Nowadays, sea traveling is increasing due to its practicality and low-cost. Ferry boats play a significant role in the marine tourism industry to transfer passengers and tourists. Nevertheless, traditional ferry ships consume massive amounts of fossil fuels to generate the required energy for their motors and demanded loads. Also, by consuming fossil fuels, ferries spatter the atmosphere with CO2 emissions and detrimental particles. In order to address these issues, ferry-building industries try to utilize renewable energy sources (RESs) and energy storage systems (ESSs), instead of fossil fuels, to provide the required power in the ferry boats. In general, full-electric ferry (FEF) boats are a new concept to reduce the cost of fossil fuels and air emissions. Hence, FEF can be regarded as a kind of dc stand-alone microgrid with constant power loads (CPLs). This article proposes a new structure of a FEF ship based on RESs and ESSs. In order to solve the negative impedance induced instabilities in dc power electronic based RESs, a new intelligent single input interval type-2 fuzzy logic controller based on sliding mode control is proposed for the dc-dc converters feeding CLPs. The main feature of the suggested technique is that it is mode-free and regulates the plant without requiring the knowledge of converter dynamics. Finally, we conduct a dSPACE-based real-time experiment to examine the effectiveness of the proposed energy management system for FEF vessels.
In 2018 the International Maritime Organization (IMO) agreed to cut the shipping sector’s overall CO2 output by 50% by 2050. One of the key methods in reaching this goal is to improve operations to limit fuel consumption. However, it is difficult to optimize speed for a complete liner shipping network as routes interact with each other, and several business constraints must be respected. This paper presents a unified model for speed optimization of a liner shipping network, satisfying numerous real-life business constraints. The speed optimization is in this research achieved by rescheduling the port call times of a network, thus, the network is not changed. The business constraints are among others related to transit times, port work shifts and emission control areas. Other restrictions are fixed times for canal crossing, speed restrictions in the piracy areas and desire for robust solutions. Vessel sharing agreements and other collaboration between companies must also be included. The modeling of the different restrictions is described in detail and tested on real-life data. The scientific contribution of this paper is threefold: We present a unified model for speed optimization together with numerous business constraints. We present a general framework for handling routes with different frequencies. Moreover, we present a bi-objective model for balancing robustness of schedules against fuel consumption. The tests show that the real-life requirements can be handled by mixed integer programming and that the model finds significant reductions of bunker consumption and cost for large-scale real-life instances.
The activities and emissions from leisure boats in the Baltic Sea have been modeled in a comprehensive approach for the first time, using a new simulation model leisure Boat Emissions and Activities siMulator (BEAM). The model utilizes survey data to characterize the national leisure boat fleets. Leisure boats have been categorized based on their size, use and engine specifications, and for these subcategories emission factors for NOx, PM2.5, CO, non-methane volatile organic compounds (NMVOCs), and releases of copper (Cu) and zinc (Zn) from antifouling paints have been estimated according to literature values. The modeling approach also considers the temporal and spatial distribution of leisure boat activities, which are applied to each simulated leisure boat separately. According to our results the CO and NMVOC emissions from leisure boats, as well as Cu and Zn released from antifouling paints, are significant when compared against the emissions originating from registered commercial shipping in the Baltic Sea. CO emissions equal 70 % of the registered shipping emissions and NMVOC emissions equal 160 % when compared against the modeled results in the Baltic Sea in 2014. Modeled NOx and PM2.5 from the leisure boats are less significant compared to the registered shipping emissions. The emissions from leisure boats are concentrated in the summer months of June, July and August and are released in the vicinity of inhabited coastal areas. Given the large emission estimates for leisure boats, this commonly overlooked source of emissions should be further investigated in greater detail.
To achieve IMO’s goal of a 50% reduction of GHG emission by 2050 (compared to the 2008 levels), shipping must not only work towards an optimization of each ship and its components but aim for an optimization of the complete marine transport system, including fleet planning, harbour logistics, route planning, speed profiles, weather routing and ship design. ShipCLEAN, a newly developed model, introduces a coupling of a marine transport economics model to a sophisticated ship energy systems model – it provides a leap towards a holistic optimization of marine transport systems. This paper presents how the model is applied to propose a reduction in fuel consumption and environmental impact by speed reduction of a container ship on a Pacific Ocean trade and the implementation of wind assisted propulsion on a MR Tanker on a North Atlantic trade. The main conclusions show that an increase of the fuel price, for example by applying a bunker levy, will lead to considerable, economically motivated speed reductions in liner traffic. The case study sowed possible yearly fuel savings of almost 21 300 t if the fuel price would be increased from 300 to 1000 USD/t. Accordingly, higher fuel prices can motivate the installation of wind assisted propulsion, which potentially saves up to 500 t of fuel per year for the investigated MR Tanker on a transatlantic route.
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 %].
Enhancing environmental sustainability in maritime shipping has emerged as an important topic for both firms in shipping-related industries and policy makers. Speed optimization has been proven to be one of the most effective operational measures to achieve this goal, as fuel consumption and greenhouse gas (GHG) emissions of a ship are very sensitive to its sailing speed. Existing research on ship speed optimization does not differentiate speed through water (STW) from speed over ground (SOG) when formulating the fuel consumption function and the sailing time function. Aiming to fill this research gap, we propose a speed optimization model for a fixed ship route to minimize the total fuel consumption over the whole voyage, in which the influence of ocean currents is taken into account. As the difference between STW and SOG is mainly due to ocean currents, the proposed model is capable of distinguishing STW from SOG. Thus, in the proposed model, the ship’s fuel consumption and sailing time can be determined with the correct speed. A case study on a real voyage for an oil products tanker shows that: (a) the average relative error between the estimated SOG and the measured SOG can be reduced from 4.75% to 1.36% across sailing segments, if the influence of ocean currents is taken into account, and (b) the proposed model can enable the selected oil products tanker to save 2.20% of bunker fuel and reduce 26.12 MT of CO2 emissions for a 280-h voyage. The proposed model can be used as a practical and robust decision support tool for voyage planners/managers to reduce the fuel consumption and GHG emissions of a ship
Waiting times for trucks, trains, airplanes and ships in service represent apparent transport system inefficiencies, and measures to reduce these may have the potential to abate transport GHG emissions. In international shipping, transportation researchers have pointed out that reduced waiting time in association with port calls holds such promise. We explore the potential for GHG abatement through port call optimization, focusing on crews and their employers - the shipping companies. Adding new empirical evidence to the transportation literature, we confirm the existence of idle time during port calls, and go beyond this in describing the causes for it. We show how several port stakeholders, including government officials, limit the crews’ and shipping companies’ room for maneuver in relation to port calls. We also show why the process of reducing waiting time in shipping is more complex than that for onshore transport modes, where real-time traffic information guides drivers’ route choices, and reduces congestion and waiting time. Our findings have implications for both policy makers and transportation research.
The purpose of this paper is to assess the status and prospects of the decarbonization of maritime transport. Already more than two years have passed since the landmark decision of the International Maritime Organization (IMO) in April 2018, which entailed ambitious targets to reduce greenhouse gas (GHG) emissions from ships. The paper attempts to address the following three questions: (a) where do we stand with respect to GHG emissions from ships, (b) how is the Initial IMO Strategy progressing, and (c) what should be done to move ahead? To that effect, our methodology includes commenting on some of the key issues addressed by the recently released 4th IMO GHG study, assessing progress at the IMO since 2018, and finally identifying other issues that we consider relevant and important as regards maritime GHG emissions, such as for instance the role of the European Green Deal and how this may interact with the IMO process. Even though the approach of the paper is to a significant extent qualitative, some key quantitative and modelling aspects are considered as well. On the basis of our analysis, our main conjecture is that there is not yet light at the end of the tunnel with respect to decarbonizing maritime transport.
The power system of an all-electric ship (AES) establishes an independent microgrid using the distributed energy resources, energy storage devices, and power electronic converters. As a hybrid energy system (HES), the power system of an AES works as a unified system where each part can affect the reliability of the other parts. The systemic reliability centered maintenance (SRCM), which efficiently enhances the reliability and safety of the AES by identifying optimal maintenance tasks of the AES, is considered in this article to apply to the entire system. In order to calculate the reliability and optimal maintenance schedule, the Markov process and Enhanced JAYA (EJAYA) are utilized. A layer of protection analysis (LOPA), which is a risk management technique, is adopted to assess the safety of the system. A hybrid molten carbonate fuel cell, photovoltaic (PV), and lithium-ion battery are considered as energy sources of the AES. Based on two common standards, DNVGL-ST-0033 and DNVGL-ST-0373, the suggested maintenance planning method can be used in industrial applications. Eventually, in order to validate the proposed method, a model-in-the-loop real-time simulation using dSPACE is carried out. The obtained results show the applicability and efficiency of the proposed method for improving reliability and safety.
Among the spectrum of logistics – based measures for sustainable shipping, this chapter focuses on speed optimization. This involves the selection of an appropriate speed by the vessel, so as to optimize a certain objective. As ship speed is not fixed, depressed shipping markets and/or high fuel prices induce slow steaming which is being practised in many sectors of the shipping industry. In recent years the environmental dimension of slow steaming has also become important, as ship emissions are directly proportional to fuel burned. Win-win solutions are sought, but they will not necessarily be possible. The chapter presents some basics, discusses the main trade-offs and also examines combined speed and route optimization problems. Some examples are presented so as to highlight the main issues that are at play, and the regulatory dimension of speed reduction via speed limits is also discussed.