To reduce the allocation of energy storage capacity in wind farms and improve economic benefits, this study is focused on the virtual synchronous generator (synchronverter) technology. A system accompanied by wind power, energy storage, a synchronous generator and load is presented in detail. A brief description of the virtual synchronous generator control strategy is given. The capacity allocation is based on different optimization goals and the optimal energy storage capacity configuration of the coordinated frequency modulation (FM) control strategy. The detail of the dual-loop control strategy is carried out by establishing the grid-connected transfer function model of the synchronverter energy storage and a theoretical model of life cycle cost is established. The optimal control strategy of coordinated FM for wind storage is implemented using MATLAB software. The simulation showed that the proposed strategy provided the energy storage capacity at high wind speed, which is configured to be 5.9% of the installed capacity of the wind turbine, marking a reduction of 26% compared with the 8% capacity required for independent support. In addition, the proposed method has improved the energy storage capacity configuration of the coordinated FM control strategy.

The energy flow is step-by-step among Lithium-ion-battery when an equalizer based on the buck-boost converter is adopted, resulting in a long energy transmission path and low equalization efficiency. First, a Lithium-ion-battery equalizer based on the dual active half-bridge is studied in this paper. Second, the key parameters of the energy flow between cells in the same group and cells in different groups in the equalizer are analyzed. Third, a phase shift control strategy is put forward according to the analysis results. The equalizer with the proposed control strategy not only can realize the energy flow between cells in the same group and different groups but also work at high frequency. Therefore, the transformer can be designed to be small in size and light in weight, greatly reducing the volume and weight of the equalizer. A prototype of the dual active half-bridge equalizer with four lithium batteries was managed. The experimental results show that the proposed Lithium-ion-battery equalizer based on phase shift control has good equalization performances.

This study introduces a sophisticated methodology that integrates 3D assessment technology for the reorganization and recycling of retired lithium-ion battery packs, aiming to mitigate environmental challenges and enhance sustainability in the electric vehicle sector. By deploying a kernel extreme learning machine (KELM), variational mode decomposition (VMD), and an advanced sparrow search algorithm (SSA), the research achieves a marked increase in the precision of battery classification and performance forecasting. Implementing a three-dimensional dynamic evaluation model, the study optimizes battery pack grouping strategies, culminating in superior secondary utilization rates, extended operational lifespans, and minimized ecological footprints. The research demonstrates that balanced weight distribution strategies, which maximize energy density to 61.37571 Wh/L and cycle counts up to 947 cycles, are pivotal for the efficient reorganization of battery packs, substantiating the economic feasibility and environmental sustainability of recycling initiatives. Future endeavors will extend this research to investigate the influence of diverse battery materials and morphologies on reorganization efficacy, with the aim of broadening the application horizons to include real-world scenarios, thereby refining battery performance and lifespan predictions and propelling forward the frontiers of recycling technology and policy development.

This study presents an innovative dual closed-loop DC control system for intelligent electric vehicle (EV) charging infrastructure, designed to address the challenges of high power factor, low harmonic pollution, and high efficiency in EV charging applications. The research implements a three-level Pulse Width Modulation (PWM) rectifier with a diode-clamped topology and Insulated-Gate Bipolar Transistors (IGBTs), achieving a power factor of 0.99, a total harmonic distortion (THD) of 1.12%, and an efficiency of 95% through rigorous simulation. These results surpass those of wireless charging technology and bidirectional DC–DC converters, demonstrating the system’s superiority in key performance metrics. The dual closed-loop strategy, integrating a current inner loop and a voltage outer loop, ensures rapid response and high steady-state accuracy, with the PI regulator effectively managing phase coupling for balanced power flow. The voltage outer loop’s stability is critical for the system’s reliable operation. The study also discusses the challenges in the dynamic variation of midpoint source current and proposes future work to increase the system’s switching frequency, improve anti-interference capabilities, and enhance the accuracy of the sampling process. Advanced computational intelligence and optimization techniques are highlighted as essential for tackling the complex challenges of modern EV charging systems. The study contributes to the development of efficient, secure technology for the next generation of wireless networks and power systems, providing a robust empirical basis for the proposed control strategies through MATLAB/Simulink simulations. This research sets a solid foundation for the performance assessment of EV charging systems, offering high-performance, environmentally friendly, and economically viable solutions for sustainable transportation.