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 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.
Hydrogen-electricity integrated multi-energy systems are promising approaches to reduce carbon emissions in ports. However, the stochastic nature of renewable energy and the imbalance between the renewable generation and load demand in ports necessitate the design of an appropriate coupled hydrogen-electricity energy storage systems (CHEESS). This paper proposes a multi-objective optimization model for CHEESS configuration in random unbalanced port integrated multi-energy systems (PIMES), aiming to minimize its life-cycle cost and carbon emissions through co-optimization of sizing and energy management. A hierarchical two-stage framework is proposed to solve the multi-objective model. The proposed optimization framework is applied to a real PIMES at the Ningbo-Zhoushan Port. The results show that the proposed method can save 10.54% of the monetary cost and 19.67% of carbon emissions over the entire life-cycle of the system. The study demonstrates that the proposed framework has the potential to generate significant economic and environmental benefits and provides a feasible solution for port authorities seeking to implement CHEESS, aiming to promote sustainability in port operations.
Adopting green vehicles in the transport sector is a highly effective policy for mitigating the sector’s carbon footprint. Moreover, the EU transport policy acknowledges the pivotal role of inland waterways (IWW) in decarbonizing Europe, with a strategic objective to enhance its modal share through the transition from road to IWW. This paper investigates the potential of electric autonomous Roll-on Roll-off (RoRo) ships to enhance the competitive edge of IWW as compared to road transport. This paper examines the impact of this innovative transport system on sustainability by analyzing Key Performance Indicators (KPIs) across economic and environmental dimensions using a comparative case study approach and quantitative analysis data. The main result is that implementing electric autonomous RoRo ships can lead to a 45 % reduction in OPEX (operational expenditure), with profitability expected after about 3.5 years. Emissions decrease by more than 60 %, and by 2030, CO2 emissions in the Well-to-Wake (WTW) cycle are projected to reduce by approximately 77,000 tonnes, aligning with EU transport and environmental policies.
Cod stocks in the Danish inland waters and the Baltic Sea have collapsed today. Fishing vessels have therefore been required to install video cameras that film the catch for control purposes. The use of artificial intelligence for automated documentation of the catch is therefore a promising solution for control as well as research and management purposes that can contribute to rebuilding cod stocks and ensuring sustainable fishing in the future.
Wind-assisted ship propulsion (WASP) technology seems to be a promising solution toward accelerating the shipping industry’s decarbonization efforts as it uses wind to replace part of the propulsive power generated from fossil fuels. This article discusses the status quo of the WASP technological growth within the maritime transport sector by means of a secondary data review analysis, presents the potential fuel-saving implications, and identifies key factors that shape the operational efficiency of the technology. The analysis reveals three key considerations. Firstly, despite the existing limited number of WASP installations, there is a promising trend of diffusion of the technology within the industry. Secondly, companies can achieve fuel savings, which vary depending on the technology installed. Thirdly, these bunker savings are influenced by environmental, on-board, and commercial factors, which presents both opportunities and challenges to decision makers.