Electric Ferries Research Articles

Impact analysis of uncoordinated electric ferry charging on distribution network

The maritime sector significantly contributes to greenhouse gas emissions, and implementing electric marine vessels can mitigate this emission. Replacing conventional ferries with EFs (Electric Ferries) necessitates dockyard charging stations, making it crucial to analyze the EF's charging impacts on the shore-side distribution network. This research examines the potential effects of uncoordinated EF charging on a regional Australian distribution network. Using OpenDSS (Open Distribution System Simulator) software, power flow impact analysis is conducted on a selected simulated distribution network, integrating BESSs (Battery Energy Storage Systems) as representation of proposed charging stations. The load demand is increased to 50 % and 80 %, given the actual demand is 15 % of the transformers’ capacities. The power flow results without BESSs serve as the base case. In uncoordinated mode, bus voltages decrease by 1 %-3 %, and load currents increase by 2 %-3.5 % compared to the base case. Additionally, lines and transformers near BESS-connected buses see a 1 % rise in power flow with increased total power consumption and loss. THD (Total Harmonic Distortion) and TDD (Total Demand Distortion) are over 5 % and 18 % in uncoordinated charging, which exceeds harmonics limits according to IEEE 519–2022 standards. These results may provide valuable insights for installing EF charging stations in distribution networks.

Unified Four Quadrant Control of Dual-Port Solar-Assisted Switched Reluctance Drive for Electric Ferries With Power Flow Management

Unified Four Quadrant Control of Dual-Port Solar-Assisted Switched Reluctance Drive for Electric Ferries With Power Flow Management

A Decision Support GIS Framework for Establishing Zero-Emission Maritime Networks: The Case of the Greek Coastal Shipping Network

Sustainability of maritime operations is a topic widely considered in recent years, as the shipping industry attempts to limit its environmental impact and meet the decarbonization goals set by the International Maritime Organization (IMO). As alternative fuels and newer ship technologies are gaining interest, the shift to more environmentally friendly fleets is quickly becoming a reality. In this context, potential areas for such shifts need to be determined, to expedite decarbonization efforts and provide passengers with a more sustainable way of travel. Greece is an insular country, with a complex coastal shipping network connecting the mainland with the islands and being of paramount importance for their economic growth. Recognizing accessibility and decarbonization needs, this paper examines whether the Greek coastal shipping network (GCSN) can be restructured, by introducing zero-emission sub-networks operated by electric ferries. The aim is to propose a methodological framework for the spatial analysis and evaluation of coastal networks, with the implementation of exploratory spatial data analysis (ESDA) methods and determination of local indicators of spatial association (LISA) with the help of geographic information systems (GIS). The proposed framework provides insight on whether and where such a restructuring is possible, with the introduction of new transshipment port hubs in the islands from which electric ferries could operate, thus determining potential electrification areas with additionally high renewable resource potential. Final conclusions indicate that a potential electrification of certain parts of the GCSN could be possible, while results for GHG emissions reduced by the introduction of electric ferries are calculated.

The synergy between the photovoltaic power systems and battery-powered electric ferries in the isolated energy system of an island

Islands have increased potential to integrate renewable energy sources (RES) into their energy systems and shift towards sustainable decarbonization. The intermittent electricity causes issues such as the mismatch between the energy demand and supply, the grid instability and the electricity price volatility. The integration of the battery-powered electric ferries (BEF) into the isolated energy system (IES) powered with RES can be considered as an economically and environmentally friendly solution for matching the demand with the supply, since all-electric ships can connect to the grid and provide positive or negative balancing power. The carbon dioxide (CO2) emissions from shipping operations can be reduced to zero by utilizing batteries as a power source. This paper deals with a holistic approach that demonstrates opportunities that implementation of BEF offers in the framework of IES of an island. A method for modelling energy supply for a 100% electric ferry transport is developed to reduce the critical excess electricity production (CEEP) from the photovoltaic (PV) power systems. The energy modelling of the IES was carried out in EnergyPLAN program. The results confirmed that synergy between the PV power systems and BEF can significantly reduce the CEEP, the operating system costs and the emissions of CO2.

The EPLANoptMAC model to plan the decarbonisation of the maritime transport sector of a small island

Islands have been identified as living labs for implementing innovative solutions so as to boost the green energy transition. In this context, energy modelling and planning are key to optimally design the future energy system and identify the most appropriate technologies for both power generation and energy system management. In this research, a Marginal Abatement Cost curve method, by means of the EPLANoptMAC model, is applied to identify the optimal energy mix for the island of Favignana, Italy. The optimisation uses the carbon avoidance cost as objective function in order to consider both environmental and economic aspects. In addition to standard technologies such as photovoltaic and battery energy storage demand response technologies that include the maritime transport and heating sectors are optimised. Particularly, the decarbonisation of the maritime transport sector is of utmost importance since it represents the biggest energy consumption and source of carbon dioxide emissions for small islands. Results show that photovoltaic is the main priority, followed by battery energy storages. Electric ferries are preferrable to hydrogen ones when enough renewable energy from photovoltaic is produced. The decarbonisation of the maritime transportation is preferable to the heating sector and is required to reach decarbonisation targets higher than 40%.

Seakeeping Analysis of a Double Ended Ferry

Awareness of environmental protection is increasing, especially in recent years when warnings of imminent climate change have begun to appear in public space. In addition to one of the most significant environmental pollutants, global maritime transport is also mentioned, where environmental pollution is explicitly in the form of exhaust gases from marine propulsion engines. The trend of developing environmentally friendly, so-called "eco" ships is on the rise, primarily in the development of electric ferries designed to transport passengers and vehicles on short routes. This paper deals with a seakeeping analysis of a double ended ferry which is intended for sea route between Brestova and Porozina in the North Adriatic. The adopted dimensions and shape of the ship, the characteristics of sea waves for the adopted spectrum will be presented, and then the obtained results, considering the limits of the ship operability related to passenger comfort and cargo safety. The analysis was performed using computer software "Sesame HydroD". A seakeeping estimation for the ferry is finally adopted and possible directions for future developments are proposed.

CO2 Emissions Reduction Measures for RO-RO Vessels on Non-Profitable Coastal Liner Passenger Transport

Reducing CO2 emissions from ships in unprofitable coastline transport using electricity and hydrogen has potential for island development to improve transport and protect biodiversity and nature. New technologies are a challenge for shipping companies and their introduction should be accompanied by a system of state aid for alternative energy sources. The energy requirements of an electric ferry for a route of up to 6 km were considered, as well as the amount of hydrogen needed to generate the electricity required to charge the ferry batteries to enable a state aid scheme. For a daily ferry operation, a specific fuel consumption of 60.6 g/kWh of liquid hydrogen is required in the system fuel cell with a total of 342.69 kg of hydrogen. Compared to marine diesel, the use of electric ferries leads to a reduction of CO2 emissions by up to 90%, including significantly lower NOx, Sox, and particulate matter (PM) emissions, and operating costs by up to 80%.

State of Charge Estimation Method for Lithium-Ion Batteries in All-Electric Ships Based on LSTM Neural Network

Abstract All-electric ships (AES) are considered an effective solution for reducing greenhouse gas emissions as they are a platform to use clean energy sources such as lithium-ion batteries, fuel cells and solar cells instead of fossil fuel. Even though these batteries are a promising alternative, the accuracy of the battery state of charge (SOC) estimation is a critical factor for their safe and reliable operation. The SOC is a key indicator of battery residual capacity. Its estimation can effectively prevent battery over-discharge and over-charge. Next, this enables reliable estimation of the operation time of fully electric ferries, where little time is spent at the harbour, with limited time available for charging. Thus, battery management systems are essential. This paper presents a neural network model of battery SOC estimation, using a long short-term memory (LSTM) recurrent neural network (RNN) as a method for accurate estimation of the SOC in lithium-ion batteries. The current, voltage and surface temperature of the batteries are used as the inputs of the neural network. The influence of different numbers of neurons in the neural network’s hidden layer on the estimation error is analysed, and the estimation error of the neural network under different training times is compared. In addition, the hidden layer is varied from 1 to 3 layers of the LSTM nucleus and the SOC estimation error is analysed. The results show that the maximum absolute SOC estimation error of the LSTM RNN is 1.96% and the root mean square error is 0.986%, which validates the feasibility of the method.

Reducing vessel noise: An example of a solar-electric passenger ferry.

Concern over the impacts of anthropogenic noise on aquatic fauna is increasing, as is the number of vessels in the world's oceans, lakes, and rivers. Sound signatures of different vessel types are increasingly characterized, yet few reports are available on solar-electric powered vessels. Such data are important to model the sound levels experienced by marine fauna and their potential impacts. Sounds from two vessel types were recorded in the shallow waters of the Swan River, Western Australia, using bottom-mounted OceanInstruments SoundTraps. Multiple passes from two 10-m solar-electric powered passenger ferries and, for comparison, two 25-m conventionally powered (inboard diesel engine) passenger ferries were selected. Analysis was conducted on 58 and 16 passes by the electric ferries (in 2016 and 2017-2018, respectively) and 10 and 14 passes by the conventional ferry (2016 and 2017-2018, respectively) at 5-m range. At 55-m range, analysis was conducted on 17 and 1 passes by the electric ferry (2016 and 2017-2018, respectively) and 9 and 3 passes of the conventional ferry (2016 and 2017-2018, respectively). Measured received levels and modeled sound propagation were then used to estimate monopole source levels (MSL) and radiated noise levels (RNL). At 55-m range, the conventionally powered ferry type produced 156 and 157 dB re 1 μPa2m2 MSL and RNL, respectively, while the same metrics for the electric ferry were 12 dB lower. At frequencies below 500 Hz, spectral levels of the electric ferry at a range of <5 m were 10-25 dB lower than those of the conventional ferry, implying a potential benefit for animals that use low-frequency communication, if electric motors replaced petrol or diesel engines.

Model predictive energy management in hybrid ferry grids

High performance and cost-effective ferry boats are of capital interest for customers and marine industry companies. On the other hand, the traditional ferry boats, operated by diesel generators, spatter the atmosphere with CO2 emissions and detrimental particles. Hence, electric propulsion in marine applications, especially in ferry vessel systems, has gained a lot of attention during the last decade as a promising technology to decrease fuel consumption and emissions. However, one of the main issues in the electric ferries (E-Ferry) is to keep the voltage and frequency within an acceptable range according to the large dynamic load fluctuations. In order to solve this issue, this paper presents a model predictive energy management based on a modified black hole algorithm (BHA) for the hybrid E-Ferry systems. Finally, to study the efficiency of our proposal, we run a real-time simulation using the d-Space simulator and compare the effect of the prediction horizon on the system performance.

Towards a modular product architecture for electric ferries using Model-Based Systems Engineering

With the reduction of the allowed emission values, the need for fast and emission-free passenger transport is growing - even on coastal or inner city waterways. Many cities and regions are therefore striving to quickly replace their existing conventional diesel ferries with electrically powered passenger ferries. Shipbuilding, however, is characterized by individual applications and corresponding one-off productions. While the concept of modularization has proven itself in many industries to realize individual products in a short development time, such approaches are hardly found in the maritime industry. In particular, the high degree of dependency between the individual system elements of a ship represents a major challenge in the development of modular ships and ship architectures. This dependencies are further increased in the case of electrically driven high-speed ships, which in the present case are used for passenger transport in urban areas. This paper presents an approach for identifying reusable and standardized modules in shipbuilding for high-speed vessels using Model-Based Systems Engineering methods. The goal of the approach is to create a multi-domain system model that enables developers to identify use-case spanning standard modules and interfaces.

Hybrid algorithm for optimal operation of hybrid energy systems in electric ferries

The move towards electrification of marine vessels enables the development of more efficient vessels by reducing fuel consumption and emissions. This includes incorporating electrical energy sources, storage systems and interfacing power electronic converters which increase system complexity. Therefore, an accurate and efficient power management system (PMS) is essential to achieve the optimum operation. This study aims to develop a novel hybrid meta-heuristic algorithm-based PMS for the fuel savings of hybrid electric ferries. The ferry power system used in this study comprises two diesel generator sets and a battery storage system. The proposed hybrid PMS method applies an interactive approach on the basis of a grey wolf optimizer (GWO) and fuzzy expert system to improve the computational efficiency of the algorithm. Measured load data from an existing short-haul ferry are used in the simulation under two load scenarios: normal and high load demands. The proposed fuzzy logic-grey wolf optimizer (FL-GWO) aims to minimize the operating cost of the proposed system while satisfying all operational and technical constraints of the ferry. Results show that the proposed FL-GWO provided a more accurate optimal solution set with less standard deviation than the GWO. The proposed method realized up to 3.14% and 1.81% fuel savings in normal- and high-load scenarios, respectively, compared with GWO. Moreover, the sensitivity analysis indicates that charging the battery from the onboard generators in a more uniform rate over the entire cruising period reduces the fuel consumption.

Power management optimization of hybrid power systems in electric ferries

The integration of more-electric technologies, such as energy storage systems (ESSs) and electric propulsion, has gained attention in recent years as a promising approach to reduce fuel consumption and emissions in the maritime industry. In this context, hybrid power systems (HPSs) with direct current (DC) distribution are currently gaining a commendable interest in research and industrial applications. This paper examines the impact of using HPS with DC distribution and a battery energy storage system (BESS) over a conventional AC power system for short haul roll-on/roll-off (RORO) ferries. An electric ferry with a HPS is modeled in this study and the power management system is simulated using the Matlab/Simulink software. The result is validated using measured load profile of a ferry. The performance of the DC HPS is compared with the conventional AC system based on fuel consumption and emission reductions. An approach to estimate the fuel consumption of the diesel engine through calculation of specific fuel oil consumption (SFOC) is also presented. This study uses two optimization techniques: a classical power management method namely Rule-Based control (RB) and a meta-heuristic power management method known as Grey Wolf Optimization (GWO) to optimally manage the power sharing of the proposed HPS. Fuel consumption and emission indicators are also used to assess the performance of the two power management methods. The simulation results show that the HPS provides a 2.91% and 7.48% fuel consumption reduction using RB method and GWO method respectively. It is apparent from the result that the HPS has more fuel savings while running the diesel generator sets (DGs) at higher operational efficiency. It is interesting that the proposed HPS using both power management methods provided a 100% emission reduction at berth. Finally, it was found that using a meta-heuristic optimization algorithm provides better fuel and emission reductions than a classical method.

Wireless Charging for Ships: High-Power Inductive Charging for Battery Electric and Plug-In Hybrid Vessels

This article discusses the general challenges of high-power battery charging in marine applications, with a focus on electric ferries that have tight schedules and short docking times. For such applications, inductive wireless power transfer allows for safe and fully automated operations with better utilization of the docking time for charging the batteries. Battery charging for ship applications requires higher power levels in a single charging unit than what has been demonstrated for public transportation systems like buses and trams. The technical challenges of designing high-power inductive charging systems in marine applications are discussed, and the general characteristics of a solution developed for power transfer in the range of 1-2 MW are described. The presented concept, envisioned as an integrated part of a zero emission ferry in Figure 1, has been demonstrated in fullscale laboratory environments and is currently being installed for testing in regular operation on the Norwegian ferry MS Folgefonn, which is a plug-in hybrid vessel being used for industrial demonstration projects.