This study presents a current balancing technique for high-current windings in medium-frequency transformers (MFTs), particularly relevant to solid-state transformer (SST) applications. Handling high currents on the low-voltage high-current winding of MFTs is challenging due to skin and proximity effects. Conventional techniques, such as continuously transposed conductors (CTCs) and parallel winding paths, are applicable but have limitations in medium-and high-frequency applications such as SSTs due to skin and proximity effects. To address these issues, a modular and tunable compensation method is proposed, based on adding small, series-connected inductive elements (compensation toroids) to each parallel winding path. Experimental results from a prototype validate the proposed compensation technique, highlighting its effectiveness in mitigating unbalanced current distribution. Finite element analysis (FEA) and experimental validation across a wide frequency range (1–10 kHz) confirm the effectiveness of the method. The results demonstrate a significant reduction in current imbalance with minimal added losses or system impact.

Active power oscillations (APOs) frequently arise in inverter-dominated power systems with multiple converters operating under virtual synchronous generator (VSG) control, posing risks to system stability and protection coordination. While various mitigation strategies have been proposed, many rely on prior knowledge of system parameters, offer limited damping performance, or involve complex models that lack physical interpretability—making them difficult to apply in practice. To address these challenges, this article first introduces a physically intuitive resistor-inductor-capacitor (RLC) equivalent circuit model to explain the root causes of APOs in both stand-alone (SA) and grid-connected (GC) modes. By mapping inertia, damping, and feeder impedance to capacitive, resistive, and inductive elements, respectively, the model reveals how mismatches among converters lead to interunit oscillations characterized by LC resonance. Building on this insight, we propose two mode-specific mitigation strategies: 1) in SA mode, a graph-theory-based impedance control ensures proportional reactive power sharing and effectively suppresses APOs; and 2) in GC mode, adaptive inertia and damping control with feedforward loop is designed to reshape transient power dynamics while preserving frequency stability. The proposed methods are validated through extensive simulations and real-time hardware-in-the-loop experiments, demonstrating their effectiveness in suppressing oscillations and enhancing the robustness of multiconverter power systems.

This paper presents a practical approach to reduce the size of medium-frequency, medium-voltage dry-type transformers through the innovative use of semiconductive screening. The proposed method minimizes the required air gaps, a critical aspect of dry-type transformer design, particularly for medium-frequency applications. Analytical approaches and Finite Element Method (FEM) simulations in COMSOL are used to demonstrate how to achieve a uniform electric field distribution within the transformers. Experimental investigations by means of partial discharge measurement on a prototype epoxy-based stress cone termination with a semiconductive shield are conducted. The results demonstrate the potential for this method to enhance transformer performance and provide a foundation for further advancements in medium-frequency transformer design.

In line with climate goals and ambitions, the maritime industry is undergoing a technological transformation. Hybrid vessels offer the opportunity to optimize the use of the available distributed (renewable) energy resources on the grid. Hybrid Vessel Energy Management Systems need to make decisions with objectives to reduce fuel consumption, greenhouse gas emissions and maintenance expenditures during operation of the vessel. The verification of the Energy Management System is conducted by creating a Digital Twin of the hybrid vessel on the Typhoon Hardware-In-Loop platform. The model results are achieved in real time, thereby setting the foundation for Controller HIL (C-HIL) projects.

Grid-following control (GFL) has been widely implemented as the dominant control method for inverter-based resources (IBR). However, because GFL cannot provide sufficient inertia for frequency regulation, grid-forming control (GFM) is proposed as an alternative solution. However, the impact of grid dynamics characteristics on GFL and GFM control is rarely discussed. Therefore, this paper systematically derives and compares the frequency response of GFL and GFM control, considering the grid dynamics that are emulated by a synchronous generator. The impact of the inertia of GFM is investigated by pole-zero maps.

Partially rated DC interlinking converters are recognized for their high-gain power regulation capabilities, which effectively synergize active power across DC microgrids (DCMGs). Integrating energy storage units (ESUs) to address the intermittent nature of renewables in DCMGs has become an enhanced requirement for these converters. This article proposes a partially rated multiport interlinking converter (PMIC) that incorporates a distributed ESU. The PMIC controls a floating voltage and a bidirectional shunt current on the DC line, ensuring full galvanic isolation for the ESU while operating at a low DC-link voltage. It regulates multidirectional power flow and balances power during peak and off-peak periods. A decentralized droop-based power flow control strategy is proposed for the PMIC, which distributes renewable energy generation, load consumption, and ESU utilization proportionally across the system. The control strategy includes two tailored continuously differentiable activation functions, Sigmoid and Hyperbolic Tangent, to facilitate autonomous global power-sharing and seamless ESU engagement. Simulation and experimental case studies confirm the PMIC's capability to smooth renewable energy fluctuations and enhance the power and voltage profiles of DCMGs.

The development of lithium-ion batteries has experienced massive progress in recent years. Battery aging models are employed in advanced battery management systems (BMSs) to optimize the use of the battery and prolong its lifetime. However, Li-ion battery cells often experience fluctuations in battery capacity and performance during cycling, which makes capacity prediction more difficult. Moreover, the reason for the capacity regeneration phenomenon occurring after resting periods is not clear yet, as well as the influence of cycling conditions on capacity regeneration. A relationship between this phenomenon to cycling state of charge (SoC) ranges and current rates was investigated in this article on a battery cell with lithium nickel manganese cobalt (NMC) oxide positive electrode. Experimental results show that the capacity increase is a consequence of decreased internal impedance after the resting period. The experiments also showed that a significant power drop and subsequent power regeneration after a resting period occurs only for specific SoC ranges, and applying a resting period after battery cycling can mitigate this power fading process. The semi-empirical model of battery degradation including capacity regeneration is proposed in this article based on physical processes inside of the cell retaining low computational requirements. The acquired results can be utilized in BMSs for more accurate state of health (SoH) estimation and to prolong battery lifetime.

Active power oscillation (APO) issues may arise during the deployment of multiple parallel converters with Virtual Synchronous Generator (VSG) control in Microgrids. To that end, the equivalent circuit models of a converter with VSG control are proposed, which intuitively reveals the root cause of APOs. Accordingly, a graph-theory-based virtual impedance is introduced to harmonize parameters among involved VSGs, effectively eliminating APOs. Simulation and experimental results verify the improvements of the proposed control.

Distributed secondary control achieves voltage restoration and power sharing through communication among adjacent units but exposes the microgrid to potential cyber-attacks. Traditional mitigation strategies modify the secondary controller after the attack, addressing the issue only postoccurrence. Furthermore, in microgrid planning, the structure of the communication network significantly influences the resilience to attacks, but it remains to be explored. This article presents a proactive defense mechanism by designing a resilient communication network. The proposed method quantifies the impact of attacks and develops a multiobjective optimization algorithm to design the network, considering quantified attacks, convergence, time-delay robustness, and communication costs. The method is validated through OPAL-RT simulations of an islanded microgrid with ten converters.

Accurate battery capacity estimation is essential for the effective and reliable operation of lithium-ion battery management systems. Battery impedance is a key parameter that encapsulates electrochemical information, closely correlating with the internal states of batteries. This study proposes a novel capacity estimation framework that effectively balances accuracy, efficiency, and practicality. Firstly, a novel feature extraction method is introduced to extract health features from the imaginary impedance at a single frequency. The extracted feature demonstrates a strong and stable correlation with battery degradation under various operation conditions, while significantly reducing data requirements. To address the impact of diverse degradation patterns on estimation accuracy, an initial adjustment method is applied to precisely retrace the relative degradation paths of batteries. The results show that the mean absolute percentage error of battery capacity estimation decreases from 15.65% to 2.87%. Additionally, a transformer-based capacity estimation model is developed, which integrates a feature fusion unit to explicitly eliminate the influence of temperature on model performance. As a result, the model's accuracy improves by over 28% under various thermal conditions.

Consensus algorithm-based secondary control, such as virtual impedance, is typically used to achieve power-sharing and ensure stable operation in microgrids. The introduction of communication, however, increases the system's vulnerability. Communication failure, e.g., under cyber attack or disruption, can lead to a huge loss. To solve this, this article proposes a signal reconstruction approach for the miscommunicated signals. The power-sharing convergence, both in normal conditions and under communication failure, is analyzed via the Lyapunov method. The feasibility and effectiveness of the proposed approach are validated on a lab-scale microgrid.

Highly self-sufficient energy hubs offer a promising solution to mitigate grid congestion in favor of grid operators and to reduce grid fees for the benefit of energy hub operators. Meanwhile, the energy hub's capacity may far exceed the grid connection capacity, creating a weak grid situation. As a result, power quality issues such as voltage fluctuations, frequency deviations, and even instability may occur. In this work, a grid-forming energy storage system (GFM-ESS) is integrated to address these potential problems. A model of the GFM-ESS and energy hub is established based on a 50 kW PV-Hydrogen energy hub demonstrator, where PV-generated power is utilized for green hydrogen production. A trade-off design is proposed to identify the optimal balance between the capacity of the GFM-ESS and the grid connection. The voltage and frequency response at the hub's bus are analyzed to evaluate this trade-off. While experiments with the 50 kW demonstrator are ongoing, simulation results are provided to validate the effectiveness of the proposed design.

A fast and efficient charging infrastructure has become indispensable in the evolving energy landscape and thriving electric vehicle (EV) market. Irrespective of the charging stations’ internal alternating current (AC) or direct current (DC) bus configurations, the main concern is the exponential growth in charging demands, resulting in network congestion issues. In the context of exponential EV growth and the provision of charging facilities from low-voltage distribution networks, the distribution network may require frequent upgrades to meet the rising charging demands. To avoid network congestion problems and minimize operational expenses (OE) by integrating energy storage systems (ESS) into ultra-fast charging stations (UFCS). This paper presents a techno-economic analysis of a UFCS equipped with a battery ESS (BESS). To reduce reliance on the electric grid and minimize OE, a dual-objective optimization problem is formulated and solved via grid search and dual-simplex algorithms. Analytical energy and physical BESS models are employed to evaluate the optimization matrices. The intricacies of BESS aging are examined to ensure an optimal BESS size with a more extensive lifespan than the corresponding payback period. The integrated BESS significantly reduced reliance on the grid to tackle network congestion while fulfilling charging demands. The dynamic pricing (DP) structure has proven more favorable, as the average per unit cost remains lower than the static tariff (ST). Results illustrate that integrating BESS reduces the OE and peak-to-average ratio (PAR) by 5-to-49% and 16-to-73%, respectively. Moreover, the combination of 70% BESS and 30% grid capacities outperforms the other configurations with a 73% reduction in PAR and a 49% reduction in OE before BESS reaches the end-of-life.

The global race toward decarbonization has reached a transformative inflection point as electrification surges across the transportation sector in most of the world. No longer confined to passenger vehicles, electric mobility now spans trucks, ships, and even aircraft, driven by a confluence of environmental mandates, policy momentum, and technological innovation. Nowhere is this shift more pronounced than in Europe, where the Trans-European Transport Network (TEN-T) envisions a seamlessly connected, zero-emissions infrastructure backbone by the midpoint of this century (Figure 1). At the heart of this revolution lies a new breed of ultrafast-charging technologies, electrified highways, and maritime ports—each pushing the limits of energy delivery, grid integration, and power electronics. Yet, as the charging power scales from kilowatts to multimegawatts, and as electric mobility moves from concept to logistics-critical reality, the challenges to the power grid—especially at the distribution level—are becoming clearly visible. This article explores the emerging architectures and innovations required to enable this new era of electric transport, from the Megawatt Charging System (MCS) to medium-voltage (MV) grid integration with solid-state transformers (SSTs) and grid-forming (GFM) battery energy storage systems (BESSs) as key components.

Balancing converters play a pivotal role in bipolar dc grids, and while numerous topologies have been explored, many suffer from drawbacks, such as reliance on bulky passive components, limited soft-switching capabilities, or complex control mechanisms. This article introduces an LC series-resonant balancing converter topology that addresses these issues, featuring smaller passive components, the ability to achieve soft switching across its entire operational range, and simplified control with proper design. By operating in the capacitive region, the converter ensures soft switching for the complete load range, enabling all switches to achieve zero voltage switching (ZVS) turn on. The study reveals that the converter's power flow depends on both the switching frequency (fsw) and the phase shift angle (φ), but notably, when the resonant inductor value is kept sufficiently low, fsw and φ become decoupled, simplifying power flow control. In addition, this article provides detailed design guidelines for the converter's resonant tank and validates the operation and control of the converter through an experimental setup.

This article discusses the various operating modes of a series resonant balancing converter for bipolar dc grids. It is shown that the converter can be operated in both the capacitive and inductive regions with respect to the resonant frequency of the LC tank. Furthermore, concerning the pulse width modulation signals to the switches, the converter can either be operated by controlling the phase shift between the converter half bridge legs or the duty cycle of the half bridges. A qualitative comparison of the different modes proves that a) the phase shift modes have better soft switching capabilities, b) the capacitive phase shift mode can show zero voltage switching at switch turn-on in the whole operating range, c) the losses in case of capacitive phase shift mode shows best performance at low load power, d) the inductive region power modes show lower rms current for the same power flow compared with capacitive region modes which lead to lower losses at higher output power. The simulation and experimental results depict the operation of all the modes. Finally, a prototype is designed to validate all operating modes, demonstrating $>$99% system efficiency at 1.75 kW.

Insulated Gate Bipolar Transistor (IGBT) is the core component of current converter equipment in application scenarios such as flexible DC transmission and flexible AC transmission, and its junction temperature increases significantly with the increase of current level. Therefore, the junction temperature control of IGBT devices has become one of the bottlenecks to further increase the transmission capacity. Al/Diamond material has a much higher thermal conductivity than traditional packaging materials and a smaller coefficient of thermal expansion, so applying Al/Diamond material to IGBT packaging may improve the heat dissipation ability of IGBT and thus reduce the junction temperature. This paper constructs the IGBT model based on Al/Diamond material and the IGBT model based on traditional copper material through COMSOL simulation software, and compares the internal electro-thermal-stress distribution of the two models. In addition, this paper calculates the maximum and average values of temperature, maximum and average values of thermal stress and other parameters of each component inside the model according to the simulation data set. After comparison, it can comprehensively reflect the greater enhancement of heat dissipation capability of IGBT after applying Al/Diamond material to its encapsulation, which provides guidance for the subsequent research on the encapsulation optimization mechanism of high-power IGBT devices based on Al/Diamond material and the actual device fabrication.

The State of Health (SOH) is a crucial component of battery management systems (BMSs), offering important health information and protection against unsafe usage. In this paper, an accurate model for SOH estimation of Li-ion batteries was developed, which is uniquely characterized by using only the imaginary part of impedance at a specific frequency for precise SOH estimation. Through the identification of the relationship between impedance at a specific frequency and capacity degradation using correlation coefficients, the feature data most closely related to battery aging was selected. Next, the battery aging modeling and SOH estimation were validated on nine batteries across three different temperatures using a Feed-forward Neural Network (FNN). The validation results indicated that the proposed method has a high estimation accuracy, achieving a Mean Absolute Percentage Error (MAPE) of merely 2.05% throughout the entire lifecycle of the battery 45C02 during tests at a temperature of 45°C.

This paper concerns the control problem of the active and harmonic power sharing caused by the mismatched impedance in resistive feeders-dominated microgrids. A distributed model predictive control (DMPC) scheme is suggested to regulate the virtual impedance of each involved unit for power sharing based on the neighbor's state. With the distributed philosophy, the central controller is not required. Moreover, the proposed method benefits resilience to communication failure by designing the communication matrix. Furthermore, it involves propagating information among units in a short period, significantly reducing the communication and computation burden. Finally, the performance of the proposed control scheme is evaluated in terms of its convergence, robustness to communication delay and load variations, resilience to communication failure, and plug-and-play functionality without communication in an inverter-connected system.

In the production of green hydrogen, electrolyzers draw power from renewable energy sources. In this paper, the design of Solid State Transformer (SST) for large-scale H ₂ electrolyzers is benchmarked. The three most promising topologies are chosen for design and comparison, including Modular Multi-level Converter (MMC) based SST, Modular Multi-level Resonant (MMR) based SST, and Input-Series-Output-Parallel (ISOP) based SST. The distance between converter towers for insulation and maintenance, the insulation system of the transformer, and the cooling system are designed with practical considerations in order to have an accurate estimation of the volume and weight of the SST. Losses in the switches are calculated based on equations, and losses in passive components are calculated based on FEM simulation. The operating frequency for each topology is optimized to minimize loss, weight, and volume. The best of each topology is then compared with each other to identify the most suitable one for large-scale H ₂ electrolyzers.