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.
This study introduces WindWise, a cost–benefit analysis and design optimization tool for Wind Propulsion Systems (WPS) in sustainable shipping. By integrating route simulations, ship constraints, and fuel pricing scenarios, WindWise determines the optimal WPS configuration to maximize fuel savings and minimize payback periods. A retrofit case study of an oil tanker evaluates two WPS classes—DynaRigs and Rotor Sails—across multiple operational and economic conditions. Results reveal that optimal configurations vary based on constraints: in an unconstrained scenario, larger, well-spaced installations minimize aerodynamic losses, whereas realistic constraints shift the preference towards smaller, distributed setups to mitigate cargo loss and air draft penalties. Rotor Sails offer lower upfront costs and shorter payback periods for modest savings targets and for side-wind routes, while DynaRigs emerge as the more viable solution for higher emissions reductions and long-term profitability. Optimization of WPS configurations proves crucial, with non-optimized configurations exhibiting payback periods over 150% higher than optimized ones. Although payback period remains an important metric, considering both payback and net present value provides a more comprehensive assessment of WPS financial viability, with Rotor Sails generally offering faster payback but DynaRigs delivering higher long-term profitability across most scenarios.
This study introduces WindWise, a cost–benefit analysis and design optimization tool for Wind Propulsion Systems (WPS) in sustainable shipping. By integrating route simulations, ship constraints, and fuel pricing scenarios, WindWise determines the optimal WPS configuration to maximize fuel savings and minimize payback periods. A retrofit case study of an oil tanker evaluates two WPS classes—DynaRigs and Rotor Sails—across multiple operational and economic conditions. Results reveal that optimal configurations vary based on constraints: in an unconstrained scenario, larger, well-spaced installations minimize aerodynamic losses, whereas realistic constraints shift the preference towards smaller, distributed setups to mitigate cargo loss and air draft penalties. Rotor Sails offer lower upfront costs and shorter payback periods for modest savings targets and for side-wind routes, while DynaRigs emerge as the more viable solution for higher emissions reductions and long-term profitability. Optimization of WPS configurations proves crucial, with non-optimized configurations exhibiting payback periods over 150% higher than optimized ones. Although payback period remains an important metric, considering both payback and net present value provides a more comprehensive assessment of WPS financial viability, with Rotor Sails generally offering faster payback but DynaRigs delivering higher long-term profitability across most scenarios.
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.
The maritime sector is a key asset for the world economy, but its environmental impact represents a major concern. The sector is primarily supplied with Heavy Fuel Oil, which results in high pollutant emissions. The sector has set targets for deacrbonisation, and alternative fuels have been identified as a short-to medium-term option. The paper addresses the complexity related to the activities of the maritime industry, and discusses the possible contribution of alternative fuels. A sector segmentation is proposed to define the consumption of each sub-segment, so to compare it with the current alternative fuel availability at European level. The paper shows that costs and GHG savings are fundamental enablers for the uptake of alternative fuels, but other aspects are also crucial: technical maturity, safety regulation, expertise needed, etc. The demand for alternative fuels has to be supported by an existing, reliable infrastructure, and this is not yet the case for many solutions (i.e. electricity, hydrogen or methanol). Various options are already available for maritime sector, but the future mix of fuels used will depend on technology improvements, availability, costs and the real potential for GHG emissions reduction.
The International Maritime Organization (IMO) has recently adopted short-term measures introducing technical standards for existing ships and a labeling system reflecting their operational carbon intensity. This paper investigates the relevant techno-economic implications from a shipowner's perspective and estimates the effect of six compliance options on six sample containerships. The study applies a new evidence-based bottom-up approach, and the results show that compliance, when possible, is not straightforward and costly. Engine power limitation is the most cost-effective option, but low power limits can lead to substantially increased sailing times (up to 793.92 h/year), which can be prohibitive. The option favors older ships with oversized engines as its effectiveness is mainly determined by the main engine load profile. In general, the effectiveness of the measures is not without limits, particularly concerning older ships and those that have already installed several options. Solutions such as market-based measures and alternative fuels, classed by IMO as medium- and long-term measures, must be considered soon.
GreenHopper is the first Danish zero-emission ferry developed as a test platform for autonomous waterborne navigation technologies. The paper presents technology development within the innovation project ShippingLab Autonomy, which led to the commissioning of GreenHopper at Limfjorden (DK) in December 2022. The technology research resulted in a holistic system architecture for surface vessel autonomy, based on distribution of functionality and responsibility on software modules, similar to the structure observed in the International Maritime Organization (IMO) Seafarers Training Certification and Watch-keeping (STCW) regulatory framework. The paper shows how this approach results in an architecture that supports safe behaviours of individual modules and of autonomous navigation at a system level. The paper presents the individual modules, specific features and benefits. Elements of the regulatory framework are highlighted to poise technology approval by maritime authorities. The paper reflects on lessons learned, discusses continued technology validation in dedicated operational scenarios.
Denne artikel beretter om CO2, NOx og PM2,5 emissioner fra skibe i Københavns Havn for perioden 2015-2019 beregnet i projektet ” ” Kortlægning af udviklingen i luftforurening fra krydstogsskibe og andre skibe i danske havne” udført af DCE - Nationalt Center for Miljø og Energi under Aarhus Universitet, for Miljø- og Fødevareministeriet (MFVM). De største kilder i havnen i alle år er krydstogtskibe, fulgt af tankskibes oliepumpning (losning af olieprodukter), passagerskibe, tankskibe, containerskibe og general cargo. Mindre bidrag beregnes for ro-ro cargo og slæbebåde samt uddybningsfartøjer, bulkskibe, forskningsskibe, offshorefartøjer og flydekraner. Pr. skibstype i 2019 beregnes følgende resultater for energiforbrug, CO2, NOx og PM2.5 (procentandele i parentes) for krydstogtskibe (56 %, 57 %, 50 %, 71 %), tankskibes oliepumpning (14 %, 13 %, 18 %, 8 %), passagerskibe (9 %, 9 %, 7 %, 9 %), tankskibe (6 %, 6 %, 8 %, 4 %), containerskibe (5 %, 5 %, 6 %, 3 %), general cargo (5 %, 5 %, 5 %, 2 %), slæbebåde (2 %, 2 %, 1 %, 1 %), ro-ro cargo (1 %, 1 %, 1 %, 0 %) og øvrige skibe (2 %, 2 %, 3 %, 1 %). Øvrige skibe omfatter uddybningsfartøjer, bulkskibe, forskningsskibe, offshorefartøjer og flydekraner.Udviklingen i CO2 emissionerne følger udviklingen i energiforbruget. De totale CO2 emissioner ændrer sig kun lidt i perioden fra 2015 til 2019, men varierer en del fra år til år for de forskellige skibstyper. Fra 2015 til 2019 stiger de samlede CO2 NOx og PM2.5 emissioner med hhv. 7 %, 5 % og 31 %. De totale emissionsstigninger skyldes især 24 % flere anløb med gradvist større krydstogtskibe i perioden, der i højere grad benytter tung olie og scrubberteknologi. Scrubberen, hvis funktion er at rense røggassen for svovl, er mindre effektiv til at begrænse udledningen af PM2.5. For krydstogtskibe beregnes CO2[NOx, PM2.5] e missionsstigninger på 34 %[26 %, 62 %]. For alle andre skibe og olie pumpning falder CO2[NOx, PM2.5] emissionerne med hhv. 13 %[8 %, 8 %]og 17 %[15 %, 16 %].
Taking offspring in a problem of ship emission reduction by exhaust gas recirculation control for large diesel engines, an underlying generic estimation challenge is formulated as a problem of joint state and parameter estimation for a class of multiple-input single-output Hammerstein systems with first-order dynamics, sensor delay, and a bounded time-varying parameter in the nonlinear part. This brief suggests a novel scheme for this estimation problem that guarantees exponential convergence to an interval that depends on the sensitivity of the system. The system is allowed to be nonlinear, parameterized, and time dependent, which are characteristics of the industrial problem we study. The approach requires the input nonlinearity to be a sector nonlinearity in the time-varying parameter. Salient features of the approach include simplicity of design and implementation. The efficacy of the adaptive observer is shown on simulated cases, on tests with a large diesel engine on test bed, and on tests with a container vessel.
International shipping has been reported to account for 13% of global NOx emissions and 2.1% of global green house gas emissions. Recent restrictions of NOx emissions from marine vessels have led to the development of exhaust gas recirculation (EGR) for large two-stroke diesel engines. Meanwhile, the same engines have been downsized and derated to optimize fuel efficiency. The smaller engines reduce the possible vessel acceleration, and to counteract this, the engine controller must be improved to fully utilize the physical potential of the engine. A fuel index limiter based on air/fuel ratio was recently developed (Turbo, 2016), but as it does not account for EGR, accelerations lead to excessive exhaust smoke formation which could damage the engine when recirculated.
This paper presents two methods for extending a fuel index limiter function to EGR engines. The methods are validated through simulations with a mean-value engine model and on a vessel operating at sea. Validation tests compare combinations of the two index limiter methods, using either traditional PI control for the EGR loop or the recently developed fast adaptive feedforward EGR control (Nielsen et al., 2017a). The experiments show that the extended limiters reduce exhaust smoke formation during acceleration to a minimum, and that the suggested limiter, combined with adaptive feedforward EGR control, is able to maintain full engine acceleration capability. Sea tests with engine speed steps from 35 to 50 RPM, made peak exhaust opacity increase by only 5% points when using the proposed limiter, whereas it increased 70% points without the limiter.