This article proposed an underwater simultaneous wireless power transfer and data transfer system for the autonomous underwater vehicle. The double-sided LLCC compensation topology is proposed to effectively suppress the interference to the data channel at switching instant. With the increase of the size and turns of the coupling coils, the self-resonance frequency gradually decreases. However, the frequency of data carriers is usually much lower than the self-resonant frequency, which will reduce the data rate or improve the bit error rate at a high data rate. Moreover, the high voltage generated by coupling coils causes high voltage stress on the data channel. To deal with these two issues, the last turn of each coupling coil is used to transfer data in the proposed system. The two transceivers are, respectively, connected with the last turn of the two coupling coils, which excites the entire coils to self-resonate and generates two resonant frequencies. The two resonant frequencies are utilized to realize high-speed full-duplex communication. And the voltage stress of the data channel is effectively reduced. A 518-W full-duplex prototype is built, and the maximum data rate is 700 kb/s, which verifies the feasibility of the proposed system.

This article investigates the fully distributed resilient practical leader–follower bipartite output consensus (LFBOC) problem for heterogeneous linear multiagent systems (MASs) with denial-of-service (DoS) attacks and actuator faults. To estimate the leader matrix and state in the presence of DoS attacks, two novel adaptive event-triggered observers are proposed based on newly developed lemmas, and then the adaptive event-triggered fault-tolerant controller without chattering behavior is developed to solve the LFBOC problem. Different from most existing resilient practical LFBOC working with DoS attacks and actuator faults, our method does not rely on any global information, event-triggered communication between neighbors and discrete update controllers are implemented simultaneously. Finally, an example is presented to well illustrate the effectiveness of developed method.

This article proposes a kind of cubic-magnetic coupler (CMC) for inductive power transfer (IPT) system, which has huge application potential in the charging field of moving targets. The CMC can still maintain sufficient coupling coefficient when used for long-distance wireless power transfer, it also has great capability of misalignment tolerance. Distance-to-diameter ratio (DDR) is defined to eliminate the impact of coil size and make the comparison between different couplers fairer and easier. This article optimizes the parameters and shape of the CMC. Then, the proposed coupler is compared with several existing couplers employed in long-distance IPT systems. Double-sided LCC compensation topology is chosen to limit the current flowing through the coupling coils. A CMC with an outer size of 180×180×180 mm ³ was made, based on which an IPT prototype was built. The superiorities of the proposed coupler were verified by a series of experiments. When the DDR equals 3, the coupling coefficient of the CMC is 0.00985, and the maximum dc–dc and ac–ac efficiencies are 64.9% and 72.8%, respectively.

In this article, a 2.5m five-stage inductive power transfer (IPT) system based on domino cylindrical solenoid coupler (CSC) compensated, respectively, in layers is proposed. The system is considered to be used as 220 kV post insulators application, transferring power for sensors and measuring instruments of smart grids. The distributed series compensation method is applied to double-layer CSC. Compared with the two types of parallel schemes, this method can significantly reduce the current of the main circuit. Compared with the concentrated series compensation method, this method can effectively reduce the resistance caused by the stray capacitance. The interaction between the post insulator and the magnetic coupling structure is analyzed. The circuit model of the system with constant voltage output characteristics is analyzed. A prototype with a maximum efficiency of 66.7% is built. When the power is transferred to a larger value of 77.8W, the efficiency can still reach 62%. Comparing with previous works, the wireless distance is extended while the efficiency is improved.

A three-stage-five-coil inductive power transfer (IPT) system which is based on cylindrical solenoid coupler (CSC) is proposed in this article. The shape and parameters of the CSC are optimized. The five litz coils compensated by series capacitors are considered to form an IPT system based on equivalent CLC/S/CLC compensation topology with constant voltage characteristics. The mutual inductance between compensation auxiliary coil (CAC) and power transfer coil could be changed by moving the position of CAC, and the freedom of parameter design is enhanced. Mathematical model and loss model of the system are established, and power transfer characteristics of the system are analyzed. The system is considered to be used as a power source for state detection equipment of high-voltage (HV) device to achieve long-distance IPT, the effect of the coupler on the HV electric field is verified. Finally, a prototype with a length of 1.54 m was built. Based on the platform, output voltage and dc–dc power transfer efficiency curves with changed input voltage and load are obtained. The maximum efficiency of the dc–dc system can reach about 60%.

Sustainability can achieve a balance among economic prosperity, social equity, and environmental protection to ensure the sustainable development and happiness of current and future generations; photovoltaic (PV) power, as a clean, renewable energy, is closely related to sustainability providing a reliable energy supply for sustainable development. To solve the problem with the difficulty of PV power forecasting due to its strong intermittency and volatility, which is influenced by complex and ever-changing natural environmental factors, this paper proposes a PV power forecasting method based on eXtreme gradient boosting (XGBoost)–sequential forward selection (SFS) and a double nested stacking (DNS) ensemble model to improve the stability and accuracy of forecasts. First, this paper analyzes a variety of relevant features affecting PV power forecasting and the correlation between these features and then constructs two features: global horizontal irradiance (GHI) and similar day power. Next, a total of 16 types of PV feature data, such as temperature, azimuth, ground pressure, and PV power data, are preprocessed and the optimal combination of features is selected by establishing an XGBoost–SFS to build a multidimensional climate feature dataset. Then, this paper proposes a DNS ensemble model to improve the stacking forecasting model. Based on the gradient boosting decision tree (GBDT), XGBoost, and support vector regression (SVR), a base stacking ensemble model is set, and a new stacking ensemble model is constructed again with the metamodel of the already constructed stacking ensemble model in order to make the model more robust and reliable. Finally, PV power station data from 2019 are used as an example for validation, and the results show that the forecasting method proposed in this paper can effectively integrate multiple environmental factors affecting PV power forecasting and better model the nonlinear relationships between PV power forecasting and relevant features. This is more applicable in the case of complex and variable environmental climates that have higher forecasting accuracy requirements.