High-frequency resonances in cable-transformer systems can result in excessive overvoltages, increasing the probability of insulation failure for critical components such as power transformers. These resonances occur due to the interaction between the cable and transformer and are influenced by the cable’s characteristics, including the length and wave propagation velocity. In addition, the terminating impedances of the cable’s core and sheath conductors affect the resonance characteristic of the cable as well. Applying single-point sheath grounding to the high-voltage cable connecting the switchgear to the power transformer is conventional. This paper demonstrates that the cable-transformer resonances and resulting overvoltages can vary significantly depending on the end at which the sheath conductors are grounded. An in-depth investigation of such effects is carried out through rigorous mathematical analysis, followed by experimental validation and simulations in an electromagnetic transient (EMT)-based software using models that properly represent the equipment behaviors in a wide-frequency range. The results indicate that sheath conductor grounding configuration can profoundly affect the system response, influencing the severity of transient overvoltages caused by cable-transformer resonances.

As power-electronic (PE)-based systems become increasingly common in the electric power grid, the insulation systems used in medium- and high-voltage (HV) applications will be exposed to high-frequency (HF) electric fields. Therefore, the insulation materials must be characterised using HF waveforms. However, generating these waveforms presents a significant challenge due to the large reactive power associated with the d (Formula presented.) /d (Formula presented.). This paper proposes a resonant test system with a ferrite-based transformer for HF insulation testing. The resonant circuit is formed by the transformer's leakage inductance and the insulation sample capacitance, with an adjustable frequency tuning capacitor. The system can be driven with an inverter or linear power amplifier. Increasing the test voltage level while maintaining the same test frequency presents several challenges: transformer core grounding, high resonant current and implications for bobbin and insulation design. This paper investigates these challenges and proposes an oil-insulated resonant transformer, capable of extending the test voltage to 23 kV_pk for HF insulation tests at around 40 kHz. High-frequency breakdown tests are performed on enamelled copper wire in various insulation media using the prototype resonant test system, highlighting the importance of the dielectric's thermal performance.

Capacitance plays a crucial role in high dv/dt situations, making the accurate estimation of parasitic capacitance essential. This paper introduces an improved method of moments (MoM) for calculating the capacitance of round conductors, with or without insulation layers. The proposed method combines MoM with an analytical solution based on Laplace's equation. Compared to the original MoM, the proposed method does not require consideration of polarization charges on the surface of the insulation layer, which reduces the matrix size. Additionally, the proposed method can provide asymptotic formulas for capacitance calculation. The proposed method is compared with the 2D finite-element method (FEM), MoM and measurements. The results demonstrate that the proposed method aligns well with both the FEM simulations and the actual measurements. The proposed method uses less than half the time to calculate the same cases compared to the original MoM.

The PEA(pulsed electro-acoustic) method is widely used for measuring space charge distribution in insulation materials. However, the measured quantity reflects a voltage curve over time rather than the actual space charge distribution. Therefore, establishing a calibration procedure is crucial to determine the relationship between these two quantities. This calibration procedure aims to convert the measured voltage into the spatial distribution of space charge while correcting for non-idealities such as distortion and attenuation. This paper outlines the main steps of the PEA system calibration and provides a detailed discussion on the selection of the reference signal. Furthermore, recommendations are provided to enhance the accuracy and reliability of the calibration process.

Polyether ether ketone (PEEK), polytetrafluoroethylene (PTFE), and polyimide (PI) are widely used in aerospace due to their excellent properties. Understanding their aging behavior is essential for long-term performance in extreme environments. This study examines the effects of thermal oxidative aging (at 250°C over varying periods) under humid conditions on their chemical, structural, thermal, mechanical, and dielectric properties. In PEEK, aging led to solidification and crosslinking phenomenon which resulted in increased tensile strength and storage modulus, while elongation at break and tan δ decreased. Dielectric permittivity, polarization charge density, and leakage current also declined with aging, while AC breakdown strength increased by 1.6% in PEEK. PTFE exhibited surface oxidation, thermal degradation, and a decrease in storage modulus, with an increase in loss tangent. Breakdown strength slightly decreased, while dielectric loss and leakage current increased over aging time. PI underwent severe mechanical degradation, with tensile strength reduced by 54% and elongation by 16%, along with oxidation-induced discoloration. Low-mass polar molecules generated in PI during thermal degradation which contributed to the deterioration of its dielectric properties, lead to increased permittivity, polarization, leakage current, and a lower breakdown strength observed after aging. These findings provide insights into degradation mechanisms, aiding aerospace material selection for extreme environments.

As the voltage levels of solid-state transformers (SSTs) increase using medium-voltage switches, high-frequency transformers (HFTs) used inside SSTs are subjected to increased electrical stress. This stress, characterized by high voltage, high-frequency pulsewidth modulation (PWM) voltage, can cause insulation partial discharge (PD) and potentially lead to failure of the HFT insulation system. While PD behavior under power-frequency sinusoidal voltage has been extensively studied, the behavior of HFT insulation under PWM square pulse conditions is less well understood. To address this gap, a high voltage high-frequency PWM voltage PD test platform is developed and high-frequency current transformer (HFCT) and ultra-high-frequency (UHF) antenna are used for PD signal detection. PD tests are performed under a variety of PWM conditions including PWM frequency, rise time, voltage amplitude, and different insulation layers to thoroughly investigate the HFT insulation behavior. The PD characteristics of repetitive PD inception voltage and phase-resolved PD patterns at different PWM conditions are recorded and analyzed under PWM conditions. In addition, this article explores the underlying PD mechanisms of the HFT insulation under high-frequency PWM stress, providing insights to explain the observed test results. The findings from this research provide essential references and lay a solid foundation for future advances in optimal design, health monitoring, reliability analysis, and lifetime prediction for HFTs in power electronics applications.

Integrating renewable energy resources such as wind farms is an increasingly prominent trend for future power grids. However, the wind generator tower is consistently at risk of lightning strikes, putting the wind farms’ transformer at risk of damage by lightning transients traveling through the system. Various harmonic contents of the lightning transient can excite the transformer’s resonance frequencies, resulting in both terminal and internal overvoltages (OVs). To effectively safeguard transformers against resonance OVs, it is imperative to first identify the resonance points of the transformer. Following this, a protective method must be implemented to mitigate harmonic content magnitudes that contribute to resonance. This paper introduces a series-protection device comprising an air core reactor and suppressor resistance designed to protect the transformer. The research aims to provide solutions to safeguard wind farm transformers from both terminal and internal resonance OVs caused by lightning transients. The effectiveness of the protection device is assessed through analysis, simulation, and experiments conducted in a high-voltage laboratory setup.

Large-scale integration of renewable energy sources (RESs) presents significant challenges for modern power grids, particularly with wind farms playing a crucial role in energy generation. However, frequent switching operations during the (dis)connection of wind farms and lightning strikes on wind turbines can induce severe transient overvoltages. These fast transients (FTs) pose a serious risk to wind farm substations, potentially compromising the reliability of renewable energy generation. In particular, protecting wind farm transformers from FTs, resonances, and resulting overvoltages is essential for ensuring stable operation. This paper proposes a modular series transient suppressor (MSTS) designed to enhance the protection of wind farm transformers against FTs, thereby improving system reliability. The MSTS consists of multiple resonant circuit modules, including a core, a low-voltage capacitor, and a resistor connected in series with the transformer. Its operational behavior is analyzed using analytical methods and validated through simulation studies. Furthermore, experimental testing performed on a developed MSTS prototype confirms its effectiveness in mitigating transient overvoltages for a wind farm transformer model circuit at a 60 kV transient voltage level.

This paper presents the design and optimization of a Medium Frequency Transformer (MFT) for use in Solid State Transformer (SST) systems supporting green hydrogen production. Operating at 1 kHz and integrated within an LLC resonant converter, the transformer is optimized for minimal weight and high efficiency while ensuring adequate leakage inductance and insulation performance. A core-type configuration with cylindrical windings was selected based on FEM simulations and mass-efficiency trade-offs. The final prototype, using copper conductors, achieves 97.8% efficiency with a mass below 50 kg and meets the required 7 mH leakage inductance. High-voltage testing, including partial discharge and breakdown tests, confirmed the insulation coordination of the design. The results demonstrate a practical and scalable approach for high-performance SST integration in renewable energy applications.

PCB transformers are emerging as a promising alternative to medium-frequency wire-wound transformers due to their numerous advantages. However, research on FR-4, the primary PCB insulation material, remains limited. This study investigates the dielectric performance of PCB electrodes through interlayer breakdown tests at 50 Hz, yielding an aging curve for this condition. Additionally, layer-to-layer breakdown tests were conducted at 50 Hz and 1 kHz, revealing a reduction in time to breakdown with increasing frequency. Notably, interlayer breakdown is significantly more likely, exhibiting a breakdown strength eight times lower than that of layer-to-layer breakdown.

This paper presents the prototype development and performance evaluation of a three-stage flyback-based Input Series Converter designed as an Auxiliary Power Supply (APS) for a Modular Multilevel Converter (MMC)-based Arbitrary Waveform Generator (AWG). The APS is connected across the submodule capacitors of the MMC and converts the capacitor voltage to 24V, providing power to the gate drivers and control units within each submodule. The proposed converter features integrated active Input Voltage Sharing (IVS), a scalable architecture, and wide-input voltage operation. A multi-winding flyback transformer ensures high-voltage insulation between the submodule capacitor and the APS output while facilitating active IVS for balancing input capacitor voltages. A transformer prototype has been developed and tested in an open-loop converter configuration. The system’s performance has been evaluated at an output power of 30W across an input voltage range of 300V–3600V.

The effective prediction of dynamic cable ratings (DCR) in the HVDC cable is pivotal for enhancing transmission efficiency and maximizing electricity sales in offshore wind farms. Due to complex wind conditions, traditional machine learning methods, such as support vector machines, struggle to provide accurate long-term DCR predictions and express prediction uncertainties. To address these challenges, this article proposes a novel deep learning framework for dynamic cable rating prediction based on encoder–decoder networks, in which the encoder utilizes Bidirectional extended-long Short-Term Memory networks to encode contextual information from the input data. The decoder introduces an additive attention mechanism, which allows the network to focus on relevant features in the input sequence. In addition, to capture the uncertainty for DCR prediction, a Bayesian neural network approximation method based on the Monte Carlo dropout method is introduced. Finally, this paper introduces a thermal risk estimation method by considering both the maximum conductor temperature limit and the temperature gradient limit. Results demonstrate that the proposed method not only improves electric field distribution but also achieves superior economic benefits.

This paper presents a comprehensive model for power transformers, by considering eddy current losses in both the core and conductors. This is achieved through a meticulous analytical approach that ensures high fidelity in representing the transformer's electromagnetic properties. The consideration of magnetic flux effects on inductance and resistance values significantly enhances the model's accuracy and validity. Traditional analytical methods often resort to simplified approaches due to the complexity of these calculations. The paper addresses these limitations by evaluating the eddy current losses in the core and conductors, and by providing a detailed understanding of each component's impact on transformer behavior. Furthermore, by considering the core and conductor effects on the magnetic field distribution, the model handles a wide range of frequencies, making it suitable for conducting comprehensive transient analysis. To validate the model, comparisons with the finite element method and empirical measurements are conducted. Additionally, a reduced-order transformer model is developed using admittance matrix reduction. This approach focuses on the nodes of interest, effectively eliminating not-observed nodes and reducing computational complexity without compromising accuracy. In this way, voltages at specific points of interest are computed efficiently, maintaining the accuracy of the original model.

Innovative test methods are required to keep up with the increased demand for insulation materials which can withstand the high-frequency square-wave voltages generated by power-electronic equipment. Test systems using high-voltage, high-frequency transformers have proven versatile and easy to realise. The authors investigate the application of amorphous cut cores in such transformers. Analytical and numerical models for the transformer and its frequency response are developed, aiding the design process. An amorphous core-based transformer is designed for 8 kV_pk output at 100 kHz and compared to two previous designs based on ferrite cores. The frequency and pulse response, as well as the high-voltage and thermal performance, are evaluated. The comparison shows that while the low parasitics of the amorphous-based transformer allow for superior frequency response, they are unsuitable for long-duration tests with high pulse repetition frequencies (25–100 kHz) due to increased core losses. The partial discharge inception and flashover voltage are comparable to the ferrite-based transformers.

Traditional methods such as Steinmetz's equation (SE) and its improved variant (iGSE) have demonstrated limited precision in estimating power loss for magnetic materials. The introduction of Neural Network technology for assessing magnetic component power loss has significantly enhanced accuracy. Yet, an efficient method to incorporate detailed flux density information—which critically impacts accuracy—remains elusive. Our study introduces an innovative approach that merges Fast Fourier Transform (FFT) with a Feedforward Neural Network (FNN), aiming to overcome this challenge. To optimize the model further and strike a refined balance between complexity and accuracy, Multi-Objective Optimization (MOO) is employed to identify the ideal combination of hyperparameters, such as layer count, neuron number, activation functions, optimizers, and batch size. This optimized Neural Network outperforms traditionally intuitive models in both accuracy and size. Leveraging the optimized base model for known materials, transfer learning is applied to new materials with limited data, effectively addressing data scarcity. The proposed approach substantially enhances model training efficiency, achieves remarkable accuracy, and sets an example for Artificial Intelligence applications in loss and electrical characteristic predictions with challenges of model size, accuracy goals, and limited data.

To enhance the voltage-handling capability of a switch, the series connection of switching devices is a cost-effective method that preserves many advantages of mature low-voltage devices. Dynamic voltage imbalance and electrical isolation for the devices at the high voltage (HV) side are two important challenges associated with series connection topology. Transformer-coupled gate drivers are excellent for providing both dynamic voltage balance and high galvanic isolation. However, they can only provide the switching function at the transformer pulse frequency. To generate complex waveforms of future power-electronics-dominated grids, a switch with user-defined turn-on/off timing is required for testing grid assets under high-voltage conditions. This article presents a simple, cost-effective open-loop gate driver that overcomes this limitation by introducing two sets of complementary pulse transformers to initialize programmable frequency and duty cycle. Successful experimental verification of the series-connected SiC mosfets prototype is performed at 3.2 kV at various frequencies and duty cycles. The article also demonstrates that the measurement probes placed across series-connected mosfets significantly affect the voltage distribution and validate a compensation mechanism.

This article summarizes the main results and contributions of the MagNet Challenge 2023, an open-source research initiative for data-driven modeling of power magnetic materials. The MagNet Challenge has (1) advanced the state-of-the-art in power magnetics modeling; (2) set up examples for fostering an open-source and transparent research community; (3) developed useful guidelines and practical rules for conducting data-driven research in power electronics; and (4) provided a fair performance benchmark leading to insights on the most promising future research directions. The competition yielded a collection of publicly disclosed software algorithms and tools designed to capture the distinct loss characteristics of power magnetic materials, which are mostly open-sourced. We have attempted to bridge power electronics domain knowledge with state-of-the-art advancements in artificial intelligence, machine learning, pattern recognition, and signal processing. The MagNet Challenge has greatly improved the accuracy and reduced the size of data-driven power magnetic material models. The models and tools created for various materials were meticulously documented and shared within the broader power electronics community.

Dealing with the fast-rising current of high voltage direct current (HVdc) systems during fault conditions, is one of the most challenging aspects of HVdc system protection. Fast dc circuit breakers (DCCB) have recently been employed as a promising technology and are the subject of many research studies. HVdc circuit breakers (CBs) must meet various requirements to satisfy practical and functional needs, among which fast operation, low voltage stress, and economic issues are the key factors. This article presents the procedure for designing a superconductive reactor-based DCCB (SSR-DCCB) for HVdc applications. In the proposed structure, a full-bridge power electronic configuration controls the superconducting reactor to limit the dc fault current and create a dc zero-crossing; it is connected to the HVdc line by a series transformer. After successfully suppressing the line fault current (current zero current), an ultrafast disconnector isolates the faulty line. The main advantage of the proposed HVdc CB is its ability to interrupt the dc fault current without using the solid-state main breaker and limit the magnitude of the fault current and voltage stress. The proposed SSR-DCCB is investigated in MATLAB/Simulink, and an experimental prototype setup validates the results.

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.

Litz wires, which are utilized to suppress eddy current, often have complex structures. This paper presents a partial element equivalent circuit (PEEC)-based 3D model for Litz wires with round conductor. The model accounts for both transverse and longitudinal magnetic fields. The discretization of the Litz wire is based on cylindrical elements resulting in a reduced number of elements. Cylindrical element analysis is based on a 2D analytical method. The proposed model is compared with 3D FEM, which shows the model has good accuracy and fast computational speed. It is promising to facilitate Litz wires optimization.