M. Ghaffarian Niasar
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111 records found
1
Review
(2026)
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Zhengzhao Li, Reza Mirzadarani, Jarno van der Weg, Werner Heyns, Robin van der Sande, Mohamad Ghaffarian Niasar, Aditya Shekhar, Pavol Bauer, Zian Qin
This paper introduces a novel control strategy for Modular Multilevel Resonant converters (MMR) in Solid-State Transformer (SST) applications, with a focus on medium-voltage conversion for hydrogen electrolyzers. The article first reviews voltage control methods in MMR, analyzing their operational principles and regulation capabilities. A continuous modulation index control method with double-step staircase waveform modulation is then proposed, simplifying the control scheme to a single control variable while maintaining robust controllability. Meanwhile, the proposed approach maintains comparable power loss and harmonic performance to existing methods under the investigated operating conditions. Simulations and experiments are conducted to verify the feasibility and practical implementation of the proposed approach.
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This paper introduces a novel control strategy for Modular Multilevel Resonant converters (MMR) in Solid-State Transformer (SST) applications, with a focus on medium-voltage conversion for hydrogen electrolyzers. The article first reviews voltage control methods in MMR, analyzing their operational principles and regulation capabilities. A continuous modulation index control method with double-step staircase waveform modulation is then proposed, simplifying the control scheme to a single control variable while maintaining robust controllability. Meanwhile, the proposed approach maintains comparable power loss and harmonic performance to existing methods under the investigated operating conditions. Simulations and experiments are conducted to verify the feasibility and practical implementation of the proposed approach.
Transient Overvoltages in Onshore HVDC Cable Joints
Surge Reflections and the Influence of Grounding Configurations
This study examines transient overvoltage phenomena in 525 kV high-voltage direct current (HVDC) onshore cable systems, with particular emphasis on the influence of grounding configurations in two joint types: straight-through and screen-separated. Transient overvoltages arising from wave propagation and reflections are analysed, highlighting the impact of joint types, bonding cable configurations (coaxial vs. noncoaxial) and bonding cable length on the resulting overvoltage magnitudes. The necessity of modelling screen-to-earth representations of sectionalised cables at grounded joint locations in the vicinity of faults is emphasised, whereas simplified representations of ungrounded and grounded straight-through joints are identified as sufficient for system-level simulations. To address the computational challenges of detailed electromagnetic transient simulations, a stand-alone simplified circuit is proposed to analyse grounded joint transients and to mitigate errors caused by insufficient time-step resolution. The results provide practical insights for insulation coordination, supporting the reliable integration of HVDC technology into long-distance cable-based transmission networks while enhancing system resilience.
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This study examines transient overvoltage phenomena in 525 kV high-voltage direct current (HVDC) onshore cable systems, with particular emphasis on the influence of grounding configurations in two joint types: straight-through and screen-separated. Transient overvoltages arising from wave propagation and reflections are analysed, highlighting the impact of joint types, bonding cable configurations (coaxial vs. noncoaxial) and bonding cable length on the resulting overvoltage magnitudes. The necessity of modelling screen-to-earth representations of sectionalised cables at grounded joint locations in the vicinity of faults is emphasised, whereas simplified representations of ungrounded and grounded straight-through joints are identified as sufficient for system-level simulations. To address the computational challenges of detailed electromagnetic transient simulations, a stand-alone simplified circuit is proposed to analyse grounded joint transients and to mitigate errors caused by insufficient time-step resolution. The results provide practical insights for insulation coordination, supporting the reliable integration of HVDC technology into long-distance cable-based transmission networks while enhancing system resilience.
Journal article
(2026)
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Reza Mirzadarani, Zhengzhao Li, Zian Qin, Peter Vaessen, Pavol Bauer, Mohamad Ghaffarian Niasar
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.
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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.
Medium-Frequency Transformer for SST Applications
Design and Optimization
Journal article
(2026)
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Reza Mirzadarani, Leonardo Bolzonella, Zhengzhao Li, Zian Qin, Peter Vaessen, Pavol Bauer, Mohamad Ghaffarian Niasar
This work presents a downscaled validation of a medium-voltage, medium-frequency transformer (MFT) concept designed for high-current operation on the secondary side using multiple parallel paths. The design is based on a modular winding approach, which simplifies the construction process and conductor placement on the bobbin. A systematic design and optimization procedure is developed, combining analytical calculations and finite-element simulations to explore the mass-efficiency tradeoff and to select a candidate design that meets specified leakage inductance and loss targets. The developed prototype serves as a proof of concept, demonstrating that the electrical, magnetic, and insulation requirements of the full-scale MFT can be effectively verified at reduced power levels. The fabricated prototype is tested under short-circuit and partial discharge conditions. The impedance measurements confirmed the expected resonance behavior, and the partial discharge test results verified sufficient insulation performance under high-voltage stress. The results provide experimental evidence for the scalability and feasibility of the proposed transformer design and offer guidelines for the use of 3D-printed supports, grain-oriented electrical steel cores, and windings in medium-voltage, MFT systems for hydrogen production applications.
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This work presents a downscaled validation of a medium-voltage, medium-frequency transformer (MFT) concept designed for high-current operation on the secondary side using multiple parallel paths. The design is based on a modular winding approach, which simplifies the construction process and conductor placement on the bobbin. A systematic design and optimization procedure is developed, combining analytical calculations and finite-element simulations to explore the mass-efficiency tradeoff and to select a candidate design that meets specified leakage inductance and loss targets. The developed prototype serves as a proof of concept, demonstrating that the electrical, magnetic, and insulation requirements of the full-scale MFT can be effectively verified at reduced power levels. The fabricated prototype is tested under short-circuit and partial discharge conditions. The impedance measurements confirmed the expected resonance behavior, and the partial discharge test results verified sufficient insulation performance under high-voltage stress. The results provide experimental evidence for the scalability and feasibility of the proposed transformer design and offer guidelines for the use of 3D-printed supports, grain-oriented electrical steel cores, and windings in medium-voltage, MFT systems for hydrogen production applications.
Journal article
(2026)
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Reza Mirzadarani, Zhengzhao Li, Zian Qin, Peter Vaessen, Pavol Bauer, Mohamad Ghaffarian Niasar
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.
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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.
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.
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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.
Partial discharge (PD) within cavities in oil-impregnated paper (OIP) is one of the key aging mechanisms that can alter space-charge behavior and eventually contribute to insulation failure in underground cables. This study investigates the evolution of charge-transport characteristics in a three-layer OIP sample containing an artificial cavity under PD aging. Time-resolved pulsed electroacoustic (PEA) measurements show that PD aging changes the measured space-charge profiles, leading to a lower injected charge density, faster charge redistribution during depolarization, and enhanced charge accumulation near the oil–paper interfaces. To interpret these experimentally observed trends, a modified charge transport model incorporating dual-trap energy levels and hopping conduction is developed. Model fitting to the measured PEA profiles suggests that PD aging is associated with a reduction in the effective deep-trap energy level and an increase in shallow-trap density, which facilitates carrier de-trapping and promotes the redistribution of space charge from the bulk region toward the interfaces. The results provide insight into the relationship between PD-induced charge-transport modification and OIP insulation degradation, and may support the condition assessment and maintenance of underground cable insulation systems.
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Partial discharge (PD) within cavities in oil-impregnated paper (OIP) is one of the key aging mechanisms that can alter space-charge behavior and eventually contribute to insulation failure in underground cables. This study investigates the evolution of charge-transport characteristics in a three-layer OIP sample containing an artificial cavity under PD aging. Time-resolved pulsed electroacoustic (PEA) measurements show that PD aging changes the measured space-charge profiles, leading to a lower injected charge density, faster charge redistribution during depolarization, and enhanced charge accumulation near the oil–paper interfaces. To interpret these experimentally observed trends, a modified charge transport model incorporating dual-trap energy levels and hopping conduction is developed. Model fitting to the measured PEA profiles suggests that PD aging is associated with a reduction in the effective deep-trap energy level and an increase in shallow-trap density, which facilitates carrier de-trapping and promotes the redistribution of space charge from the bulk region toward the interfaces. The results provide insight into the relationship between PD-induced charge-transport modification and OIP insulation degradation, and may support the condition assessment and maintenance of underground cable insulation systems.
Increasing wind farm capacity via overplanting enhances energy production but risks accelerating cable aging if transmission capacity is poorly managed. Consequently, resilient Dynamic Cable Rating (DCR) prediction-defined as the ability to maintain stability under data quality degradation and operational shifts-is crucial for reliable operation. However, achieving this is challenged by limited datasets, missing data, and complex spatio-temporal correlations. To address these issues, a resilient DCR prediction and thermal estimation framework is developed. First, a Conditional Generative Adversarial Network (CGAN) is applied to synthetically augment limited datasets, effectively resolving the load data imbalance. Second, a Spatio-Temporal Graph Attention Residual Shrinkage Network (STGARSN) is proposed. This model integrates an extended Long Short-Term Memory (LSTM) network with Temporal Convolutional Networks (TCN) and a graph attention mechanism to capture complex correlations. Crucially, it incorporates a residual shrinkage module to filter noise and outliers, thereby ensuring model resilience. Finally, to optimize economic performance while minimizing cable aging, a comparative analysis of various overplanting strategies is conducted. Experiments on real cable temperature measurements demonstrate the superior resilience of the proposed model, maintaining high accuracy not only across different forecasting horizons but also under conditions of missing data and sensor noise. The proposed framework accurately predicts DCR and supports long-term offshore wind farm operations through improved economic and technical decision-making.
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Increasing wind farm capacity via overplanting enhances energy production but risks accelerating cable aging if transmission capacity is poorly managed. Consequently, resilient Dynamic Cable Rating (DCR) prediction-defined as the ability to maintain stability under data quality degradation and operational shifts-is crucial for reliable operation. However, achieving this is challenged by limited datasets, missing data, and complex spatio-temporal correlations. To address these issues, a resilient DCR prediction and thermal estimation framework is developed. First, a Conditional Generative Adversarial Network (CGAN) is applied to synthetically augment limited datasets, effectively resolving the load data imbalance. Second, a Spatio-Temporal Graph Attention Residual Shrinkage Network (STGARSN) is proposed. This model integrates an extended Long Short-Term Memory (LSTM) network with Temporal Convolutional Networks (TCN) and a graph attention mechanism to capture complex correlations. Crucially, it incorporates a residual shrinkage module to filter noise and outliers, thereby ensuring model resilience. Finally, to optimize economic performance while minimizing cable aging, a comparative analysis of various overplanting strategies is conducted. Experiments on real cable temperature measurements demonstrate the superior resilience of the proposed model, maintaining high accuracy not only across different forecasting horizons but also under conditions of missing data and sensor noise. The proposed framework accurately predicts DCR and supports long-term offshore wind farm operations through improved economic and technical decision-making.
Perfluoroalkoxy alkane (PFA) is a promising candidate for onbaord high-voltage cable insulation due to its superior dielectric properties, chemical resistance, and high thermal stability. Understanding the thermal aging behavior of PFA is essential for ensuring the long-term reliability of insulation materials in hybrid-electric aircraft, where high thermal fluctuations are common. This study investigates the chemical, structural, mechanical, and dielectric properties of PFA aged at 280 °C for up to 1000 h, simulating real-world aerospace operational environments. Results show that PFA undergoes chain scission and chemicrystallization in the early aging stages (0-480 h), leading to an increase in crystallinity. However, at longer aging times e.g. (>480 h), oxidative degradation becomes dominant, resulting in chemical and structural changes correlated with microstructural damage, including crack formation, tie-chain loss, and lamellar disruption. Dynamic mechanical analysis and tensile results show a significant decrease in molecular rigidity with a reduction in glass transition temperature (Tg), indicating a loss of material stiffness and a reduction in tensile strength (42.16%) and elongation (30.2%) after long term exposure (1000 h). Dielectric characterization demonstrates monotonic increase in dielectric constant (from 1.90 to 2.15), dissipation factor, and AC conductivity, attributed to the formation of polar oxidation products and defect-assisted interfacial polarization. The dielectric strength also decreases from 95.2 kV/mm to 87.1 kV/mm after 1000 h of aging. Molecular dynamics simulations (MDS) are also performed to study the temperature effect on PFA, revealing that at high temperatures, the PFA molecular structure is increasingly destroyed by thermal chain scission. These findings provide valuable insight into the degradation mechanisms governing PFA performance and contribute to evaluating its reliability as an insulation material for high-voltage cable systems in hybrid-electric aircraft.
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Perfluoroalkoxy alkane (PFA) is a promising candidate for onbaord high-voltage cable insulation due to its superior dielectric properties, chemical resistance, and high thermal stability. Understanding the thermal aging behavior of PFA is essential for ensuring the long-term reliability of insulation materials in hybrid-electric aircraft, where high thermal fluctuations are common. This study investigates the chemical, structural, mechanical, and dielectric properties of PFA aged at 280 °C for up to 1000 h, simulating real-world aerospace operational environments. Results show that PFA undergoes chain scission and chemicrystallization in the early aging stages (0-480 h), leading to an increase in crystallinity. However, at longer aging times e.g. (>480 h), oxidative degradation becomes dominant, resulting in chemical and structural changes correlated with microstructural damage, including crack formation, tie-chain loss, and lamellar disruption. Dynamic mechanical analysis and tensile results show a significant decrease in molecular rigidity with a reduction in glass transition temperature (Tg), indicating a loss of material stiffness and a reduction in tensile strength (42.16%) and elongation (30.2%) after long term exposure (1000 h). Dielectric characterization demonstrates monotonic increase in dielectric constant (from 1.90 to 2.15), dissipation factor, and AC conductivity, attributed to the formation of polar oxidation products and defect-assisted interfacial polarization. The dielectric strength also decreases from 95.2 kV/mm to 87.1 kV/mm after 1000 h of aging. Molecular dynamics simulations (MDS) are also performed to study the temperature effect on PFA, revealing that at high temperatures, the PFA molecular structure is increasingly destroyed by thermal chain scission. These findings provide valuable insight into the degradation mechanisms governing PFA performance and contribute to evaluating its reliability as an insulation material for high-voltage cable systems in hybrid-electric aircraft.
Low-temperature atmospheric plasma (LTP) is widely used in industrial processes, such as disinfection, surface modification and wastewater treatment. The dielectric barrier discharge (DBD) is regarded as one of the most robust and reliable methods for generating LTP in ambient air. Compared to conventional AC excitation, pulsed powering offers several advantages (i.e., lower energy use and heat production). The present trend is to use short and fast pulses (in the nano- and picosecond range). In this review, the key design parameters of a DBD (barrier thickness, relative permittivity and gap distance) are discussed. Material-specific phenomena like surface charging and degradation are analyzed. The complex interactions between the pulse source and DBD are examined. By mapping the interdependencies, this review aims to support the rational design and optimization of pulsed DBD systems, and to facilitate their broader industrial use.
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Low-temperature atmospheric plasma (LTP) is widely used in industrial processes, such as disinfection, surface modification and wastewater treatment. The dielectric barrier discharge (DBD) is regarded as one of the most robust and reliable methods for generating LTP in ambient air. Compared to conventional AC excitation, pulsed powering offers several advantages (i.e., lower energy use and heat production). The present trend is to use short and fast pulses (in the nano- and picosecond range). In this review, the key design parameters of a DBD (barrier thickness, relative permittivity and gap distance) are discussed. Material-specific phenomena like surface charging and degradation are analyzed. The complex interactions between the pulse source and DBD are examined. By mapping the interdependencies, this review aims to support the rational design and optimization of pulsed DBD systems, and to facilitate their broader industrial use.
Accurate frequency-dependent inductances and resistances are essential for high-frequency transformer models. Traditional analytical approaches, such as cases where eddy-current losses are neglected, or resistances and inductances are computed independently, and numerical techniques such as finite element methods (FEM) are either computationally intensive or rely on simplifications that reduce accuracy. This letter proposes a novel machine learning (ML)-based approach to efficiently estimate these parameters by learning from detailed analytical results. Using a localized feature selection strategy with conductors near the nearest neighbors $k$, the model considers complex electromagnetic interactions while achieving a significant reduction in computation time. This allows for generalization across different winding designs, reducing the dependence on traditional simplifications. Furthermore, the trained ML model achieves high accuracy, with predictions within an error margin of 5% for a wide frequency range. Comparison with measurements confirms the validity and effectiveness of the proposed approach, making it a promising solution for electromagnetic transient simulations.
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Accurate frequency-dependent inductances and resistances are essential for high-frequency transformer models. Traditional analytical approaches, such as cases where eddy-current losses are neglected, or resistances and inductances are computed independently, and numerical techniques such as finite element methods (FEM) are either computationally intensive or rely on simplifications that reduce accuracy. This letter proposes a novel machine learning (ML)-based approach to efficiently estimate these parameters by learning from detailed analytical results. Using a localized feature selection strategy with conductors near the nearest neighbors $k$, the model considers complex electromagnetic interactions while achieving a significant reduction in computation time. This allows for generalization across different winding designs, reducing the dependence on traditional simplifications. Furthermore, the trained ML model achieves high accuracy, with predictions within an error margin of 5% for a wide frequency range. Comparison with measurements confirms the validity and effectiveness of the proposed approach, making it a promising solution for electromagnetic transient simulations.
The increasing penetration of renewable energy sources and frequent lightning and switching events have intensified transient phenomena in modern power systems, exposing power transformers to resonance at critical frequencies. These conditions may cause internal overvoltages, and insulation failure. While many studies focus on wide-band transformer modeling and resonance identification, their primary objective is accurate frequency-domain representation rather than revealing the physical origin of resonance inside the transformer. This paper does not aim to introduce a new transformer modeling method. Instead, it presents a visualization-based approach to identify transformer components responsible for resonance. By analyzing the branch current matrix of a transformer disk model and visualizing current distribution using a color map, dominant resonance-driving elements are identified. This visualization enables protection and future design enhancement.
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The increasing penetration of renewable energy sources and frequent lightning and switching events have intensified transient phenomena in modern power systems, exposing power transformers to resonance at critical frequencies. These conditions may cause internal overvoltages, and insulation failure. While many studies focus on wide-band transformer modeling and resonance identification, their primary objective is accurate frequency-domain representation rather than revealing the physical origin of resonance inside the transformer. This paper does not aim to introduce a new transformer modeling method. Instead, it presents a visualization-based approach to identify transformer components responsible for resonance. By analyzing the branch current matrix of a transformer disk model and visualizing current distribution using a color map, dominant resonance-driving elements are identified. This visualization enables protection and future design enhancement.
Power transformer energization involves a significant electromagnetic energy exchange among system components, with periodic oscillations at the system's natural frequencies. As a result, weakly damped resonance overvoltages may occur, overstressing the system and thereby leading to potential insulation failure. This phenomenon is particularly notable for topologies where a transformer is supplied via cable, as low-damping resonance frequencies are likely to be formed due to mutual interactions between the cable and the transformer. The prestriking phenomenon during circuit breaker closing plays an important role in the excitation of resonance frequencies. Specifically, repeated prestrikes can create highfrequency resonances during switching-on operations. This paper analyzes the mutual interactions between the cable and the transformer, focusing on how the resonances between the cable and the transformer are created. Then, using a suitable modeling approach, the impact of CB prestrikes on the resultant resonance excitation in cable-transformer systems is investigated. Finally, tests are conducted using an experimental test setup to validate the investigations performed. The obtained results demonstrate that resonance frequencies emerging from cable-transformer interactions lead to the excitation of oscillatory overvoltages with extreme magnitudes.
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Power transformer energization involves a significant electromagnetic energy exchange among system components, with periodic oscillations at the system's natural frequencies. As a result, weakly damped resonance overvoltages may occur, overstressing the system and thereby leading to potential insulation failure. This phenomenon is particularly notable for topologies where a transformer is supplied via cable, as low-damping resonance frequencies are likely to be formed due to mutual interactions between the cable and the transformer. The prestriking phenomenon during circuit breaker closing plays an important role in the excitation of resonance frequencies. Specifically, repeated prestrikes can create highfrequency resonances during switching-on operations. This paper analyzes the mutual interactions between the cable and the transformer, focusing on how the resonances between the cable and the transformer are created. Then, using a suitable modeling approach, the impact of CB prestrikes on the resultant resonance excitation in cable-transformer systems is investigated. Finally, tests are conducted using an experimental test setup to validate the investigations performed. The obtained results demonstrate that resonance frequencies emerging from cable-transformer interactions lead to the excitation of oscillatory overvoltages with extreme magnitudes.
High-end power conversion applications increasingly use insulated metal substrate (IMS) printed circuit boards (PCBs) with very thin dielectrics to improve thermal performance. To ensure the reliability of these PCBs when exposed to high-frequency voltages, the breakdown and aging mechanisms of the PCB laminates under high-frequency voltage stress must be understood. This article investigates the breakdown and lifetime of these laminates using two high-frequency test sources for sinusoidal and square-wave voltages in the typical frequency range of 25–100 kHz and a test voltage up to 8 kV, which is a significant increase compared with the existing literature. Diagnostic tests, such as partial discharge (PD) measurement and dielectric frequency response analysis, are performed to analyze the high-frequency aging mechanisms further. Despite the rapid degradation of the insulation system under high-frequency voltage stresses, the results show that the IMS PCB laminates are quite robust, with high breakdown fields. The lifetime of the PCB laminates is found to vary approximately with the inverse of the frequency. Surface degradation due to the high inhomogeneous fields at the edges of the conducting planes is identified as one of the main lifetime risks. This is similar to more conventional PCB constructions. Diagnostic tests suggest that the accelerated degradation is due to highly localized PD activity and electrical treeing.
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High-end power conversion applications increasingly use insulated metal substrate (IMS) printed circuit boards (PCBs) with very thin dielectrics to improve thermal performance. To ensure the reliability of these PCBs when exposed to high-frequency voltages, the breakdown and aging mechanisms of the PCB laminates under high-frequency voltage stress must be understood. This article investigates the breakdown and lifetime of these laminates using two high-frequency test sources for sinusoidal and square-wave voltages in the typical frequency range of 25–100 kHz and a test voltage up to 8 kV, which is a significant increase compared with the existing literature. Diagnostic tests, such as partial discharge (PD) measurement and dielectric frequency response analysis, are performed to analyze the high-frequency aging mechanisms further. Despite the rapid degradation of the insulation system under high-frequency voltage stresses, the results show that the IMS PCB laminates are quite robust, with high breakdown fields. The lifetime of the PCB laminates is found to vary approximately with the inverse of the frequency. Surface degradation due to the high inhomogeneous fields at the edges of the conducting planes is identified as one of the main lifetime risks. This is similar to more conventional PCB constructions. Diagnostic tests suggest that the accelerated degradation is due to highly localized PD activity and electrical treeing.
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.
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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 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.
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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.
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.
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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.
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.
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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.
Journal article
(2025)
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L.F.A. Wymenga, J. van Turnhout, M. Ghaffarian Niasar, H.W. van Zeijl, W.D. van Driel, G.Q. Zhang
Cold atmospheric plasma (CAP) is widely used in domains such as disinfection, surface treatment and food preservation. When generated in air, CAP is rich in reactive oxygen and nitrogen species (RONS), such as ozone (O3). A dielectric barrier discharge (DBD) is a reliable method to create CAP. We developed a double-sided (twin) surface DBD with novel ‘interfractal’ electrode geometries. This fractal configuration creates stronger electric fields than the customary interdigital line geometry. So, CAP is produced more effectively, resulting in higher RONS concentrations. The performance of interfractal electrodes was compared to that of interdigital electrodes (IDE) in atmospheric air. Nanopulsed powering was used, since it is the most efficient for powering DBDs. Electrical and chemical characteristics (such as ozone level) were assessed. The results show that interfractal electrodes enhance the electric field, conduction current and ozone yield.
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Cold atmospheric plasma (CAP) is widely used in domains such as disinfection, surface treatment and food preservation. When generated in air, CAP is rich in reactive oxygen and nitrogen species (RONS), such as ozone (O3). A dielectric barrier discharge (DBD) is a reliable method to create CAP. We developed a double-sided (twin) surface DBD with novel ‘interfractal’ electrode geometries. This fractal configuration creates stronger electric fields than the customary interdigital line geometry. So, CAP is produced more effectively, resulting in higher RONS concentrations. The performance of interfractal electrodes was compared to that of interdigital electrodes (IDE) in atmospheric air. Nanopulsed powering was used, since it is the most efficient for powering DBDs. Electrical and chemical characteristics (such as ozone level) were assessed. The results show that interfractal electrodes enhance the electric field, conduction current and ozone yield.
Journal article
(2025)
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Zhaoxin Wang, Xing Wei, Claus Leth Bak, Filipe Faria da Silva, Tianming Luo, Weichuan Zhao, Peter Vaessen, Henrik Sorensen, Mohamad Ghaffarian Niasar
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.
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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.