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The maritime sector is striving to lessen its dependence on fossil fuels, motivated by both economic factors related to fuel efficiency and the policies established by the International Maritime Organization (IMO). Consequently, there has been a growing focus on developing and deploying all-electric ships (AES) as a more sustainable alternative to conventional fossil fuel-powered vessels. AES presents several advantages over conventional ships, including zero emissions, enhanced energy efficiency, and greater sustainability. However, the implementation of AES also brings new challenges, such as the necessity to manage a hybrid microgrid and optimize voyage scheduling. Hybrid fuel cell (FC)-battery energy storage (BES) technology can significantly contribute to addressing these requirements. To tackle these challenges, this article introduces a comprehensive framework for the optimal planning of hybrid microgrids and voyage scheduling in AES. The framework incorporates multi-objective optimization techniques based on genetic algorithms to achieve a balance between cost and voyage time. The proposed framework is applied to a case study of a ship operating on a fixed route between two ports. The simulation results indicated that the total cost per voyage, associated with the objective function of cost minimization and voyage time reduction, has decreased by 12% and increased by 40%, respectively, when compared to the regular ship speed profile. Additionally, the travel time has been reduced by half an hour and 2 h, respectively, in comparison to the regular ship speed profile. To verify the results, the optimization problem for cost and voyage scheduling is also solved by Mayfly Algorithm (MA) separately. Thus, it can be illustrated the effectiveness of the framework in enhancing energy efficiency and fuel economy while preserving the ship's performance. • Fuel cell-powered ship's energy management and voyage scheduling co-optimization. • All-electric ship (AES) optimal planning for economic and sustainable operation. • Considering ship speed profile management in optimal AES voyage scheduling. • Incorporating the dimensional constraints into the AES optimal design strategy. • Considering generation reserve capacity to supply unanticipated shipboard demands. [ABSTRACT FROM AUTHOR]

The study aims to evaluate system combinations including batteries and electric motors for the all-electric training ship and to develop a shore facility with photovoltaic solar panels for battery charging. To achieve the objectives, the ship's power requirements were calculated using Savitsky and Wyman methods. Specifications of the propulsion units were decided by utilizing three different driving cycles and a battery discharge simulation for these cycles was ensured. Then, time series analyses forecasted the discharge durations, and lifespans of the batteries. Finally, economic performance comparison and the ranking of the configurations were provided. Results indicate that nominal battery capacities are detected as 21.39, 39.22, and 7.51 kWh, having 4.86, 9.13, and 11.53-hours' usage range, and payback periods of the configurations are 8.19, 6.88, and 8.05 years for each driving cycle. The configuration designed regarding the third driving cycle is the most feasible according to the multi-criteria decision-making analysis. [ABSTRACT FROM AUTHOR]

The All-electric ship (AES) concept has revolutionized the maritime sector. Indeed, AES is a promising solution for modern vessels where decreasing emission pollution, suppressing fossil fuel consumption, and making economical operation are its brilliant merits. Fuel cell (FC) technology based on clean hydrogen energy sources can play a significant role in meeting these requirements in the AES platform. Because of the slow transient response of the FC, an energy storage system (ESS) is required to improve AES performance in different operation scenarios. Therefore, optimal sizing of the FC and the ESS and proper design of energy management strategy is a challenging problem. This paper proposes a systematic approach for the optimal design of hybrid FC-ESS of AES power systems. The proposed method is based on an optimization technique to determine the optimal sizing of the FCs and the ESS. Capital investment, fuel consumption, personnel electrical safety, and occupied volume of the AES power system are the main objectives. The FC size, the battery size, the scheduled output power of the FC, and the battery are the decision variables. Genetic Algorithm (GA) is used to solve the optimization problem. To validate the numerical results, the optimization problem is also solved by Mayfly Algorithm (MA) separately. To assess the feasibility of the proposed strategy, the optimal design of hybrid FC-ESS for a vessel is implemented based on the proposed method. The simulation results validate the proposed approach's sufficiency to investigate and optimize the economic, safety, and dimensional aspects of designing the FC ship's IPS. Numerical results are reported for each design aspect. Considering the minor differences of the numerical results obtained by GA and MA, the optimum points are validated by the two techniques. Using the obtained results, various perceptions can be derived from the FC ship's IPS design. For example, the IPS cost in the cases with optimum volume, weight, and safety, has 2.3%, 2.6%, and 7.3% penalties, respectively compared to the case with the minimum cost. • Fuel cell-based electrification of a fishing ship based on practical information. • Systematic approach for optimal power system design of hydrogen-powered ship. • Proposing safety objective function for integrated power system of fuel cell ship. • Fuel cell hybrid IPS optimization based on volume, mass, cost and safety. • Estimation of propulsion power demand based on ship's resistance and speed profile. [ABSTRACT FROM AUTHOR]

The increasing global warming problem has pushed the community to implement emission reduction measures in almost every segment of human life. Since the major source of anthropogenic Greenhouse Gases (GHGs) is fossil fuel combustion, in the shipping sector, these measures are oriented toward a reduction in tailpipe emissions, where the replacement of traditional internal combustion marine engines with zero-carbon technologies offers the ultimate emission reduction results. According to the International Maritime Organization (IMO) GHG strategy, vessels involved in international shipping must achieve a minimum 50% reduction in their GHG emissions by 2050. However, this requirement does not extend to fishing vessels, which are significant consumers of fossil fuels. This paper deals with the full electrification of two types of fishing vessels (purse seiners and trawlers), wherein different Lithium-ion Batteries (LiBs) are considered. To investigate their environmental footprint and profitability, Life-Cycle Assessments (LCAs) and Life-Cycle Cost Assessments (LCCAs) are performed. The comparison of all-electric fishing vessels with existing diesel-powered ships highlighted the Lithium Iron Phosphate (LFP) battery as the most suitable alternative powering option regarding environmental and economic criteria. [ABSTRACT FROM AUTHOR]

The electrified hybrid shipboard power system with high-level integration of renewable energy resources and energy storage system has become the new trend for the all-electric ship (AES) configuration. However, the traditional rule-based energy management system (EMS) is not able to fulfill the increasingly complex control requirements, and a more advanced EMS control algorithm is required to handle the multiple power sources and even achieve optimal energy management control. This paper proposes a supervisory-level EMS with an improved adaptive model predictive control (AMPC) strategy to optimize the power split among the hybrid power sources and to reduce the total cost of ownership (TCO) of vessel operation, which considers not only the fuel and emission costs but also the power source degradation. In order to achieve real-time implementation, the AMPC-based EMS software has been developed and deployed to a programmable logic controller (PLC) hardware. The prototyping controller verification tests have been performed with a hybrid fuel cell-fed shipboard power system hardware-in-the-loop (HIL) plant in the lab environment. Three typical tugboat load profiles with power fluctuations are implemented as case studies. Lastly, a cost study was performed to compute the economic benefits for a ten-year long-term vessel operational cycle. The proposed AMPC-based EMS is robust and effective, which can achieve up to 12.19% TCO savings compared to those of a traditional rule-based control strategy.

Abstract This paper proposes a three‐layer framework for energy efficiency evaluation of Shore‐to‐Ship Charging (S2SC) systems using load‐dependent loss models of the components. The considered S2SC system is supplied by the grid but is also supported by On‐Shore Batteries (OSB). The presented approach is then used to investigate the impact of the specific design and operational parameters on energy efficiency. Power system architectures for three general S2SC solutions for ac, dc, and inductive charging are defined and compared in terms of energy efficiency. Operational parameters are also considered in the analysis, namely, the grid power ratio, determining the load sharing between the grid and the OSB, as well as the OSB charging profile. A case study is performed with peak charging power of 1 MW, and the most efficient S2SC solutions are identified for both ac‐ and dc‐based onboard power systems. Moreover, it is shown that charging OSB with the highest available power from the grid between the charging breaks would often lead to higher energy efficiency than the maximum utilization of the available charging time. Field data from a real S2SC system is used to verify the estimated energy efficiency by the proposed framework. The analysis of the real case S2SC is then extended to include and verify a projected OSB.

The unfolding of MVDC (Medium Voltage DC) systems has the prospects to enable the incorporation of power electronic converters with higher power density and reliability. A tool with an integrated design approach is required to minimise the overall system volume by identifying optimal components. In this paper, a component-level early-stage design tool has been developed to attain the minimum achievable volume and failure rate for MVDC power converters. The developed tool optimises the choice of semiconductor switching devices, required heatsink, and other passive components (including dc-link filters and inductors) to minimise failure rate and overall converter volume. The optimisation algorithm employs the non-dominated sorting genetic algorithm (NSGA-II) to evaluate designs based on developed fitness functions. The design tool demonstrates the trade-off when evaluating multiple converter topologies and helps make an informed decision. A comparative study between two converter topologies shows the outcomes in terms of targeted metrics (volume and failure rate). This tool is expected to benefit early-stage design to perform trade-off studies among power electronic converter topologies based on key metrics like volume and failure rate. [ABSTRACT FROM AUTHOR]

The increasing global warming problem has pushed the community to implement emission reduction measures in almost every segment of human life. Since the major source of anthropogenic Greenhouse Gases (GHGs) is fossil fuel combustion, in the shipping sector, these measures are oriented toward a reduction in tailpipe emissions, where the replacement of traditional internal combustion marine engines with zero-carbon technologies offers the ultimate emission reduction results. According to the International Maritime Organization (IMO) GHG strategy, vessels involved in international shipping must achieve a minimum 50% reduction in their GHG emissions by 2050. However, this requirement does not extend to fishing vessels, which are significant consumers of fossil fuels. This paper deals with the full electrification of two types of fishing vessels (purse seiners and trawlers), wherein different Lithium-ion Batteries (LiBs) are considered. To investigate their environmental footprint and profitability, Life-Cycle Assessments (LCAs) and Life-Cycle Cost Assessments (LCCAs) are performed. The comparison of all-electric fishing vessels with existing diesel-powered ships highlighted the Lithium Iron Phosphate (LFP) battery as the most suitable alternative powering option regarding environmental and economic criteria.

This paper proposes a three‐layer framework for energy efficiency evaluation of Shore‐to‐Ship Charging (S2SC) systems using load‐dependent loss models of the components. The considered S2SC system is supplied by the grid but is also supported by On‐Shore Batteries (OSB). The presented approach is then used to investigate the impact of the specific design and operational parameters on energy efficiency. Power system architectures for three general S2SC solutions for ac, dc, and inductive charging are defined and compared in terms of energy efficiency. Operational parameters are also considered in the analysis, namely, the grid power ratio, determining the load sharing between the grid and the OSB, as well as the OSB charging profile. A case study is performed with peak charging power of 1 MW, and the most efficient S2SC solutions are identified for both ac‐ and dc‐based onboard power systems. Moreover, it is shown that charging OSB with the highest available power from the grid between the charging breaks would often lead to higher energy efficiency than the maximum utilization of the available charging time. Field data from a real S2SC system is used to verify the estimated energy efficiency by the proposed framework. The analysis of the real case S2SC is then extended to include and verify a projected OSB. [ABSTRACT FROM AUTHOR]

The International Marine Organization (IMO) regulations forcing shipbuilders to use electric ships to reducing pollution emitted from ship engines. Renewable energy resources are the perfect solution to solve this issue. The ship’s hybrid energy power system consists of several non-homogeneous energy resources diesel generator, renewable energy source or more, energy-storing system, and may hydrogen source as fuel cells. The EMS manages and controls the balance between the different types of sources and loads demand to ensure system stability and dependability. In this paper, energy management strategy (EMS) for fuel cell and battery hybrid systems is an essential property of controlling power flow between sources. A crucial ingredient of an intelligent control strategy is to manage the flow of a hybrid system corresponding to the changing of the load demand and battery state of charge (SoC) using the ANFIS/Simulink toolbox implements a case study architecture. This paper proposes a hybrid energy source for use in a naval ship’s silent mode of operation while looking for submarines with a low acoustic signature based on adaptive neuro-fuzzy procedures. The main objective of this analysis is to investigate the efficiency of the proposed system preserving compared with practical results obtained from previous work. These studies provide valuable understandings into hybrid power systems’ flow of EMS on the marine field.

To address marine pollution caused by fuel usage and reduce carbon emissions in ships, the development of alternative fuel electric propulsion ship power systems presents a promising solution. In this study, an integrated Methanol-fueled SOFC-sCO 2 combined power system is proposed for all-electric ships. The system efficiently utilizes waste heat from SOFCs by integrating it into a partial heating sCO 2 power cycle to generate additional power. Through the utilization of a thermodynamic model, parametric sensitivity analysis and multi-objective optimization are conducted to maximize the system's energy efficiency while reducing investment and maintenance costs. Comprehensive energy, exergy, and economic analyses are performed on the optimized system. The achieved energy efficiency and exergy efficiency are 66.10 % and 57.74 % respectively, with an investment and maintenance cost of 16.96 $/h and a payback period of 2.2 years. When applied to container ships and compared with other ship power systems, the proposed system demonstrates the highest energy efficiency, delivering an impressive output power of 65,092 kW. The energy efficiency design index (EEDI) of the system is moderate, reaching 5.94. Despite the relatively high fuel cost, the proposed system offers a simpler design compared to existing SOFC-sCO 2 systems and is only slightly more complex than integrated systems like SOFC-GT. [Display omitted] [ABSTRACT FROM AUTHOR]

During the navigation of all-electric ships, a hybrid energy storage system (HESS) is required to compensate power imbalance and maintain bus voltage stability. For a HESS composed of multiple energy storage (ES) devices, an unreasonable power distribution causes the ES devices with a low state of charge (SoC) to draw from power supply early, which deepens the operating pressure of the other ES devices. This in turn, affects the stable operation of the entire system. To achieve power distribution based on the SoC of different ES devices, a novel power distribution strategy for use in all-electric ships was proposed. In the proposed strategy, the virtual impedance of an ES device is connected with the SoC through exponential functions. As a result, the output power can be dynamically changed according to changes of the SoC. On the premise of obtaining a proper dynamic power distribution among ES devices with complementary characteristics, the SoC balance among ES devices with the same characteristics can be realized. Meanwhile, the bus voltage deviation induced by the virtual resistor is eliminated via an added compensation voltage. The effectiveness of proposed method is verified by both simulations and a StarSim hardware in loop (HIL) experimental platform. [ABSTRACT FROM AUTHOR]

Unlike a land-based standalone microgrid, a shipboard microgrid of an all-electric ship (AES) needs to shut down generators during berthing at the port for exanimation and maintenance. Therefore, the cost of onshore power plays an important role in an economic operation for AESs. In order to fully exploit its potential, a two-stage joint scheduling model is proposed to optimally coordinate the power generation and voyage scheduling of an AES. Different from previous studies that only consider the operation cost of the ship itself, a novel coordinated framework is developed in this article to address the shore-side electricity price variations on the ship navigation route. A deep learning-based forecasting method is utilized to predict the electricity price in various harbors for ship operators. Then, a hybrid optimization algorithm is designed to solve the proposed multiobjective joint scheduling problem. A navigation route in Australia is adopted for case studies and simulation results demonstrate the high energy utilization efficiency of the proposed algorithm and the necessity of on-shore power influence on the AES voyage. [ABSTRACT FROM AUTHOR]

Multiple pulsed loads arise in all-electric ship power systems, which consume an enormous amount of energy in a short time. Moreover, pulsed load requirements may change rapidly, and a fast regulation method is indispensable for optimal energy management. To this end, the article formulates an optimal coordination problem and develops an online algorithm for a shipboard power system, where the periodic operation of pulsed loads is utilized. The problem is divided into two parts: i) the energy allocation for each pulsed load is optimized to maximize total utility; ii) the joint charging period is determined to supply pulsed loads in a shorter cycle. In the solution method, the Fourier series is used to represent the operation period of pulsed loads and accelerate the algorithm. Case studies on a shipboard power system with eight pulsed loads show that the proposed algorithm is effective, and applicable for online use. [ABSTRACT FROM AUTHOR]

Using different types of generation systems in ships, which are known as all‐electric ships, can play a key role in increasing economic benefits in the long term. On the other hand, electrical energy storage systems (EESSs) provide flexibility for supporting the electrical load of ships in the presence of renewable energy sources and the other generation units. Since power demands of a ship are not limited to an electrical load, combined heat and power (CHP) units can be considered as backup units for heat‐only units in addition to their economic and environmental advantages. In this study, new optimal power management is presented to handle a generation scheduling problem of a cruise ship for 12 h time intervals. In this regard, this method is based on the Lagrangian relaxation approach, a subset of ɛ‐constraint approaches, and the use of marginal cost to determine the performance of EESS in each time interval by taking all the constraints into account. The capability of the proposed algorithm is analysed by simulation results of a cruise ship, including conventional, CHP, EESS and heat‐only units, in order to achieve minimum operation cost with a short runtime. [ABSTRACT FROM AUTHOR]

Fully electrified ships, which is known as the “all-electric ships (AESs)”, have the potentials to bring great economic /environmental benefits. To further improve the energy efficiency of AESs, PV generations are gradually integrated, which introduces uncertainties to the AES operation. However, current researches mostly focus on sizing problem whereas rarely concern the operation. In this perspective, a data-driven robust coordination of generation and demand-side is proposed to properly address the onboard PV generation uncertainties as well as reducing the fuel cost of AESs, which consists of an extreme learning machine (ELM) based PV uncertainty forecasting method and a two-stage operating framework, where the first stage for the worst PV generation case and the second stage targets at the uncertainty realization. A 4-DG AES is implemented into the case study and the simulation results show that the ELM-based method can well characterize the PV uncertainties, and the two-stage operating framework can well accommodate the onboard PV uncertainties. Further analysis also demonstrates the proposed method has enough flexibility when facing working condition variations. [ABSTRACT FROM AUTHOR]

Due to the increasing impact of ship emissions on the environment and the preventive measures of current regulations introduced by the International Maritime Organization to significantly reduce them, the development of ocean-going all-electric ships has been addressed as a concept applied to achieve it. Being a promising technology considers the use of technology alternatives such as fuel cells, batteries, and supercapacitors together with the use of zero-carbon alternative fuels such as hydrogen (H2) and ammonia (NH3) as main energy sources. This article addresses a state-of-the-art on several challenges related to the ocean-going zero-emissions ship to achieve a zero-emissions shipping, based on the technology associated with hybrid and all-electric ship, and the zero-carbon fuels alternatives. In this respect, a transition from fossil fuel-based propulsion and auxiliary systems to a zero-emissions ship concept are related to the challenges to overcome the needs of energy density for these new alternatives energy sources compared to current fossil fuel options. The transitional process should consider a first step of hybridization of the propulsion and auxiliary systems of existing ships to get a baseline from where to move forward to a zero-emissions configuration for new designs.

with the onboard diesel generators and energy storage system to meet the propulsion and service load, the all-electric ship (AES) can be viewed as a ‘mobile microgrid’. Nowadays, photovoltaic (PV) generation is gradually integrated into the AES for a ‘greener’ voyage. To fully utilise the PV energy, this paper proposes a joint generation and voyage scheduling method for the PV integrated AES. The overall model is formulated as a bi-level programming problem and solved by column-and-constraint generation method. The simulation results manifest that, the integration of PV into AES leads to reductions on both the fuel consumption and CO2 emission.

With the strengthening of international environmental regulations, many studies on the integrated electric propulsion systems applicable to eco-friendly ship are being conducted. However, few studies have been performed to establish a guide line for the overall pure electric propulsion ship design. Therefore, this paper introduces the comprehensive design of DC shipboard power system for pure electric propulsion ship based on battery energy storage system (BESS). To design and configure the pure electric propulsion ship, 2 MW propulsion car ferry was assumed and adopted to be the target vessel in this paper. In order to design the overall system, a series of design processes, such as the decision of the ship operation profile, BESS capacity selection, configuration of the power conversion systems for propulsion, battery charging/discharging procedures, classification of system operation modes, and analysis of the efficiency, were considered. The proposed efficient design and analysis of the pure electric propulsion ship was qualitatively and quantitatively validated by MATLAB Simulink tool. The methodology presented in this paper can help design real ships before the system commissioning.

This paper proposes an energy management system (EMS) of the electrical system of a luxury ship (yacht). Starting from the analysis of the current configuration of the electric system, it proposes some solutions for its improvement, aiming at the reduction of the fuel consumption of the diesel engine (DE) driven permanent magnet synchronous generators (PMSG) and, therefore, at the reduction of the related ship polluting emissions. From the architectural side, a dc electrical distribution on-board has been adopted in place of the existing ac. Moreover, the dc micro-grid has been integrated with renewable energy sources (RES) based generators, as well as an energy storage system (ESS). From the management point of view, the proposed EMS governs the ship electric system in three working conditions: 1) regular operation; 2) DE driven PMSG fault/outage; 3) overload. During regular operation, the EMS implements the variable speed paradigm of the DE driven PMSGs on-board, permitting a reduction of the fuel consumption, and the related polluting emissions. In this phase, the ESS is exploited to minimize the speed and power transients of the DE. In case of a fault of one of the DE driven PMSGs, the ESS compensates the power missing for the entire duration of the cold start up of the auxiliary generator. In case of big overload, the ESS provides the exceeding power with respect to the rated one, thus avoiding potential micro-grid instability problems. This paper proposes also a stability analysis of the entire on-board dc micro-grid. [ABSTRACT FROM AUTHOR]

The all-electric ship (AES) usually employs battery energy storage systems (ESSs) in the shipboard microgrid. However, the battery-only storage usually experiences frequent deep discharging or charging to meet the sudden load variations in a voyage, which may lead to significant degradation of battery lifetime. This paper, hybridizes two types of ESSs and proposes a two-step multi-objective optimization method for hybrid ESS (HESS) management. The first step regulates the HESS with the onboard diesel generators to simultaneously optimize both the economic and environmental objectives, and the second step is to split the active power of HESS into two individual ESSs for minimizing the battery cycle degradation. The first step is formulated as a bi-level optimization model through constraint decomposition. Then, a normal boundary intersection method combining with the column-and-constraint generation algorithm is developed to solve the proposed model. Extensive simulations demonstrate that the HESS can effectively resolve the power-density shortage of the battery-only system, and its integration into AES is able to extend the battery lifetime and improve both the economic and environmental indices. [ABSTRACT FROM AUTHOR]

Highlights • Proposes a decentralized energy management strategy for enhancing the system resilience. • Applies the concept of cloud energy storage system to a shipboard power system. • Achieves cost reduction and privacy preservation in addition to enhanced resilience. Abstract The shipboard power system of an all-electric ship can be characterized as an isolated microgrid system. To achieve resilient, cost-effective and privacy-preserved operation of the shipboard power system, a novel energy management strategy is proposed in this paper. Currently, a master controller is required for energy management. However, such a centralized energy management strategy suffers from numerous disadvantages. Therefore, a modified nested energy management method is proposed to preserve privacy and run the microgrid system in a distributed manner for plug-and-play operation. Furthermore, the system resilience is enhanced against energy deficiency by reserving more in the energy storage system. This is achieved by a distributed algorithm, known as alternating direction method of multipliers (ADMM), to obtain the solution of an optimization problem with contradicting objectives. Simulation results are presented to demonstrate the benefits of proposed energy management system. [ABSTRACT FROM AUTHOR]

Electric ships experience large propulsion-load fluctuations on their drive shaft due to encountered waves and the rotational motion of the propeller, affecting the reliability of the shipboard power network and causing wear and tear. To address the load fluctuations, model predictive control has been explored as an effective solution. However, the load torque of the propulsion system, knowledge of which is essential for model predictive control, is difficult to measure and includes multi-frequency fluctuations. To deal with this issue, an adaptive model predictive control is developed so that the load torque estimation and prediction can be incorporated into model predictive control. In order to evaluate the effectiveness of the proposed adaptive model predictive control, an input observer with linear prediction is developed as an alternative approach to obtain the load estimation and prediction. Comparative studies are performed to illustrate the importance of the load torque estimation and prediction, and demonstrate the effectiveness of the proposed adaptive model predictive control in terms of improved efficiency, enhanced reliability and reduced wear and tear. [ABSTRACT FROM AUTHOR]

We present the development, coupling, and application of a quasi-3D multiphysics model of a notional all-electric ship electromagnetic launcher (EML) and a dynamic parallel-flow heat exchanger (PFHX) model to devise effective thermal management strategies for naval EMLs. The EML model combines a 2D electromagnetic-thermal model and a 3D thermal-fluid model developed based on the fundamental laws of electromagnetism, heat transfer, and fluid dynamics. Similarly, we applied the conservation laws to formulate a PFHX model and nondimensionalized it by identifying dimensionless parameters that pertained to the effectiveness-NTU method. We solved the coupled EML-PFHX model using finite element method and employed it to investigate the following aspects of naval EML thermal management: the effects of (1) thermal diffusion in the rail, (2) PFHX design and operation, and (3) cooling channel location on cooling performance and heat reversal. Subsequently, we deduced the following from our study: (1) thermal diffusion effectively assists the cooling channel with peak temperature reduction, and its contribution to the determination of optimal channel allocation is non-trivial; (2) improvement in cooling performance is not always directly proportional to larger heat exchanger size and higher flow rate—increased flow rate and NTU only result in higher pumping power as well as heat exchanger cost and volume without significant improvement in cooling performance beyond the optimal design and operating point; (3) placing the cooling channel close to the initial hot spot in the rail yields inferior cooling performance at high mass flow rate with 10 s of cooling and exacerbates the heat-reversal effect; and (4) optimal cooling channel allocation must therefore base on the given mass flow rate and cooling period—placing the channel near the initial hot spot is favorable for lower mass flow rates and shorter cooling periods, whereas channels should be placed at the rail center for equidistant heat flow from all four corners in the opposite case. [ABSTRACT FROM AUTHOR]

• Large-scale global optimization based parameter identification model for lithium battery. • Dynamical evolution strategy for parameter identification model. • Semi-online operation mechanism of cooperatively coevolving algorithm. • Information exchanging and solution inheriting by multiple context vectors. • Real-time output of optimal identification solution. Due to the special working environment of power lithium battery (P-LiB) on all-electric ships, the high-efficiency battery management system (BMS) is required. In this study, a novel semi-online parameter identification methodology integrated with large-scale global optimization algorithm is developed, in order to ensure the high-quality performance of subsequent BMS functions like the equalization control and state-of-charge estimation. Firstly, the P-LiB parameter identification model is established based on the first-order Thevenin equivalent circuit. Then, the evolution strategy of identification model is developed for dynamically updating the model along with the entire charging/discharging process of P-LiB. Considering that the model complexity increases exponentially with dimensionality, the AMCCDE algorithm developed in our previous work is employed to optimize the dynamic model repeatedly. Moreover, the semi-online operation mechanism for AMCCDE is proposed, in which the multiple context vectors are used to exchange information and inherit the optimal solution between each two adjacent semi-online cycles, and the identification solutions can be dynamically corrected and output at the end of each cycle. Finally, the developed semi-online identification methodology is verified using the USTC-DST and USTC-UDDS datasets. Experimental results show that the developed methodology can well balance the identification accuracy and timeliness, and dynamically output the accurate identification solutions in real-time. [ABSTRACT FROM AUTHOR]

Underwater radiated noise (URN) emanating from ships can adversely impact the life functions of certain marine mammals that rely on sound to navigate, communicate, and locate prey. This paper formulates an optimal voyage scheduling problem to mitigate the impact of URN on sensitive marine species by choosing amongst different possible paths and specifying the cruising speed along the selected path. We focus on all-electric ships (AESs) owing to their greater flexibility for speed regulation by coordinating an integrated power system. The proposed optimization model schedules generators and energy storage devices toward minimizing the operation cost while satisfying constraints pertinent to URN levels and atmospheric greenhouse gas (GHG) emissions, the electric power network and operational limits, and expected voyage timelines, culminating in a mixed-integer nonlinear programming problem. To promote computational tractability, we approximate the nonlinear relationships for URN, propulsion load, and fuel consumption with piecewise linear functions. This leads to a mixed-integer second-order cone programming problem, which enables convergence to the global optimum and computationally efficient solutions. We illustrate the effectiveness of the proposed model in curbing URN levels and GHG emissions with numerical case studies involving an 18-node ship test system. • Mitigating the impact of URN on sensitive marine species via efficient voyage plan. • Enabling selection between alternative paths connecting consecutive destinations. • Linearizing the nonlinear relationships for URN, propulsion load and fuel consumption. • Formulating a computationally efficient mixed-integer SOCP problem. • Illustrating the effectiveness of the proposed model with numerical case studies. [ABSTRACT FROM AUTHOR]

This paper presents the mathematical formulation and unique capability of a system-level ship thermal management tool, vemESRDC, developed to provide quick ship thermal responses in early design stages. The physical model combines principles of classical thermodynamics and heat transfer, along with appropriate empirical correlations to simplify the model and expedite the computations. As a result, the tool is capable of simulating dynamic thermal response of an entire ship, characterized by intricate thermal interactions within a complex ship structure, within an acceptable time frame. In this work, vemESRDC is demonstrated through three case studies in which transient thermal responses of an all-electric ship to different ship operation modes, weather conditions, and partial loss of cooling are investigated. The analysis examines particularly the following: (1) the required cooling capacities to maintain each ship component within its design limit; (2) equipment temperature variations with respect to partial cooling loss in battle mode; and (3) the assets of installing seawater heat exchangers to pre-cool deionized freshwater before chillers. For the notional all-electric ship conceived and assessed in this work, the results verify the capability of vemESRDC to capture dynamic thermal interactions between shipboard equipment and their respective surroundings and cooling systems, e.g., the tool provides practical insights into pulse load cooling strategy, and different solutions are obtained for distinct weather conditions. In addition to the case studies performed in this work, vemESRDC can be employed to conduct diverse studies based on which concrete ship thermal management strategies can be formulated in early design stages. [ABSTRACT FROM AUTHOR]

All-electric ships (AES) with energy storage systems (ESS) and solar photovoltaic (PV) are gaining popularity due to their capability to provide clean energy and improve operational efficiency. However, it introduces additional complexity to voyage and energy management schedules. Hence, this research proposes a data-driven many-objective voyage and energy management scheduling of AES with ESS and PV while considering non-linearity in constraints and objectives formulation. It minimizes fuel consumption, emission, ESS cumulative damage, and the operating cost of auxiliary units (PV, ESS, and shore-power supply). It investigates the performance of non-dominated sorting algorithms (NSGA-II and NSGA-III) on the proposed AES mathematical model. Furthermore, a long-short term memory (LSTM) based PV forecast is carried out based on the environmental factors, PV characteristics, and operation time to improve the voyage and energy dispatch accuracy. In addition, the proposed framework identifies the conflicting and associating objectives based on the Pearson correlation coefficients to establish the relationship between the objective functions. The result illustrates that the proposed non-linear AES model can converge to the solutions within 300 iterations. Hence, allowing the vessel operator to identify the desired operating points that meet the objectives and constraints quickly and efficiently. Furthermore, the correlation coefficients can identify respective associations and conflicting objective terms in the proposed coordinated AES voyage and energy dispatch model. • Detailed mathematical modeling of voyage and energy schedule optimization for AES. • Optimized many critical AES operations and voyage objectives simultaneously. • Addressed non-linearity, conflicting, and association in the problem formulation. • Used actual meteorological data, PV characteristics, and operation profiles. • Detailed case study and analysis to prove the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

As the oil shortage continues and the environmental regulation of emissions grows more restrictive, hydrogen becomes an attractive energetic vector. There are various possible applications for both merchant vessels and warships. Standard distributed electricity or emergency electrical requirements can be generated by fuel cells systems. Moreover, low propulsion power requirements or the total demand for electricity can also be supplied on ships equipped with electric propulsion by means of fuel cells. [ABSTRACT FROM AUTHOR]

Isolated microgrid power systems are prone to large frequency and voltage deviations, since they have limited generation and finite inertia and may include pulse power loads and large proportion of dynamic loads. Thus, they require effective power management methods to operate optimally, while satisfying operating and security constraints. In this paper, a novel integrated security-constrained model-based power management approach is proposed for isolated microgrids in all-electric ships during the normal/alert operating state. The new power management method was formulated as a multi-objective optimal control problem. A method based on the Nondominated Sorting Genetic Algorithm II was developed to solve the problem. The developed integrated security-constrained power management approach was applied to a notional all-electric ship computer model. The simulation results, conducted in PSCAD, showed the effectiveness of the new power management method. [ABSTRACT FROM PUBLISHER]

During recent years, optimal electrification of isolated offshore systems has become increasingly important and received extensive attention from the maritime industry. Especially with the introduction of electric propulsion, which has led to a total electrification of shipboard power systems known as all-electric ships (AESs), the need for more cost-effective and emission-aware solutions is augmented. Such onboard systems are prone to sudden load variations due to the changing weather conditions as well as mission profile, thus they require effective power management systems (PMSs) to operate optimally under different working conditions. In this paper, coordinated optimal power management at the supply/demand side of a given AES is studied with regard to different objectives and related technical/environmental constraints. The optimal power management problem is formulated as a mixed-integer nonlinear programming (MINLP) model and is solved using a metaheuristic algorithm. To show the effectiveness and applicability of the proposed PMS, several test scenarios are implemented and related simulation results are analyzed and compared to those from conventional methods.

The main motivation for writing this article is to develop a model library for an All-Electric Ship that gives an opportunity to simulate both existing and new machinery systems without having to remodel the entire system each time. The model library should support the process of modelling and reuse, while also emphasizing openness to brace the modeller during the development and refinement phase. The bond graph approach is good when it comes to the physical modelling of systems and is a good tool for combining different energy domains to better help in understanding the system. In addition, a bond graph is a powerful method to find dependencies between various components. Using a causal analysis, any problems in the model, for example, algebraic constrains or dependent system variables, will be detected, and the necessary remodelling may be performed to handle such problems. The bond graph approach is therefore used when developing the component library. The component library consists of selected power producers such as diesel and gas engines, fuel cell and synchronous generator and power consumers such as asynchronous motor with a voltage source converter in addition to a generic load used for hotel and auxiliary loads. The library also consists of a ship model and propeller models. [ABSTRACT FROM AUTHOR]

Future ship integrated power systems (IPSs) will be characterized by complex topologies of advanced power electronics and other evolving components. Advanced capabilities, such as intelligent reconfiguration of system function and connectivity will be possible; however, system level knowledge of component failure will be needed for intelligent power distribution under failure mode conditions. Diagnostic and prognostic coverage for sensors, components, and subsystems will be essential for achieving reliability goals. This paper will look at some diagnostic requirements and emerging technologies available for insertion into future ship IPSs. [ABSTRACT FROM AUTHOR]

Due to the increasing impact of ship emissions on the environment and the preventive measures of current regulations introduced by the International Maritime Organization to significantly reduce them, the development of ocean-going all-electric ships has been addressed as a concept applied to achieve it. Being a promising technology considers the use of technology alternatives such as fuel cells, batteries, and supercapacitors together with the use of zero-carbon alternative fuels such as hydrogen ( H 2 ) and ammonia ( N H 3 ) as main energy sources. This article addresses a state-of-the-art on several challenges related to the ocean-going zero-emissions ship to achieve a zero-emissions shipping, based on the technology associated with hybrid and all-electric ship, and the zero-carbon fuels alternatives. In this respect, a transition from fossil fuel-based propulsion and auxiliary systems to a zero-emissions ship concept are related to the challenges to overcome the needs of energy density for these new alternatives energy sources compared to current fossil fuel options. The transitional process should consider a first step of hybridization of the propulsion and auxiliary systems of existing ships to get a baseline from where to move forward to a zero-emissions configuration for new designs. [ABSTRACT FROM AUTHOR]

With the strengthening of international environmental regulations, many studies on the integrated electric propulsion systems applicable to eco-friendly ship are being conducted. However, few studies have been performed to establish a guide line for the overall pure electric propulsion ship design. Therefore, this paper introduces the comprehensive design of DC shipboard power system for pure electric propulsion ship based on battery energy storage system (BESS). To design and configure the pure electric propulsion ship, 2 MW propulsion car ferry was assumed and adopted to be the target vessel in this paper. In order to design the overall system, a series of design processes, such as the decision of the ship operation profile, BESS capacity selection, configuration of the power conversion systems for propulsion, battery charging/discharging procedures, classification of system operation modes, and analysis of the efficiency, were considered. The proposed efficient design and analysis of the pure electric propulsion ship was qualitatively and quantitatively validated by MATLAB Simulink tool. The methodology presented in this paper can help design real ships before the system commissioning. [ABSTRACT FROM AUTHOR]

In order to comply with stringent environmental regulations, shipbuilders and ship-owners are seeking cleaner fuels and the integration of renewable energy sources into ship power systems. Such solutions regularly result in additional costs for ship operators, both in the case of retrofitting existing ships or acquiring completely new vessels. This paper deals with the life-cycle cost assessments (LCCAs) of different power system configurations of a ro-ro passenger vessel operating in the Croatian short-sea shipping sector. Electrification of the ship is considered as an option to reduce the carbon footprint (CF) of the vessel and to achieve economic savings during its lifetime. In this sense, the ship operational profile is analysed and its total power needs are determined. The life-cycle assessments of an existing diesel engine-powered solution and two potential battery-powered ship options (with and without photovoltaic cells) are performed by means of GREET 2018 software. Furthermore, these options are compared from an economical viewpoint, where different carbon credit scenarios are investigated. The results show that a diesel engine-powered vessel has the highest carbon footprint, as expected. However, it is also found that a battery-powered vessel (with or without photovoltaic cells) has a minimum environmental footprint and at the same time represents economically the most favourable solution for all possible carbon allowance scenarios. This indicates that all-electric ships seem to be a promising option for the future development of the Croatian short-sea shipping sector. • The applicability of different power sources in short-sea shipping is investigated. • LCAs and LCCAs of different power options for ro-ro vessels are performed. • The influence of carbon credit policies in the marine sector is considered. • The electrification of the Croatian ro-ro fleet is a viable option to reduce the CF. [ABSTRACT FROM AUTHOR]