost-effective WPS installation complex. Failure to optimize design and placement can lead to suboptimal fuel savings or unprofitable deployments, limiting industry confidence, and slowing adoption.
To address these challenges, this PhD Thesis presents a novel modelling framework to optimize WPS installation designs by evaluating their cost-benefit trade-offs. The framework identifies the optimal WPS class, design, positioning, and arrangement to maximize fuel savings and emission reductions while minimizing investment costs, tailored to an operator’s specific profile. The study addresses three main objectives: (1) determining the most cost-effective WPS installation design, (2) enhancing industry understanding of WPS performance, and (3) supporting informed decision-making for shipowners and operators.
The results demonstrate that there is no on-size-fits-all WPS solution; instead, each optimal configuration requires a use-case-specific evaluation, accounting for factors such as ship type, route, wind conditions, emissions reduction targets, and operational constraints. However, general trends emerge. Higher emissions reduction ambitions – requiring larger WPS installations — favor high lift-to-drag ratio and lightweight technologies for costeffectiveness. In contrast, low lift-to-drag ratio systems are more sensitive to deck placement and wind conditions due to the resulting hydrodynamic penalties to counteract aerodynamic
forces, though these effects become less significant for lower emissions reduction targets. Installation viability is further constrained by factors such as maximum air draft and cargo space loss due to weight penalties, which may significantly impact economic feasibility.
Optimization of WPS installation design is found to be critical for maximizing economic returns and ensuring fair comparisons across different WPS classes, as each class has unique performance characteristics. The most cost-effective configurations generally involve max imizing unit spacing to reduce aerodynamic interactions and placing units near the hydrodynamic center of lateral resistance to minimize added resistance penalties. Suboptimal designs can extend payback periods by over 150% compared to optimized configurations. Additionally, while WPS-equipped vessels require higher upfront investment, they demonstrate rapid payback periods and strong profitability, particularly in favorable operational and economic conditions.
A critical threshold of limited return on investment is identified for retrofit installations, occurring when additional WPS units no longer yield increased fuel and emissions savings. This is due to hydrodynamic penalties required to maintain yaw moment balance, ultimately offsetting the WPS benefits. This also underscores the need for an optimized deployment strategy to maximize savings while minimizing investment costs, preventing unprofitable installations that could foster skepticism and hinder adoption.
The methods and findings presented in this PhD Thesis provide a foundation for unlocking the full potential of wind propulsion systems, supporting a more sustainable, cost-effective, and decarbonized shipping industry.