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Specific fuel consumption graph for representative diesel generator versus engine speed and load left, examined SFOC curves of MAN 7S60MC — C8 engine (right).
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... combination with the rotational speed and the slip of the propeller, calculation of the actual rpm of the engine can be performed and the curve of engine-ship interaction can be plotted. Fig. 2 illustrates the effect that variations in engine loading have on specific fuel ...
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... of significant faults due to crew error. However, most differences can be explained due to sea and air inlet temperatures that affect the performance of the engine (MAN Diesel, 2007) and the actual operation in non- laboratory environment , which leads to an increase in the actual fuel consumption of up to 8% of the initial, as depicted in Fig. 2 ...
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... generators. This selection is made in order to have larger engines which consume less fuel and for which heat recovery is better. This enables the system to cover the working points as efficiently as possible. Any potential application of slow steaming is made more efficient, as the SFOC of all engines is at the minimum value as depicted in Fig. 2. Furthermore, there is the potential to overhaul the generators while the ship is in operation. Thus, using the already installed power and that this output has to be covered by the 85% output of the generators (optimum). Possible marine generator sets from two major manufactures are presented in Table 6. For shore applications, ...
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... P is the mean daily power and t 1 and t 2 are the time in days for the duration of the voyage. Thus, the energy requirements (integration results) are presented in Fig. 7 for three Post- Panamax ships used to illustrate the methodology. The hybrid system sizing utilises multiple diesel generator sets with different electrical output and energy storage devices such as batteries. The operational point of is taken as equivalent to the two-stroke conventional plant predicted by average loading in similar routes or by a smart controller. The latter will interpret data such as, state of charge of batteries, number of generators currently in operation, estimated time of arrival (ETA) at destination port and forecast of sea state. The decision constraints are the operation with the minimum number of generators and the likely demanded energy availability at the end or start of the voyage. The operation of the hybrid system is simplified as the engines operates in discrete stages of the previously installed power output (for the two-stroke engine), points that are highly optimised (minimum SFOC for stationary applications) by the engine manufacturers and produce constant amount of energy. These are referred as the ‘working points’ of the hybrid system. Table 5 represents the closest working point to the mean value of each voyage. Thus, the energy produced by the power output of the working point is considered to cover the average propulsion energy demand for the examined period. Importing the values from Table 5 and combined with the results of Figs. 7 and 8 is developed. This figure depicts the daily fluctuation of energy requirements for the vessel, if the hybrid propulsion system was in operation. The generators are set to produce the 80% of the conventional output. However, the requirements of propulsion vary with time. Consequently the energy storage medium, in order to keep the vessel speed constant, is required to supply energy for propulsion. In the ideal operation of the system, with no conversion losses and an immediate response of the controller, the green areas above and below each period of operation would be equal. This implies that after a voyage, the system will have run in optimum condition and the storage medium will be fully charged. As battery charge/ discharge conversion losses exist, these these areas have to be equal with respect to the conversion losses. This means that the charging area (above the operational point) is greater that the area below and this difference is equal to the loss of power times the hours of operation. Immediate conclusions for the energy storage installation and for the power output can be extracted. As can be observed from Fig. 8, the amount of energy that is available for storage, or is required to be supplied for the propulsion needs, is closely related to the working point of the engine as it was previously defined. The selection of this point can be further optimised and adjusted. Moreover, installation of a hybrid propulsion unit potentially allows the main engine to be smaller since in case of rough weather the extra amount of energy required for propulsion can be covered by the stored energy. The procedure to size the hybrid ship is separated into two major parts that are connected to each other. The first part is the selection and sizing of the diesel generator sets. The original ship design is assumed to remain constant so that the hull form and the propeller are unaltered. It is possible that further fuel savings may be made possible by subsequent modification to these areas (Molland et al., 2011). Hence, the overall system power delivered to the propeller remains the same. Potential reductions in the installed power will be as a result of optimised selection of both engines and storage medium. The installed engine onboard the examined Post-Panamax vessels is an MAN 7S50MC-C7 engine with Maximum continuous Rating (SMCR) of 11,060 kW at 127 rpm. The optimum point of operation is at 75% of the SMCR (MAN Diesel, 2007). A previous study (Dedes et al., 2010) showed that three preliminary scenarios of engine installation should be considered before simulating the overall system and running optimisation algorithms. This study is based on the scenario that the available power will be supplied by a total of six generator sets. With these six generators, 60% of the power will be supplied by two identical engines and the remaining 40% by four identical diesel generators. This selection is made in order to have larger engines which consume less fuel and for which heat recovery is better. This enables the system to cover the working points as efficiently as possible. Any potential application of slow steaming is made more efficient, as the SFOC of all engines is at the minimum value as depicted in Fig. 2. Furthermore, there is the potential to overhaul the generators while the ship is in operation. Thus, using the already installed power and that this output has to be covered by the 85% output of the generators (optimum). Possible marine generator sets from two major manufactures are presented in Table 6. For shore applications, optimisation at high single operational load is done, which results in further SFOC reduction and is applicable in hybrid propulsion system, as generator output is not altered. The loading difference, as it was previously explained, was multiplied by the MCR and the voyage time, in order to give the energy difference between production and requirement. These values are shown in Fig. 9, marked by the þ symbol. The diamond symbol represents every area above and below the constant energy production. In order to estimate the actual storage capacity of the system during voyages, a regression algorithm was created importing the statistic values of every vessel of a given type within the examined fleet. The first regression curve, depicted in Fig. 9, is based on the values denoted by the diamond symbol and the second is based on the daily energy difference. Additionally, the data presented with the diamond symbols relate to the ‘autonomy radius’ of the system and represent the ability of the system to cover the demand without alternating the production of energy by switching the generators on and off. In Fig. 9 the everyday energy report model is more accurate in the prediction of requirement than the total area energy model which overestimates the required energy due to the small sample inserted in the regression model calculation. With the aim of determining the required energy storage capacity, the propulsion designer has to define the vessel autonomy time. Autonomy time is set, to be the time (hours) before battery energy is depleted. In this work, a 200 h autonomy time of the system, is considered sufficient for bulk carrier applications. The results for ‘at sea operation’ for the rest of the fleet are summarised in Table 7. Although the energy storage requirements are summarised in Table 7, more aspects of energy availability have to be considered. It was previously mentioned that the batteries at the end of the voyage are fully charged. This requirement is justified by the existence of Emission Control Areas (ECAs). In these zones, an ‘emission free’ battery only operation is ideal. Thus, the energy storage system will supply sufficient energy to the vessel, either at normal voyage speed or at lower speed, until ship is berthed as well as to perform cargo handling. Moreover in certain sizing scenarios, sufficient stored energy has to available for departure without engine operation while the cargo handling had also been performed without ship engine operation. The latter potential is possible when harbours are equipped with ‘cold ironing’ facilities. Notwithstanding these variations in this study we concentrate on the voyage phase and assume that the battery system is fully charged at the beginning and end of each voyage. For the analysis of the performance of the hybrid propulsion system, a simplified model is used for the battery energy storage device. Although some aspects of performance will not be captured precisely, it should provide sufficient detail to size the system. It is assumed that the operation of an equivalent Diesel Electric system has the minimum SFOC of each vessel’s current propulsion engine. Although the engine shop test curve, shows that the SFOC curve is almost flat near the optimum area, the actual measured consumption differs significantly due to HFO operation and due to actual engine ship interaction. The sea and air temperature correction is assumed to make an insignificant contribution for the examined voyages. The overall battery performance cycle efficiency (charging–discharging) is considered constant for any discharge current and equal to 85% for redox flow batteries (Mohamed et al., 2009) and 92% for Sodium Nickel Chloride (Dustmann, 2004). These values for high instan- taneous discharge currents will drop but for over an overall cycle it should adequately represent the battery behaviour. The conversion losses from electrical to mechanical energy are typically 8–10%. These values depend on the individual electromechanical system. In this study, two scenarios were investigated as illustrated schematically in Fig. 10. The first scenario depicts an All Electric Ship (AES) vessel equipped with the four-stroke auxiliary generator engines of Table 6 and with motor/generator conversion losses equal to 8%. The second scenario can be identified as a theoretical two-stroke hybrid system with gearbox and electric motor similar to Power Take Off/In (PTO–PTI) systems that currently are under research and considered to offer gains in terms of safety and fuel consumption (Prousalidis et al., 2005). Battery efficiency issues have been accounted for in ...
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... ageing of the engines, poor maintenance and actual operation in non-ISO conditions result in a decrease of engine efficiency and increase of the SFOC. Consequently the ‘as measured’ fuel consumption will still imply a degree of uncertainty for the NO x emissions although the real engine would likely to emit more than that assumed in this study. This section presents the actual engine operation analysis applied to 31 separate voyages across five vessel types and for a variety of laden, and ballast conditions. Engine loading is calculated along with the actual energy requirements. Sizing of a replacement hybrid propulsion system is performed and energy consumption results for the total bulk carrier fleet are demonstrated. Daily ship performance data were collected from the technical department of a Greek Maritime Corporation. Each technical form includes the daily maintenance and monitoring logs together with operational orders for ship routing. These forms are commonly known as ‘noon reports’ and an example is shown in Table 4. The engine loading, as a percentage of the maximum continuous rating of the engine (MCR), was calculated by correlation of direct and indirect influence factors with the shop tests of the propulsion engine and the sea trials of the vessel. Direct influence parameters are the engine rpm, the Fuel Admission Lever, the Load Indicator and the rotational speed of the turbochargers. Secondary parameters are the slip of propeller, the ship’s speed, the wind direction and force, the sea condition, the current strength and direction. These parameters have an indirect influence in the correlation with the shop tests but are the main reasons why the engine loading varies. Direct influence factors are interpolated into the performance curves of the engine. The load indicator shows the desired engine loading, which shows the percentage of the MCR that the engine should be operating at. The fuel admission level shows the actual petroleum that is injected per cycle and hence the actual loading can be calculated. In practice, due to possible inaccuracies in the daily reports, this technique can introduce errors. The knowledge of the turbochar- ger rotational speed, which is unique to each engine load (except the loads requiring the use of the air blower), does allow a cross- check of the previously calculated value. In combination with the rotational speed and the slip of the propeller, calculation of the actual rpm of the engine can be performed and the curve of engine–ship interaction can be plotted. Fig. 2 illustrates the effect that variations in engine loading have on specific fuel consumption. These curves suggest that total emissions which are directly connected to the SFOC of the engine are dependent on the loading. Any transient operation away from the minimum, lead to increased SFOC, thus emissions in terms of g/kWh. Ship operation in calm sea has almost constant resistance for constant ship speed. When sea state is considered moderate or rough, added wave resistance is present. Hence thrust is increased, as the propeller is now not working at the design point, more fuel is injected into the engine to cover the torque and rpm demand. Sea motions affect this percentage of added resistance, while in extreme seas the propeller maybe partially outside the water. All this operation of the engine to cover the demand is considered transient, as the spectrum of waves is stochastic and irregular (Molland et al., 2011). Previous studies try to assume the engine loading and calculate indirectly the consumed fuel per voyage day by multiplying SFOC, engine loading factor, the kW of the engine’s MCR and the activity time (Corbett and Koehler, 2003) and (Endresen et al., 2003). This loading factor is found using (IMO, 2009) Actual speed Load Factor 1⁄4 ð 1 Þ Max : speed In this study the consumed fuel is reported and measured by the flow meters inside the engine rooms of each examined vessel. The knowledge of engine loading gives an initial approximation of the consumed fuel and allows the detection of significant faults due to crew error. However, most differences can be explained due to sea and air inlet temperatures that affect the performance of the engine (MAN Diesel, 2007) and the actual operation in non- laboratory environment , which leads to an increase in the actual fuel consumption of up to 8% of the initial, as depicted in Fig. 2 (right). The conventional diesel installation on-board bulk cargo vessels is a large two-stroke diesel engine (e.g. tankers, dry bulk ships), mostly without a generator attached to the main shaft, to cover the propulsion loads. The influence of weather on the performance of the vessel is important and previous work to estimate the magni- tude of these influences on vessel speed is summarised in Aertssen (1969). Fig. 3 illustrates the variance of engine loading from the optimum point and from each voyage mean loading (as found later in Fig. 6) of the examined Post-Panamax fleet. It can also be extracted from Fig. 4, there is a large range between the minimum and maximum reported values, while the difference from the maximum reported value to the MCR of the engine is also large. Typically, while sizing the propulsion unit, a margin is left so that the engine will operate at 85%, MCR in calm sea conditions at the service speed. The margin account up to 100% covers increased energy demands due to rough sea conditions and the progressive fouling of the ship hull (Molland et al., 2011). However, this point is not always the optimum point of operation of the engine, as may be found from the project guide of the installed two-stroke engine on the examined vessels (MAN Diesel, 2007), where the optimum loading is at 75% MCR. One other important aspect in the total power train is the loading of auxiliary engines. Fig. 5 demonstrates that auxiliary electrical demands do not regularly exceed 600 kW. Hence, every reported load above 600 kW will be considered as a ‘peak value’. Peak values are significant since at these times the output of a single generator is insufficient to cover the peak demands. Hence, coupling a second generator is required, causing the overall system to be partially loaded and at an inefficient operational point. This can significantly increase their specific fuel consumption, whilst the turbochargers of the engine will not be working near their surge line. The supply of air may be insufficient, further reducing the efficiency of combustion and smoke will be visible. Similar effects occur for the main engine operating at a reasonable distance away from its optimum. It is not possible to completely remove transient operation of the engines since when starting from cold conditions (idle and switched off) it takes time to increase the pressure and the temperature of the engine materials in stages so as to be ready to increase the load. A potential solution for transients during voyage could be the application of load levelling techniques using an appropriate storage medium (Hybrid System). Meanwhile the fully electrified vessel permits the uncoupling of loads and the engine and allows a more efficient handling of the complete power train. From Fig. 6 it can be observed that in every voyage of the Post- Panamax vessels within the fleet, the engine mean load varies from 70% to 80% of the MCR. Hence, the appropriate sizing of the main propulsion unit that could achieve a mean loading into that range, potentially the excess of produced energy in some cases can even that lack of required energy, achieving a NET energy demand equal to zero. Using the reported power requirements shown in Fig. 4, Eq. (2) is introduced, as from now; the hybrid system is examined from an energy ...
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... ageing of the engines, poor maintenance and actual operation in non-ISO conditions result in a decrease of engine efficiency and increase of the SFOC. Consequently the ‘as measured’ fuel consumption will still imply a degree of uncertainty for the NO x emissions although the real engine would likely to emit more than that assumed in this study. This section presents the actual engine operation analysis applied to 31 separate voyages across five vessel types and for a variety of laden, and ballast conditions. Engine loading is calculated along with the actual energy requirements. Sizing of a replacement hybrid propulsion system is performed and energy consumption results for the total bulk carrier fleet are demonstrated. Daily ship performance data were collected from the technical department of a Greek Maritime Corporation. Each technical form includes the daily maintenance and monitoring logs together with operational orders for ship routing. These forms are commonly known as ‘noon reports’ and an example is shown in Table 4. The engine loading, as a percentage of the maximum continuous rating of the engine (MCR), was calculated by correlation of direct and indirect influence factors with the shop tests of the propulsion engine and the sea trials of the vessel. Direct influence parameters are the engine rpm, the Fuel Admission Lever, the Load Indicator and the rotational speed of the turbochargers. Secondary parameters are the slip of propeller, the ship’s speed, the wind direction and force, the sea condition, the current strength and direction. These parameters have an indirect influence in the correlation with the shop tests but are the main reasons why the engine loading varies. Direct influence factors are interpolated into the performance curves of the engine. The load indicator shows the desired engine loading, which shows the percentage of the MCR that the engine should be operating at. The fuel admission level shows the actual petroleum that is injected per cycle and hence the actual loading can be calculated. In practice, due to possible inaccuracies in the daily reports, this technique can introduce errors. The knowledge of the turbochar- ger rotational speed, which is unique to each engine load (except the loads requiring the use of the air blower), does allow a cross- check of the previously calculated value. In combination with the rotational speed and the slip of the propeller, calculation of the actual rpm of the engine can be performed and the curve of engine–ship interaction can be plotted. Fig. 2 illustrates the effect that variations in engine loading have on specific fuel consumption. These curves suggest that total emissions which are directly connected to the SFOC of the engine are dependent on the loading. Any transient operation away from the minimum, lead to increased SFOC, thus emissions in terms of g/kWh. Ship operation in calm sea has almost constant resistance for constant ship speed. When sea state is considered moderate or rough, added wave resistance is present. Hence thrust is increased, as the propeller is now not working at the design point, more fuel is injected into the engine to cover the torque and rpm demand. Sea motions affect this percentage of added resistance, while in extreme seas the propeller maybe partially outside the water. All this operation of the engine to cover the demand is considered transient, as the spectrum of waves is stochastic and irregular (Molland et al., 2011). Previous studies try to assume the engine loading and calculate indirectly the consumed fuel per voyage day by multiplying SFOC, engine loading factor, the kW of the engine’s MCR and the activity time (Corbett and Koehler, 2003) and (Endresen et al., 2003). This loading factor is found using (IMO, 2009) Actual speed Load Factor 1⁄4 ð 1 Þ Max : speed In this study the consumed fuel is reported and measured by the flow meters inside the engine rooms of each examined vessel. The knowledge of engine loading gives an initial approximation of the consumed fuel and allows the detection of significant faults due to crew error. However, most differences can be explained due to sea and air inlet temperatures that affect the performance of the engine (MAN Diesel, 2007) and the actual operation in non- laboratory environment , which leads to an increase in the actual fuel consumption of up to 8% of the initial, as depicted in Fig. 2 (right). The conventional diesel installation on-board bulk cargo vessels is a large two-stroke diesel engine (e.g. tankers, dry bulk ships), mostly without a generator attached to the main shaft, to cover the propulsion loads. The influence of weather on the performance of the vessel is important and previous work to estimate the magni- tude of these influences on vessel speed is summarised in Aertssen (1969). Fig. 3 illustrates the variance of engine loading from the optimum point and from each voyage mean loading (as found later in Fig. 6) of the examined Post-Panamax fleet. It can also be extracted from Fig. 4, there is a large range between the minimum and maximum reported values, while the difference from the maximum reported value to the MCR of the engine is also large. Typically, while sizing the propulsion unit, a margin is left so that the engine will operate at 85%, MCR in calm sea conditions at the service speed. The margin account up to 100% covers increased energy demands due to rough sea conditions and the progressive fouling of the ship hull (Molland et al., 2011). However, this point is not always the optimum point of operation of the engine, as may be found from the project guide of the installed two-stroke engine on the examined vessels (MAN Diesel, 2007), where the optimum loading is at 75% MCR. One other important aspect in the total power train is the loading of auxiliary engines. Fig. 5 demonstrates that auxiliary electrical demands do not regularly exceed 600 kW. Hence, every reported load above 600 kW will be considered as a ‘peak value’. Peak values are significant since at these times the output of a single generator is insufficient to cover the peak demands. Hence, coupling a second generator is required, causing the overall system to be partially loaded and at an inefficient operational point. This can significantly increase their specific fuel consumption, whilst the turbochargers of the engine will not be working near their surge line. The supply of air may be insufficient, further reducing the efficiency of combustion and smoke will be visible. Similar effects occur for the main engine operating at a reasonable distance away from its optimum. It is not possible to completely remove transient operation of the engines since when starting from cold conditions (idle and switched off) it takes time to increase the pressure and the temperature of the engine materials in stages so as to be ready to increase the load. A potential solution for transients during voyage could be the application of load levelling techniques using an appropriate storage medium (Hybrid System). Meanwhile the fully electrified vessel permits the uncoupling of loads and the engine and allows a more efficient handling of the complete power train. From Fig. 6 it can be observed that in every voyage of the Post- Panamax vessels within the fleet, the engine mean load varies from 70% to 80% of the MCR. Hence, the appropriate sizing of the main propulsion unit that could achieve a mean loading into that range, potentially the excess of produced energy in some cases can even that lack of required energy, achieving a NET energy demand equal to zero. Using the reported power requirements shown in Fig. 4, Eq. (2) is introduced, as from now; the hybrid system is examined from an energy ...
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Ammonia is emerging as a viable alternative to fossil fuels in combustion systems, aiding in the reduction of carbon emissions. However, its use faces challenges, including NOx emissions and low flame speed. Innovative approaches and technologies have significantly advanced the development and implementation of ammonia as a zero-carbon fuel. This review explores current advancements in using ammonia as a fuel substitute, highlighting the complexities that various systems need to overcome before reaching full commercial maturity in support of practical decarbonising global strategies. Different from other reviews, this article incorporates insights of various industrial partners currently working towards green ammonia technologies. The work further addresses fundamental complexities of ammonia combustion, crucial for its practical and industrial implementation in various types of equipment.
... Optimising propulsion systems is one of the most necessary yet difficult steps in shipping decarbonisation (Blasco, Durán-Grados, Hampel, & Moreno-Gutiérrez, 2014;Dedes, Hudson, & Turnock, 2012), especially with a new alternative source of energy like ammonia. As Kim et al. (2020) investigated, approximately 83.7-92.1% of GHG emissions could be reduced if the ammonia-fuelled ship uses an appropriate propulsion system and fuel production method. ...
Decarbonisation efforts in shipping have intensified amid recent regulations and net-zero emission pledges from governments and global supply chains. Green ammonia is one of the alternative fuels that can accomplish net-zero targets of the industry. However, considerable challenges exist for green ammonia adoption as the future clean energy source in maritime transport. This study scrutinises the success factors of the industry-wide adoption of green ammonia. We examine the structural relationship between success factors to explore antecedents, illustrate the precedence relationships between success factors, and present a roadmap. We first determine success factors and then employ Interpretive Structural Modelling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) to reveal relationship between success factors and suggest a roadmap. The success factors of an alternative fuel adoption are the availability of the fuel, the cost of the fuel, R&D in the fuel, safety regulations of the fuel, propulsion technology, port infrastructure for the fuel, stakeholder support, setting of carbon tax, public awareness on emissions and early adopter companies using the fuel. 48 experts completed the ISM survey for green ammonia. Results indicate that the most fundamental success factors are stakeholder support, carbon taxation, public awareness, and the number of early adopters. These fundamental success factors would pave the way to safety regulations of ammonia and R&D progress, which would then improve ammonia-powered propulsion systems and support a vast availability of green ammonia. Following the accomplishment of the above listed success factors, ammonia cost reduction and port infrastructure development can be delivered.
... They use statistical distributions of the main engine, auxiliary engine, and thermal power for thermodynamic cycle optimisation (Baldi et al., 2015a,b;Shu et al., 2017) or a number of typical steady state operating (Sakalis and Frangopoulos, 2018). A similar strategy uses these power profiles in the time domain to examine different system configurations (Dedes et al., 2012(Dedes et al., , 2016Ancona et al., 2018). The work proposed in this paper differs from these studies as it examines the aggregate effect of different operational and environmental conditions over selected voyages of the complete energy system rather than each parameter or subsystem separately. ...
... Finally, energy performance analysis and optimisation at a component and subsystem level is also dominated by the use of steady state models, although these models can vary in their level of detail. For example, applications in finding optimal configurations use look-up tables (Dedes et al., 2012(Dedes et al., , 2016Ancona et al., 2018), but applications on optimising thermodynamic working cycles require much more detailed models based on energy efficiency analysis (Sakalis and Frangopoulos, 2018) or even exergy analysis (Baldi et al., 2015a,b;Shu et al., 2017). Those studies focus on the low-level examination of the system, nevertheless, they confirm the general practice of sacrificing time dependency for more detailed models and a higher number of simulations. ...
Maritime industry has set ambitious goals to drastically reduce its greenhouse gas emissions through stipulating
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and CII do not account for the operational and environmental uncertainty of operations at sea, even though
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operational data offers the opportunity to quantify and account for this uncertainty in energy
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system level do not sufficiently account for operational and environmental uncertainty. In this work, we
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propulsion system of an Ocean-going Patrol Vessel (OPV) of the Royal Netherlands Navy under the aggregate
effect of operational and environmental uncertainty. It combines first-principle steady-state models with
machine learning algorithms to reach an accuracy of less than 5% MAPE on both mechanical and electrical
propulsion, while bringing a 40% to 50% improvement over a model that does not utilise machine learning
algorithms. Results over actual voyage intervals indicate a prediction accuracy of consumed fuel and carbon
intensity within 2.5% accounting for a confidence interval of 95%. Finally, the direct comparison between
mechanical and electrical propulsion showed no clear energy-saving benefits and a strong dependency of the
results on each voyage’s specific operational and environmental conditions.
... Third, small boats are a diverse segment of shipping and usage depends on the geographical location, type of activity, construction and operating costs and accessibility to fuel or bunkering infrastructure [18]. Similarly, engine providers are extensive, giving a broad range of fuel consumption curves and emissions [19][20][21]. ...
Tracking and measuring national carbon footprints is key to achieving the ambitious goals set by the Paris Agreement on carbon emissions. According to statistics, more than 10% of global transportation carbon emissions result from shipping. However, accurate tracking of the emissions of the small boat segment is not well established. Past research looked into the role played by small boat fleets in terms of greenhouse gases, but this has relied either on high-level technological and operational assumptions or the installation of global navigation satellite system sensors to understand how this vessel class behaves. This research is undertaken mainly in relation to fishing and recreational boats. With the advent of open-access satellite imagery and its ever-increasing resolution, it can support innovative methodologies that could eventually lead to the quantification of greenhouse gas emissions. Our work used deep learning algorithms to detect small boats in three cities in the Gulf of California in Mexico. The work produced a methodology named BoatNet that can detect, measure and classify small boats with leisure boats and fishing boats even under low-resolution and blurry satellite images, achieving an accuracy of 93.9% with a precision of 74.0%. Future work should focus on attributing a boat activity to fuel consumption and operational profile to estimate small boat greenhouse gas emissions in any given region.
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... The world's first hybrid tug was delivered in November 2009 and is powered by two diesel generators and lead-acid batteries [5]. In 2013, a hybrid ferry based on lithium battery energy storage was delivered in Germany. ...
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... In [26], a battery system operation is investigated alongside a diesel generator for a ship crane. In [27], a battery system is studied to maximize fuel savings in electric power system-based ships. Several control strategies have been evaluated in [26] to increase battery life and reduce fuel consumption. ...
Hybrid renewable energy systems are becoming widely prevalent in warships due to their reliability and acceptability. However, the uncertainty caused by using renewable energy resources is one of the primary challenges. Therefore, this paper investigates the implementation of a dynamic voltage restorer (DVR) with a new control strategy in a hybrid solar power generation system, including photovoltaic (PV) panels, diesel generators, battery storage, and conventional and sensitive loads. Furthermore, a new metaheuristic-based active disturbance rejection control (ADRC) strategy for fast and accurate DVR control is proposed. In this regard, a novel chimp optimization algorithm (ChOA)-based (i.e., ChOA-ADRC) strategy is suggested to increase the stability and robustness of the aforementioned hybrid system. The ADRC controller’s parameters are updated in real-time using the ChOA approach as an automatic tuning mechanism. In order to evaluate the performance of the proposed control strategy, the model is evaluated under two and three-phase fault case scenarios. Also, a comparison with the conventional PI controller has been performed to further evaluate the proposed method. Simulation findings reveal the suggested control strategy’s remarkable effectiveness in correcting fault-caused voltage drop and maintaining sensitive load voltage. Additionally, the results show that ChOA-ADRC presents a better dynamic response compared to conventional control strategies and increases the reliability of the hybrid power generation system.
... From the figure it can be observed the very different trend of the BSFC contours and of the power limit curves that characterize the two engines versions (unfortunately similar data are not available for the GE12V228 engine). The BSFC contours of the 900 rpm Nmax engine (Fig. 2a) are characterized by a shape similar to that of most marine engines of the same category [5,6,10,11,12]. The BSFC contours of the 1000 rpm Nmax engine are instead characterized by a particular trend, that the authors have not found in any other similar engine with a single turbocharger. As shown in Fig. 2b, the BSFC contours characterized by a lower specific fuel consumption, have a tendency that brings them closer to each other near the power limit curve, when the engine speed decreases. ...
In this study two four-stroke marine diesel engines, characterized by very similar nominal power and speed, but with very different trend of the power lint curve and specific fuel consumption contours in the engine load diagram, are compared by simulation, using each of them as an alternative to the other engine, for the motorization of a conventional (mechanical) propulsion plant for a small cruise ship. It is thus possible to determine and compare the efficiencies of the two engines and the vessel propulsion system overall performance for different ship speeds. The results of the comparisons are presented and discussed in the paper.
... The batteries installed onboard the vessel enable load levelling between the power fluctuation that occurs when vessel speed increases, thus leading to a more efficient operation, a method known as the peak shaving strategy. The peak shaving strategy from the battery, which is a method for the battery to deliver power during times when high power is required for a smoother operation and recharge when less power is required, can allow the engine to run more efficiently [27]. The energy storage can be recharged with the "charge-discharge mode" when the engine is operating with lesser fuel consumption to reduce emissions and save fuel [28]. ...
The increasing environmental concerns due to emissions from the shipping industry have accelerated the interest in developing sustainable energy sources and alternatives to traditional hydrocarbon fuel sources to reduce carbon emissions. Predominantly, a hybrid power system is used via a combination of alternative energy sources with hydrocarbon fuel due to the relatively small energy efficiency of the former as compared to the latter. For such a hybrid system to operate efficiently, the power management on the multiple power sources has to be optimised and the power requirements for different vessel types with varying loading operation profiles have to be understood. This can be achieved by using energy management systems (EMS) or power management systems (PMS) and control methods for hybrid marine power systems. This review paper focuses on the different EMSs and control strategies adopted to optimise power management as well as reduce fuel consumption and thus the carbon emission for hybrid vessel systems. This paper first presents the different commonly used hybrid propulsion systems, i.e., diesel–mechanical, diesel–electric, fully electric and other hybrid systems. Then, a comprehensive review of the different EMSs and control method strategies is carried out, followed by a comparison of the alternative energy sources to diesel power. Finally, the gaps, challenges and future works for hybrid systems are discussed.
... Further, internal combustion engine operation adds to passenger discomfort through increased vibration levels [1]. Among the various possible alternatives to this configuration, the International Maritime Organization (IMO) identified the hybrid electric vessel concept [2]. A hybrid architecture, compared to a fully electric one, guarantee the same performance of the current diesel configurations, achieving a higher efficiency level and allows for electric running near terminals and residential or protected areas, reducing noise and pollution issues [3] [4]. ...
The coastal passenger transport in touristic areas like Costa Smeralda (Sardinia), Cinque terre (Liguria), Costiera Amalfitana (Campania), Venetian Lagoon (Veneto) and others, is constantly growing. At the same time, the sensitivity of authorities to the issue of environmental impact in those areas is leading the transportation companies to investigate technical solutions that can guarantee high volumes of passenger being as much as possible eco-friendly. Hybrid or full electric passenger vessels are becoming more and more popular, starting from this assumption the authors examined the possibility to combine state of art technologies, with an innovative approach to match the propulsion system with hull resistance data, in order to propose a passenger ferry capable to operate in protected areas with an extremely low impact on the environment and taking advantage also from a basic energy distribution ashore. The usage of new generation batteries, with the highest safety standards, will be also investigated. The paper starts from the determination of the operative profile for the ferry, evaluating the best solution in terms of efficiency and power management, considering the resistance data of various hulls, focusing on a traditional displacement hull, and then developing a study of the propulsion system through the usage of last generation generators with variable speed and batteries different from traditional Li-Fe-PO4, in order to achieve a high efficiency level.
