Due the concern about serious environmental pollution and fossil energy consumption, introducing solar generation into ship power systems has drawn greater attention. However, the penetration of solar energy will result in ship power system instability caused by the uncertainties of the solar irradiation. Unlike on land, the power generated by photovoltaic (PV) modules on the shipboard changes as the ship rolls. In this paper, a high-speed flywheel energy storage system (FESS) is modeled to smooth the PV power fluctuations and improve the power quality on a large oil tanker which contains a PV generation system, a diesel generator, a FESS, and various types of ship loads. Furthermore, constant torque angle control method combined with sinusoidal pulse width modulation (SPWM) approach is proposed to control the FESS charging and discharging. Different ship operating situations and the impact of the ship rolling is taken into consideration. The simulation results demonstrate the high efficiency and fast response of the flywheel energy storage system to enhance the stability of the proposed hybrid ship power system.

Renewable energy ship was regarded as one of the ship energy technologies with a good prospect. In order to study the application of solar and wind energy on ships in the marine environment and the impact of ship rolling on the system, the feasibility of applying solar energy and wind energy to ships was analyzed, and the structural composition of ship power system incorporating renewable energy source was studied. The model of the ship power system integrated with renewable energy was built in PSCAD/EMTDC simulation software. The layout of wind power generation system and photovoltaic power generation system was given for the actual ship, and the ship parameters and specific parameters of each simulation module were determined. It can be seen that the rolling of ship will cause fluctuations in the grid-connected power of the photovoltaic power generation system and the wind power generation system from the comparison of the simulation curves. Finally, a simulation experiment is provided to prove the access of the battery can well suppress the grid-connected power fluctuation caused by the rolling of the ship, which has an important impact on the stability of the ship power system with renewable energy.

A new energy ship is being developed to address energy shortages and greenhouse gas emissions. New energy ships feature low operational costs and zero emissions. This study discusses the characteristics and development of solar-powered ships, wind-powered ships, fuel cell-powered ships, and new energy hybrid ships. Three important technologies are used for the power system of the new energy ship: new-energy spatio-temporal prediction, ship power scheduling, and Digital Twin (DT). Research shows that new energy spatio-temporal prediction reduces the uncertainty for a ship power system. Ship power scheduling technology guarantees safety and low-carbon operation for the ship. DT simulates the navigational environment for the new energy ship to characterize the boundary of the shipboard’s new energy power generation. The future technical direction for new energy ship power systems is also being discussed.

In the current context of a demand for high-efficiency and high-performance motors, AC copper loss is a key factor limiting the power density improvements of high-speed motors. Due to the interaction of multiple factors affecting AC copper losses, there is a lack of comprehensive and consistent understanding of the loss mechanism. Moreover, existing analysis methods face limitations in either computational efficiency or result accuracy. To address this, this study proposed a fully analytical model for hollow conductor AC loss, derived from a detailed analysis of magnetic and current distributions within hollow conductors under high-frequency armature and air-gap magnetic fields. It also examines the correlation between the armature AC copper loss and induced AC copper loss. The model accounts for the nonlinear effects of the iron core by incorporating an anisotropic equivalent magnetic permeability. The model accuracy was verified under various magnetic field settings and hollow structure designs, with errors within 4% and 6% in comparison to simulation and experimental data, respectively. This study enhances understanding and computational precision of AC copper loss in high-speed motors and provides a refined model for performance analysis and optimization.

With the increasing penetration of wind power, not only the uncertainties but also the correlation among the wind farms should be considered in the power system analysis. In this paper, Clayton-Copula method is developed to model the multiple correlated wind distribution and a new point estimation method (PEM) is proposed to discretize the multi-correlated wind distribution. Furthermore, combining the proposed modeling and discretizing method with Hybrid Multi-Objective Particle Swarm Optimization (HMOPSO), a comprehensive algorithm is explored to minimize the power system cost and the emissions by searching the best placements and sizes of energy storage system (ESS) considering wind power uncertainties in multi-correlated wind farms. In addition, the variations of load are also taken into account. The IEEE 57-bus system is adopted to perform case studies using the proposed approach. The results clearly demonstrate the effectiveness of the proposed algorithm in determining the optimal storage allocations considering multi-correlated wind farms.

The operating conditions of all-electric tugboats are flexible and changeable. They are more complicated than conventional vessels in terms of joint voyages and power generation scheduling. To guarantee the reliable operation of the ship, a new coordinated optimization scheme that combines economy and operational reliability is proposed. It is based on the various operating conditions of the tugboat during its voyage, taking into account the random outages of equipment and load fluctuations due to speed and wave uncertainties. Due to the difficulty of implementing a stochastic sampling method with space-time coupling constraints (e.g., the voyage is related to propulsion load), an analytical approach is needed to transform the model into a readily solvable mixed-integer linear program (MINP) which attributes risk scenarios to load fluctuations under various conditional probabilities. In addition, this paper proposes an improved piecewise linearization method based on a differential evolutionary algorithm to speed up the solution process and improve computational accuracy. Meanwhile, the energy storage loss cost due to battery degradation is added to the optimization target. The battery’s cycle life is extended by rational scheduling of charging and discharging. Simulations validate this paper’s joint scheduling optimization scheme in multiple comparison experiments. The results show that it can effectively balance the economic and reliability levels under various risk scenarios and improve the environmental energy efficiency indicators.