Many DC energy solutions have emerged as potential candidates to enhance the electrical infrastructure in a localized approach, allowing future expansion in the transportation sector despite the congestion of the utility grid. However, the risk of designing large power converter units as controllable substations in complex networks, such as electric railway systems, has encouraged the sophistication of modeling and testing tools. This paper presents a high-fidelity, real-time model implementation of a controllable substation for DC traction power systems. This representative model is developed to facilitate the testing of different upgrading options to understand and quantify how these changes will affect the system and, more importantly, which features are critical to further increasing the sustainability of the railways. This is applied to a case study of the Dutch railway system in Wierden. It is found that while controllable substations can reduce voltage drops from an average of 400 V to only about 230 V, the benefit they bring in regenerative braking harvesting does not outweigh the investment costs, calling for further investigation of energy storage systems as another potential solution.

The multilevel dual-active-bridge (ML-DAB) converter offers enhanced performance and power density operation compared with conventional DAB counterparts. This article introduces a GaN-FET-based T-type DAB converter interface, designed to enable transition between full power conversion (FPC) and partial power conversion (PPC) modes. The proposed converter generates five voltage levels on both the primary and secondary sides of the high-frequency transformer (HFT), reducing voltage transitions (dvdt) and increasing the high power efficiency range. The main contribution of the proposed converter lies in the integration of an ML-DAB architecture with the capability to operate in PPC reconfiguration, enabling the processing of only a fraction of the total power with enhanced thermal performance. Output voltage regulation is achieved by a single-phase shift (SPS) between the primary and secondary sides, simplifying control and enhancing overall performance. Simulation and experimental tests under a scaled-down prototype to verify the proposed modulation method and control scheme implementation are performed.

DC energy hubs have emerged as suitable candidates to enhance the electrical infrastructure in a localized approach, allowing future expansion in the transportation sector despite the electricity grid congestion. However, a risk in designing such a hub is that the outcome of the optimization can be a mere consequence of the (lack of) sophistication of its generation and load models. In that aim, this paper presents a sensitivity analysis for a power demand profile for a DC railway traction power substation, taking into account traction power parameters and the heating, ventilation, and air conditioning (HVAC) modeling approaches. It is found that the traction parameters such as total mass can be confidently considered using an averaged value. On the other hand, modeling the HVAC system using an averaged power demand can lead to errors over 6%, especially in the recovered braking energy calculations.

In recent years, the electric vehicle (EV) industry has experienced significant advancements, simultaneously driving substantial progress in battery technology. The evolution of battery systems necessitates enhancements in charging infrastructure to attain elevated power levels during the charging process, thereby minimizing charging time. Various algorithms have been developed for driving battery charging; however, these algorithms necessitate the creation of diverse controllers to generate precise trigger signals for the semiconductors within the various power converters utilized in charging stations. This work presents the design of an innovative model-free control system for Type I impedance network Partial Power Converter (PPC) in which a Deep Reinforcement Learning (DRL) agent generates control signals during the different charging stages. Particularly, a Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm is used to substitute the inner control loop of traditional control systems. To this end, different agents were designed, trained, and tested inside a built simulation environment. It is worth noting that TD3-based control allows for the optimal functionality of a type I impedance network PPC within the context of EV battery charging applications, according to the specified CC-CV charging algorithm. Empirical results revealed that the battery system reached an 80% state of charge in under 8 minutes starting from an initial 20%.

Battery Energy Storage Systems (BESS) offer scalable energy storage solutions, especially valuable for remote, off-grid applications. However, traditional battery packs with fixed series-parallel configurations lack reconfigurability and are limited by the weakest cell, hindering their application for second-life batteries. The Modular Multilevel Series-Parallel Converter (MMSPC) addresses these limitations by enabling dynamic reconfiguration, optimizing cell balancing, and enhancing energy control. This paper experimentally evaluates a single-phase BESS based on the MMSPC with an output power equivalent to 2 kW and two battery units (155V), demonstrating stable output and reduced internal losses across varied battery parameters.

This work introduces a reconfigurable topology for AC-link partial power converters (PPC), intended for use as high-frequency transformerless regulated DC-DC converters in fast charging stations for electric vehicles (EV). This new topology allows an AC-link PPC to be reconfigured so that it works as a type I PPC during boost mode and as a type II PPC during buck mode. The converter is able to operate across a wide output voltage range, making it compatible with the different battery voltage configurations found in the electric vehicle industry. The converter is reconfigured using four additional switches. Depending on the operating mode, these switches can be turned on or off to achieve the desired topology. In a type I PPC configuration, the input is connected in parallel, and the output is connected in series with the battery. In a type II configuration, the input is connected in series, and the output is connected in parallel with the battery. This paper presents an analysis of converter operations and control for EV charging systems operating at 400 V and 800 V, incorporating both operation validation and efficiency metrics derived from simulations.

Hybrid Energy Storage Systems (HESSs) have gathered considerable interest due to their potential to achieve high energy and power density by integrating different storage technologies, such as batteries and capacitors, to name a few. Among the various topologies explored for HESSs, the multi-output multilevel converter stands out as a promising option, offering decoupled operation of the AC ports while maintaining an internal balance among the diverse storage units. In this paper, the operation and restrictions of a HESS based on a multi-output multilevel converter with a carrier-based modulation scheme are presented. The study provides compelling evidence of the correct operation of the proposed modulation scheme and highlights its advantages, including simplicity and stability.

Energy storage systems (ESSs) allow improving the stability and efficiency of the electrical grids with a high penetration of renewable energy sources. Moreover, the use of Hybrid ESSs (HESSs) enables storage solutions with both high-energy and high-power densities, by combining different storage technologies such as diverse battery chemistries, ultracapacitors, or hydrogen fuel cells to name a few. In this article, an HESS-based multioutput multilevel (MOM) converter is presented. The proposed topology enables decoupled control of each ac converter voltage output. The internal switching states further allow the use of different storage units and high-quality multilevel voltage in each ac output. The mathematical model of the proposed topology and the defined operation region of the system, besides a model-predictive control strategy, are developed. Finally, simulation and experimental results validate the performance of the proposed topology.

DC microgrids initiated the change of a paradigm regarding the concept about electrical distribution networks, especially in the context of the distributed generation associated with renewable energies. However, this new reality opens a new area of research, in which several aspects must be carefully studied. Indeed, the bipolar design is one of the principal dc microgrid configurations considering its characteristic wiring. Although holding many promising advantages, the bipolar dc microgrid has a tendency toward voltage and current imbalances due to the unequal distribution of the loads and generators between the two poles. Thus, specific power electronic-based solutions are required to ensure the balance of these dc microgrids. Within this frame, this article gives a comprehensive review of the multiple architectures and power electronic topologies proposed to mitigate/eliminate this undesired condition. The following provides an insightful classification and discussion with the pros and cons of these solutions. This work can serve as a timely review for researcher/engineers who want to enter the voltage balancing field in the bipolar dc grids and promote the innovation of their power electronics-enabled solutions.

Electric vehicle (EV) charging infrastructure will play a critical role in decarbonization during the next decades, energizing a large share of the transportation sector. This will further increase the enabling role of power electronics converters as an energy transition technology in the widespread adoption of clean energy sources and their efficient use. However, this deep transformation comes with challenges, some of which are already unfolding, such as the slow deployment of charging infrastructure and competing charging standards, and others that will have a long-term impact if not addressed timely, such as the reliability of power converters and power system stability due to loss of system inertia, just to name a few. Nevertheless, the inherent transition toward power systems with higher penetration of power electronics and batteries, together with a layer of communications and information technologies, will also bring opportunities for more flexible and intelligent grid integration and services, which could increase the share of renewable energy in the power grid. This work provides an overview of the existing charging infrastructure ecosystem, covering the different charging technologies for different EV classes, their structure, and configurations, including how they can impact the grid in the future.

This paper proposes a new buck-boost flying-capacitor (FC) converter for the DC-DC stage of an Electric Vehicle (EV) fast charging station. The proposed converter is capable of delivering a wide output range of voltage to charge different battery configurations. The converter has two modes of operation, buck and boost. Thanks to this feature, the proposed converter allows higher efficiency and a wide operating range. The proposed converter is capable of supplying a voltage range from 200 V to 1000 V at its output, which shows the feasibility of occupying the converter inside a charging station that allows charging 400 V and 800 V battery systems. The average efficiency reported is over 97%. It is concluded that the proposed buck-boost FC converter is suitable for modern wide-output EV fast charging applications.