Electric means of transportation have seen a rapid expansion partly due to flexibility to commuters and carbon emission reduction. However, transportation electrification is creating severe power quality problems in the utility grid. A single-phase voltage-source traction converter (VSTC) plays a vital role in high-speed train operation. However, it is partly blamed for injecting instability into the vehicle-grid coupling systems (VGCSs). Therefore, understanding the function of VSTC and complying with various grid codes and technical standards for VGCSs is essential. Furthermore, grid-connected VSTC must comply with strict safety standards, such as IEEE Std. 519 and IEEE Std. 16. However, with hundreds or thousands of literature available, it is difficult to choose an effective control method that meets all the requirements. Consequently, to illustrate a clear picture of the development of effective control strategies, this work review recent control techniques, mainly for harmonics rejection and low-frequency oscillation suppression. Factors affecting grid stability and control performance are first identified and discussed in detail. Then, effective control methods to alleviate the disturbance are elaborated. Moreover, future trends on control strategies for VSTCs considering the recent advancements of artificial intelligence are extensively discussed.

The fourth energy revolution is characterized by the incorporation of renewable energy supplies into intelligent networks. As the world is shifting towards cleaner energy sources, there is a need for efficient and reliable methods to predict the output of renewable energy plants. Hybrid machine learning modified models are emerging as a promising solution for energy generation prediction. Renewable energy generation plants, such as solar, biogas, hydropower plants, wind farms, etc. are becoming increasingly popular due to their environmental benefits. However, their output can be highly variable and dependent on weather conditions, making integrating them into the existing energy grid challenging. Smart grids with artificial intelligent systems have the potential to solve this challenge by using real-time data to optimize energy production and distribution. Although by incorporating sensors, analytics, and automation, these grids can manage energy demand and supply more efficiently, reducing carbon emissions, increase energy security, and improve access to electricity in remote areas. However, this research aims to enhance the efficiency of solar power generation systems in a smart grid context using machine learning hybrid models such as Hybrid Convolutional-Recurrence Net (HCRN), Hybrid Convolutional-LSTM Net (HCLN), and Hybrid Convolutional-GRU Net (HCGRN). For this purpose, this study considers various parameters of a solar plant such as power production (MWh), irradiance or plane of array (POA), and performance ratio (PR). The HCLN model demonstrates superior accuracy with the RMSE values of 0.012027 for MWh, 0.013734 for POA and 0.003055 for PR, along with the lowest MAE values of 0.069523 for MWh, 0.082813 for POA, and 0.042815 for PR. The obtained results suggest that the proposed machine learning models can effectively enhance the efficiency of solar power generation systems by accurately predicting the required measurements.

Modulating the traction converters produces current harmonics at the switching frequencies and their multiples. These harmonics should be minimized to meet the network specifications. The LC ‐trapped filters, tuned to these frequencies, can easily meet this requirement, but the existing applicable trap filters have not been studied with the traditional traction system topologies. Thus, this paper presents a trapped LCL filter with an LC resonator on the converter side, called a fully integrated T‐LCL filter, for the traction power supply system. The model and analysis reported in this research demonstrate that the presented filter has several advantages, which can be summarized by: reducing the size by winding many coils through magnetic integration, attenuating the switching frequency and its multiple harmonics that reduce the current total harmonic distortion, assuring durability against the filter parameters differences, and preserving system stability under transient conditions. The proposed filter can become a promising trap filter based on these advantages. Simulation models of an ac/dc single‐phase traction rectifier with the proposed filter were created and tested in MATLAB/Simulink, verifying its superiority. Finally, the filter is validated by performing hardware‐in‐the‐loop experiments.

This paper presents a design technique of magnetic integrated LLCL filters for grid‐tied inverters. With the proposed design technique, the LLCL filter's resonant frequency can be higher than the Nyquist frequency. Furthermore, the proposed concept was only reported for the LCL filter in the previous research works. In addition, the modulation process will produce dominant switching harmonics for unipolar PWM H‐bridge inverters at the double switching frequency. Thus, putting the resonant frequency beyond the Nyquist frequency will increase the stability zone. The proposed design methods maximize the filter inductors' utilization and resist the grid impedance variations under weak grid conditions, depending on the improved stability zone. Comparative simulation and HIL experimental results are presented to confirm the effectiveness of the proposed magnetic integrated LLCL filter design. The HIL experimental results and the simulation results agree well with each other.

The traction converter modulation generates switching-frequencies current harmonics. The trapped filters can eliminate these switching harmonics, reducing total inductance and filter size. Nonetheless, in comparison with the typical inductor-capacitor-inductor (LCL) filter, the trap inductor needs a larger magnetic core. Moreover, the trapped filter has not been analyzed in the traction systems. This paper proposes a magnetic integrated inductor-trap-inductor (LLCL) filter to decrease the filter’s size and investigate its application in traction converters. In fact, the application range of this filter is quite broad, and it can be used in various electrical power systems, including industrial power systems, renewable energy systems, transportation systems, and building power systems. The LC-trap may be formed by connecting the equivalent trap inductor, introduced through the magnetic coupling between inverter-side and grid-side inductors, in series with the filter capacitor. Furthermore, for H-bridge unipolar pulse width modulation (PWM) traction converters, the prominent switching harmonics are concentrated at the double switching frequencies. Therefore, the stability zone is expanded by moving the resonance above the Nyquist frequency. The presented filter’s features and design are thoroughly analyzed. The proposed method is finally validated by the MATLAB/Simulink simulation and hardware-in-the-loop (HIL) experimental results. Compared to the discrete windings, the integrated ones can save two magnetic cores. Furthermore, the proposed filter can meet IEEE criteria with 0.3% for all the harmonics and total harmonic distortion (THD) of 2.15% of the grid‐side current.

This paper introduces magnetic integrated high-order trap–trap–inductor (TTL) and inductor–trap–trap (LTT) filters featuring two LC-traps designed for grid-tied inverters, aimed at reducing the size of output-power multi-trap filters. The proposed filters exhibit excellent harmonic absorption capabilities alongside a compact design. Building on the conventional integrated inductor–capacitor–inductor (LCL) filter, the approach involves connecting a small capacitor in parallel with either the inverter-side or grid-side inductors to create an LC trap. Additionally, a second LC trap can be achieved by integrating the filter capacitor in series with the equivalent trap inductance, established by the magnetic coupling between the grid-side inductor and inverter-side one. This paper thoroughly analyzes the characteristics of the proposed filters. Moreover, a design method is presented to further minimize the size of the output filter components. Finally, validation through simulations and hardware-in-the-loop (HIL) experiments confirms the proposed approach’s effectiveness and feasibility. The integrated designs achieve a size reduction of 35.4% in comparison with the discrete windings. Moreover, these designed filters comply with IEEE standards, maintaining a grid-side current total harmonic distortion (THD) of less than 0.9%, with all current harmonics below 0.3% of the fundamental current.