All-electric ships are now a standard offering for energy/propulsion systems in boats. In this context, integrating fuel cells (FCs) as power sources in hybrid energy systems can be an interesting solution because of their high efficiency and low emission. The energy management strategy for different power sources has a great influence on the fuel consumption, dynamic performance and service life of these power sources. This paper presents a hybrid FC/battery power system for a low power boat. The hybrid system consists of the association of a proton exchange membrane fuel cell (PEMFC) and battery bank. The mathematical models for the components of the hybrid system are presented. These models are implemented in Matlab/Simulink environment. Simulations allow analyzing the dynamic performance and power allocation according to a typical driving cycle. In this system, an efficient energy management system (EMS) based on operation states is proposed. This EMS strategy determines the operating point of each component of the system in order to maximize the system efficiency. Simulation results validate the adequacy of the hybrid power system and the proposed EMS for real ship driving cycles.

The smart grid and electric vehicles (EVs) are widely used all over the world. As the key role, the Vehicle-to-Grid (V2G) has been attracting increasing attention. The bidirectional grid-connected AC/DC converter is one of the indispensable parts in the V2G system, which can realize bidirectional power flow and meet the power quality requirements for grid. A three-phase bidirectional grid-connected AC/DC converter is presented in this paper for V2G systems. It can be used to achieve the bidirectional power flow between EVs and grid, supply reactive power compensation, and smooth the power grid fluctuation. Firstly, the configuration of V2G systems is introduced, and the mathematical model of the AC/DC converter is built. Then, for bidirectional AC/DC converters, the grid voltage feedforward decoupling scheme is applied, and the analysis of PI control strategy is proposed and the controller is designed. The system simulation model is established based on MATLAB/Simulink, and the experiment platform of the bidirectional grid-connected converter for V2G is designed in lab. The simulation and experiment results are shown, and the results evaluate the effectiveness of the model and the performance of the applied control strategy.

Around the world, the development of electric vehicles is underway, including in maritime transportation. However, the development of clean energy vessels still has a long way to go. Fuel cells (FCs) are a relevant choice among the many clean energy sources to power clean energy vessels. However, due to the complex and drastic change in the shipload power, FCs need to be equipped with dynamic fast-response energy storage equipment to make up for it. For multiple energy storage devices connected in parallel, the state of charge (SOC) is not balanced, which affects their service life and the stability of the vessel microgrid, as well as slowing the speed and lowering the accuracy of SOC equalization. This paper proposes a distributed variable sag slope control strategy for vessels to improve SOC equalization, with a FC as the energy source and a battery and supercapacitor as the energy storage system (ESS). For the output power distribution problem of energy storage equipment caused by shipload power variation, a power distribution strategy with a variable filter time constant is used to improve the reasonableness of the output power distribution of energy-based lithium batteries and power-based supercapacitors. Meanwhile, this paper considers the power generation equipment’s service life and energy cost as the optimization objectives, considering the discharge depth of the energy storage equipment. Finally, a method based on the combination of the lithium battery SOC rule (the rule formulated according to the state of charge and load power change in energy storage equipment) and particle swarm optimization algorithm is proposed to solve this problem. The simulation results show that the proposed strategy improves the equalization speed and accuracy of the SOC of energy storage devices, fully realizes the characteristics of different energy storage devices, and reduces the life loss of energy storage devices.

This study mainly investigates the current and speed control strategies of a doubly-fed induction generator (DFIG), which is applied to a tidal stream turbine (TST). Indeed, DFIG using integer-order PI (IOPI) controller has been widely proposed in the applications with a similar system, especially in wind energy conversion system (WECS). However, these conventional controllers cannot deal with the problems caused by the parameter variations satisfactorily under complex and harsh operation conditions, and may even deteriorate the performance. As a result, a fractional-order PI (FOPI) controller is considered to improve the efficiency and performance of DFIG-based TST in this paper. The FOPI controller, developed from the traditional IOPI controller and the fractional calculus theory, has a lot of prominent merits in many aspects, such as robustness, stability, and dynamic performance. In this paper, the proposed control strategies are embedded into the whole TST model which contains the tidal stream turbine, and the generator. The obtained simulation results demonstrate the prominent effectiveness and advantages of the proposed strategies compared with the conventional IOPI controller in terms of overshoot, static error, adjustment time, and robustness. It implies that FOPI controller could be a good candidate in TST applications.

Wave compensation technology is crucial to the safety of the ship operation and the accurate placement of load. Its compensation efficiency and the gentle change of the rope tension are particularly important. In this paper, we adopt permanent magnet synchronous machine (PMSM) as the actuator to construct the basic wave compensation system. Firstly, the motion model of ship and load under wave action is established, and the fractional-order PID (FOPID) controller for the position loop of the PMSM is introduced. Then, the parameters of FOPID are optimized by genetic algorithm-particle swarm optimization (GAPSO) algorithm, which is based on genetic algorithms (GA) and particle swarm optimization (PSO) algorithms for better compensation performance. The wave synchronization strategy is used to simulate the load, when it needs to be taken into the water. The non-linear dynamic equations of the rope are solved by Lagrange mechanics and the heave displacement is obtained by time series prediction algorithm. Finally, the effect of wave compensation and wave synchronization strategy are verified on MATLAB/Simulink. The results show that after the compensation, the crane load can follow the set height value very well, the compensation efficiency can reach more than 94%, and the wave synchronization strategy significantly reduces the change of the rope tension.