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High-temperature superconducting materials have shown great potential for the design of large-scale industry applications. However, they are complicated under AC conditions, resulting in penalties such as power loss or AC loss. This loss has to be considered in order to design reliable and efficient superconducting devices. Furthermore, when superconductors are used in rotating machines, they may be exposed to rotating magnetic fields, which is critical for the design of such machines. Existing AC loss measuring techniques are limited to measuring under one-dimensional AC magnetic fields or transport currents. Therefore, it is essential to develop and investigate robust experimental techniques to investigate the loss mechanism in HTS machines. In this paper, a new and novel experimental technique has been presented to measure AC loss in rotating magnetic field conditions. The loss under rotating magnetic fields is measured and compared by numerical modeling methods, and the results show a strong correlation with the numerical modeling and show the effectiveness of the experimental setup.

High-temperature superconductor (HTS) bulks have shown very promising potential for industrial applications due to the ability to trap much higher magnetic fields compared to traditional permanent magnets. In rotating electrical machines, the magnetic field is a combination of alternating and rotating fields. On the contrary, all studies on electromagnetic characterization of HTS presented in the literature so far have only focused on alternating AC magnetic fields and alternating AC loss due to the unavailability of robust experimental techniques and analytical models. This paper presents a numerical investigation on the characterization of HTS bulks subjected to rotating magnetic fields showing AC loss, current density distribution in three-dimensional axes, and trapped field analysis. A three-dimensional numerical model has been developed using H-formulation based on finite element analysis. An HTS cubic sample is magnetized and demagnetized with two-dimensional magnetic flux density vectors rotating in circular orientation around the XOY, XOZ, and YOZ planes.

Due to the pressures caused by the energy crisis, environmental pollution, and international regulations, the largest ship-producing nations are exploring renewable resources, such as wind power, solar energy, and fuel cells to save energy and develop more environmentally-friendly ships. Solar energy has recently attracted a great deal of attention from both academics and practitioners; furthermore, the optimization of energy management has become a research topic of great interest. This paper takes a solar-diesel hybrid ship with 5000 car spaces as its research object. Then, following testing on this ship, experimental data were obtained, a multi-objective optimization model related to the ship’s fuel economy and diesel generator’s efficiency was established, and a partial swarm optimization algorithm was used to solve a multi-objective problem. The results show that the optimized energy management strategy for a hybrid energy system should be tested under different electrical loads. Moreover, the hybrid system’s economy should be taken into account when the ship’s power load is high, and the output power from the new energy generation system should be increased as much as possible. Finally, the diesel generators’ efficiency should be taken into consideration when the ship’s electrical load is low, and the injection power of the new energy system should be reduced appropriately.

The new round of electricity market reform in 2015 completely changed the profit pattern of power grid enterprises (PGEs) in China, and directly affected their investment plans. Under the new electricity market reform (NEMR), the government regulatory authority made higher requirements for the investment efficiency of PGEs, and the investment effectiveness hence became the core criterion for investment plans. Therefore, the PGEs are now attaching great importance to the investment efficiency. According to their geographical differences, this paper divides the Chinese provincial PGEs into three groups, namely eastern, central and western region enterprises. Based on the NEMR, we developed an evaluation system of investment efficiency for the above-mentioned enterprises. Moreover, this paper selects GDP per capita, electricity consumption in industry, and electrification rate as external environment variables, and conducts an empirical research on the investment efficiency of 31 provincial PGEs in China in 2017. The analysis reveals that three external environment variables have considerable impacts on the investment efficiency. Though the increase of GDP per capita and electricity consumption in industry are not conducive to improving investment efficiency, the advancement of electrification plays a positive role in its improvement. And from the real efficiency results, Tianjin, Liaoning, Jiangsu, and Fujian have relatively higher investment efficiency, while Henan, Shandong, and Shanghai exhibit lower investment efficiency. By comparing the investment efficiency of PGEs in the first and third stage, conclusions can be drawn that in the first stage the investment efficiency of PGEs was overestimated, and the inefficient investments prevailed some provincial PGEs, which caused by low scale efficiency.

Energy management strategy is a key technology of hybrid power ships. In recent years, renewable energy ship technologies have become a popular research field and one promising development direction to realize reasonable utilization of energy resource, as well as energy conservation and emission reduction. Among these technologies, the solar energy hybrid ship technology is currently attracting attention all over the word. In this paper, a 5000-car space solar energy hybrid ship is used as the research objective, and an energy management strategy that is based on fuzzy logic is proposed to distribute the ship power generation, solar energy, and battery output power according to the ship’s electrical load demand, and the fuzzification and stochasticity of solar energy. By comparing the simulation results with real ship testing results, it is identified that the proposed fuzzy logic energy management strategy can optimize the operation conditions of individual power generation sources, improve the overall performance of power system, and reduce the ship’s overall fuel consumption.