Search Results (77)

Synchronous Alternating Current (AC) power systems are increasingly supported by embedded High-Voltage Direct Current (HVDC) links to enhance operational flexibility and ensure security of supply. However, the loss of High-Voltage Alternating Current (HVAC) interconnections in these synchronous areas may lead to transmission network splitting, posing serious challenges to frequency stability due to the reduction in overall system inertia and stiffness. In this paper, a supplementary control layer is proposed to enable embedded HVDC systems, particularly those based on modern Voltage Source Converters (VSCs), to support frequency stability under post-splitting conditions. The proposed control strategy combines Angle-Difference Control (ADC), Frequency-Difference Control (FDC), and feedforward action, enabling fast and coordinated active-power modulation. A single-bus, dynamic multi-area Load Frequency Control (LFC) model is developed, combining the regulation of thermal units, Renewable Energy Sources’ (RESs’) Fast Frequency Response (FFR) with Synthetic Inertia (SI), and VSC-HVDC modulation. The effectiveness of the proposed control layer is demonstrated by applying it to the East Tyrrhenian Link (ETL), an embedded VSC-HVDC interconnection connecting Sicily with the mainland of Italy, under a post-splitting low-inertia condition in which Sicily operates as an islanded synchronous system, i.e., after losing synchronism with the mainland of Italy, in a 2030 scenario condition. The simulation results demonstrate that the proposed controller enables embedded VSC-HVDC systems to actively participate in post-splitting frequency containment and damping, as well as coordinated active power reallocation, thereby enhancing overall system stability and resilience. Full article

Phase-shifting fringe projection (PSFP) is widely used in industrial inspection and three-dimensional measurement, where $\gamma$ nonlinearity of the projector–camera system is traditionally treated as a phase-error source to be calibrated or compensated. In this work, $\gamma$ nonlinearity is reinterpreted from an imaging perspective and shown to act as a statistical distortion mechanism that reshapes modulation stability, overexposure behavior, and defect saliency in fringe-based imaging. Building on the intrinsic DC–AC decomposition of phase-shifting demodulation, we analyze how $\gamma$ nonlinearity interacts with fringe modulation and frequency-selective transfer. An analytical model reveals that $\gamma$ nonlinearity simultaneously suppresses the fringe fundamental and introduces harmonic leakage, leading to systematic compression of mean modulation contrast in high-brightness regions. As a result, $\gamma$ correction does not necessarily enhance mean-based defect contrast and may even reduce it, contrary to common intuition. We further demonstrate that the primary benefit of $\gamma$ correction lies in statistical stabilization rather than contrast amplification. By introducing modulation-domain saliency formulations and a frequency-domain harmonic energy ratio, a physical link is established between $\gamma$ nonlinearity, overexposure, and defect separability. Controlled experiments on highly reflective sheet-metal specimens confirm that while mean-contrast- and SNR-based saliency metrics often decrease after $\gamma$ correction, separability-based metrics consistently improve due to reduced nonlinear- and saturation-induced variance. Cross-channel and cross-condition analyses further show that modulation and reflectance images respond differently to $\gamma$ correction, yet metric-level separability exhibits consistent improvement across channels. These results clarify the true role of $\gamma$ correction in fringe-based inspection and provide theoretical insight and practical guidance for robust defect imaging under nonlinear and near-overexposure conditions. Full article

The Atomic Clock Ensemble in Space (ACES) mission, currently operating aboard the International Space Station (ISS), is designed to provide high-precision time and frequency measurements and to test fundamental aspects of relativistic physics. Gravitational redshift (GRS), a fundamental prediction of General Relativity (GR), implies that clocks positioned at different gravitational potentials experience relative time dilation. Previous GRS experiments have focused primarily on microwave technologies, with negligible experimental coverage in the optical domain, particularly for ground-to-space links. Motivated by the European Laser Timing (ELT) experiment and the high-precision laser-cooled cesium clock aboard ACES, we introduce and evaluate an optical time-transfer method designed to achieve high-accuracy measurements of GRS. In the absence of actual ELT/ACES optical data, a high-fidelity numerical simulation framework was developed to assess the performance of this method. The framework incorporates representative ELT/ACES mission parameters, including the space-based cesium clock and the H-MASER clock located at the reference ground station, both providing frequency stability at the level of ${10}^{-15}$ for 1000 s averaging time. Applying a $\pm 1\sigma$ filtering criterion, we obtain a simulated dataset comprising 33 ELT/ACES passes, representing a total observation time of 4.38 h over a single week. Analysis of this high-fidelity dataset reveals a GRS deviation from GR of $(-7.19\pm 0.63)\times {10}^{-5}$, achieving a 3.4 orders of magnitude improvement over the best previous laser-ranging experiment conducted at the University of Maryland (UMD), USA, 51 years ago. These simulation results demonstrate that the optical time-transfer link constitutes a powerful tool for testing fundamental physics and, when combined with next-generation optical atomic clocks, enables unprecedented capabilities in space-based timekeeping and geoscience applications. Full article

Wide-bandgap (WBG) semiconductor materials such as silicon carbide (SiC) and gallium nitride (GaN) are key enablers of power-electronics converters for aerospace platforms, where high efficiency, weight reduction, and thermal robustness are critical requirements. This paper presents the main challenges associated with the use of these technologies, including protection requirements, electromagnetic compatibility, and thermal management, as well as the material advantages that enable higher switching frequencies and lower losses compared to conventional Si technologies. A comparative analysis of semiconductor technologies and suitable power-conversion topologies for the aerospace context is provided. Representative laboratory-scale experimental validation is presented, including the development of a DC–DC boost converter and a DC–AC full-bridge inverter, which are linked through the common DC-link and are used for interfacing batteries and an electrical motor, both based on GaN and SiC diodes. The results demonstrated the correct operation, with stable high-frequency performance under controlled laboratory conditions, supporting aerospace-oriented development, although evaluated in a laboratory environment, confirming the potential of WBG technologies for future power-conversion architectures. Full article

This paper proposes a single-phase AC-AC solid-state transformer (SST) that eliminates bulky energy storage components. The proposed matrix-type structure comprises a line-frequency (LF) rectifier, a half-bridge (HB) LLC resonant converter, a buck–boost converter, and an LF inverter. The HB LLC resonant converter not only achieves high efficiency at unity voltage gain but also provides high-frequency (HF) isolation as a DC transformer (DCX). Meanwhile, the buck–boost converter ensures precise voltage regulation. The replacement of traditional DC-link electrolytic capacitors with small film capacitors effectively suppresses the second-harmonic power ripple, leading to a significant improvement in both power density and operational reliability. Experimental results from a 1 kW prototype demonstrate high-quality sinusoidal input and output, a wide range of zero-voltage switching (ZVS) operations, and stable output voltage control. Full article

Computational analysis using PSpice has become an indispensable tool for evaluating power electronics circuits, as it allows accurate simulation of transient effects, ripple, and component dynamics, enabling reliable assessment of complex topologies before physical implementation. In single-phase systems, electrolytic components are commonly used due to their high energy density, which helps mitigate low-frequency ripple caused by power oscillations between the DC and AC sides. However, these components have a limited lifespan, which compromises the system’s long-term reliability. This work proposes and evaluates the Stacked Switched Capacitor (SSC) topology as a power decoupling technique, implemented within a 200 W Cuk converter. The proposed SSC design enables a substantial reduction in required capacitance, replacing a conventional 600 μF capacitor with only three 36 μF capacitors, while maintaining voltage stability and output power performance. Simulation results show a high efficiency of 94% and a DC-link energy of 0.992 J, confirming the SSC’s ability to effectively mitigate voltage ripple at twice the grid angular frequency (2ω, rad/s) without compromising system durability. Comparative analysis with conventional decoupling strategies demonstrates that the SSC topology offers a compact, efficient, and reliable alternative, reducing the number of required passive components and switching devices. These results provide a strong basis for further exploration of SSC-based designs in space- and cost-constrained single-phase DC-AC applications. Full article

High-voltage (HV) cable systems—particularly those insulated with cross-linked polyethylene (XLPE)—are increasingly deployed in both AC and DC applications due to their excellent electrical and mechanical performance. However, their long-term reliability is challenged by partial discharges (PD), insulation aging, space charge accumulation, and thermal and electrical stresses. This review provides a comprehensive survey of the state-of-the-art technologies and methodologies across several domains critical to the assessment and enhancement of cable reliability. It covers advanced condition monitoring (CM) techniques, including sensor-based PD detection, signal acquisition, and denoising methods. Aging mechanisms under various stressors and lifetime estimation approaches are analyzed, along with fault detection and localization strategies using time-domain, frequency-domain, and hybrid methods. Physics-based and data-driven models for PD behavior and space charge dynamics are discussed, particularly under DC conditions. The article also reviews the application of numerical tools such as FEM for thermal and field stress analysis. A dedicated focus is given to machine learning (ML) and deep learning (DL) models for fault classification and predictive maintenance. Furthermore, standards, testing protocols, and practical issues in sensor deployment and calibration are summarized. The review concludes by evaluating intelligent maintenance approaches—including condition-based and predictive strategies—framed within real-world asset management contexts. The paper aims to bridge theoretical developments with field-level implementation challenges, offering a roadmap for future research and practical deployment in resilient and smart power grids. This review highlights a clear gap in fully integrated AC/DC diagnostic and aging analyses for XLPE cables. We emphasize the need for unified physics-based and ML-driven frameworks to address HVDC space-charge effects and multi-stress degradation. These insights provide concise guidance for advancing reliable and scalable cable assessment. Full article

Parental adverse childhood experiences (ACEs) are linked to negative outcomes in children, including emotional and behavioral problems, developmental delays, and higher risk for psychopathology. Most research focuses on school-aged children or community samples, with few studies examining preschool-aged children in child psychiatric care. Understanding parental ACEs in this population is crucial, as early childhood is a sensitive developmental period, and intergenerational effects may be particularly pronounced in children already presenting with psychiatric symptoms. Background/Objectives: The goal of this study was to analyze how parents of patients in an early childhood (0–5.9 yrs) mental health outpatient clinic differ from the general population in terms of the frequency of ACEs. In addition, we investigated the connection between mental health disorders in young children and the specific ACE scores of their parents. Methods: A total of 116 caregivers (34.45 years (SD = 5.28)) and their children (71.6% boys, 28.4% girls) at an average age of 3.99 years (SD = 1.35, range = 0.31–5.95) were included in the analysis. The legal guardians completed the 10-item ACE questionnaire. The young children were diagnosed as part of outpatient treatment using the DC:0–5 classification system. We analyzed the ACE scores and diagnoses descriptively and in comparison to a community sample. Results: An average value of 2.38 parental ACEs was reported by our sample, and 68.1% (n = 79) reported at least one ACE. The high-risk group with four or more ACEs comprised 30.2% (n = 35). The most common diagnosis in young children was the Disorder of Dysregulated Anger and Aggression of Early Childhood, followed by global developmental delay. Adjustment disorder was third in terms of frequency. Among the examined child psychiatric diagnoses, adjustment disorder showed a significant correlation with parents being affected by the ACE category of neglect (OR = 2.54; 95% CI: 1.012–6.369; p = 0.047). Conclusions: Parents who presented their children at an early childhood mental health outpatient clinic reported significantly more ACEs as compared to representative data on ACEs in adulthood. These results highlight the need for further studies with larger samples to enable a more in-depth analysis of the general intergenerational transmission processes and the differential transmission of specific ACEs to specific diagnoses in preschool-aged children. Full article

This paper presents a novel open-loop modulation and control strategy for bidirectional, multi-source/load parallel AC-link power converters. While these converters offer advantages such as high-frequency operation and flexible power conversion capabilities, their application to complex systems such as nanogrids presents significant control challenges. Traditional control methods often struggle to efficiently manage power flow and charging/discharging processes, especially when dealing with multiple sources and loads of varying characteristics. To address these issues, this paper proposes a new control strategy that enables intelligent source and load selection while maintaining fast charging and discharging times. Simulation results demonstrate the effectiveness of the proposed approach. This research contributes to advancing the state-of-the-art in power electronics by providing a foundation for improved control of complex power conversion systems for renewable energy applications. Full article

Partial discharge (PD) is a critical indicator of insulation degradation in high-voltage DC systems, necessitating accurate diagnosis to ensure long-term reliability. Conventional AC-based diagnostic methods, such as phase-resolved partial discharge analysis (PRPDA), are ineffective under DC conditions, emphasizing the need for waveform-based analysis. This study presents a novel clustering framework for DC PD pulses, leveraging multi-level wavelet decomposition and statistical feature extraction. Each signal is decomposed into multiple frequency bands, and 70 distinctive waveform features are extracted from each pulse. To mitigate feature redundancy and enhance clustering performance, principal component analysis (PCA) is employed for dimensionality reduction. Experimental data were obtained from multiple defect types and measurement distances using a 22.9 kV cross-linked polyethylene (XLPE) cable system. The proposed method significantly outperformed conventional time-frequency (T-F) mapping techniques, particularly in scenarios involving signal attenuation and mixed noise. Propagation-induced distortion was effectively addressed through multi-resolution analysis. In addition, field noise sources such as HVDC converter switching transients and fluorescent lamp emissions were included to assess robustness. The results confirmed the framework’s capability to distinguish between multiple PD types and noise sources, even in challenging environments. Furthermore, optimal mother wavelet selection and correlation-based feature analysis contributed to improved clustering resolution. This framework supports robust PD classification in practical HVDC diagnostics. The framework can contribute to the development of real-time autonomous monitoring systems for HVDC infrastructure. Future research will explore incorporating temporal deep learning architectures for automated PD-type recognition based on clustered data. Full article

Enhancing the resilience of renewable energy systems in ultra-weak grids is crucial for promoting sustainable energy adoption and ensuring a reliable power supply during disturbances. Ultra-weak grids characterized by a very low Short-Circuit Ratio, less than 2, and high grid impedance significantly impair voltage and frequency stability, imposing challenging conditions for Inverter-Based Resources. To address these challenges, this paper considers a 110 KVA, three-phase, two-level Voltage Source Converter, interfacing a 700 V DC link to a 415 V AC ultra-weak grid. X/R = 1 is controlled using Sinusoidal Pulse Width Modulation, where the Grid-Connected Converter operates in Grid-Forming Mode to maintain voltage and frequency stability under a steady state. During symmetrical and asymmetrical faults, the converter transitions to Grid-Following mode with current control to safely limit fault currents and protect the system integrity. After fault clearance, the system seamlessly reverts to Grid-Forming Mode to resume voltage regulation. This paper proposes an improved control strategy that integrates voltage feedforward reactive power support and virtual capacitor-based virtual inertia using Active Disturbance Rejection Control, a robust, model-independent controller, which rapidly rejects disturbances by regulating d and q-axes currents. To test the practicality of the proposed system, real-time implementation is carried out using the OPAL-RT OP4610 platform, and the results are experimentally validated. The results demonstrate improved fault current limitation and enhanced DC link voltage stability compared to a conventional PI controller, validating the system’s robust Fault Ride-Through performance under ultra-weak grid conditions. Full article

This paper presents a comprehensive review of High-Voltage Direct-Current (HVDC) systems, focusing on their technological evolution, fault characteristics, and advanced signal processing techniques for fault detection. The paper traces the development of HVDC links globally, highlighting the transition from mercury-arc valves to Insulated Gate Bipolar Transistor (IGBT)-based converters and showcasing operational projects in technologically advanced countries. A detailed comparison of converter technologies including line-commutated converters (LCCs), Voltage-Source Converters (VSCs), and Modular Multilevel Converters (MMCs) and pole configurations (monopolar, bipolar, homopolar, and MMC) is provided. The paper categorizes HVDC faults into AC, converter, and DC types, focusing on their primary locations and fault characteristics. Signal processing methods, including time-domain, frequency-domain, and time–frequency-domain approaches, are systematically compared, supported by relevant case studies. The review identifies critical research gaps in enhancing the reliability of fault detection, classification, and protection under diverse fault conditions, offering insights into future advancements in HVDC system resilience. Full article

A dysprosium-based metal–organic framework (MOF), namely [DyLH₂O]_n (1) (H₃L = 4-((bis(carboxymethyl) amino)methyl)benzoic acid), was successfully synthesized via the hydrothermal method. According to the structural characterization, metal centers in this complex are linked by four bridges (two oxygens and two carboxylic groups), leading to Dy₂ units. On further connection by single carboxylic groups, the dimeric units extend to form a two-dimensional layer with a 4⁴ topological structure. Finally, the 2D layers were assembled into a 3D framework by the L⁻³ anions. A thermogravimetric test shows that [DyLH₂O]_n can maintain high thermal stability after losing water, until the temperature reaches 426 °C. Magnetic studies on 1 reveal antiferromagnetic exchange interactions of Dy³⁺…Dy³⁺ at low temperatures. Additionally, frequency-dependent out-of-phase signals were observed in alternating current (ac) magnetic susceptibility measurements for 1, indicating that it has slow magnetic relaxation features. Full article

Severe acute respiratory symptom coronavirus 2 (SARS-CoV-2) infection occurs via the attachment of the spike (S) protein’s receptor binding domain (RBD) to human ACE2 (hACE2). Natural polymorphisms in hACE2, particularly at the interface, may alter RBD–hACE2 interactions, potentially affecting viral infectivity across populations. This study identified the effects of six naturally occurring hACE2 polymorphisms with high allele frequency in the African population (S19P, K26R, M82I, K341R, N546D and D597Q) on the interaction with the S protein RBD of the BA.4/5 Omicron sub-lineage through post-molecular dynamics (MD), inter-protein interaction and dynamic residue network (DRN) analyses. Inter-protein interaction analysis suggested that the K26R variation, with the highest interactions, aligns with reports of enhanced RBD binding and increased SARS-CoV-2 susceptibility. Conversely, S19P, showing the fewest interactions and largest inter-protein distances, agrees with studies indicating it hinders RBD binding. The hACE2 M82I substitution destabilized RBD–hACE2 interactions, reducing contact frequency from 92 (WT) to 27. The K341R hACE2 variant, located distally, had allosteric effects that increased RBD–hACE2 contacts compared to WThACE2. This polymorphism has been linked to enhanced affinity for Alpha, Beta and Delta lineages. DRN analyses revealed that hACE2 polymorphisms may alter the interaction networks, especially in key residues involved in enzyme activity and RBD binding. Notably, S19P may weaken hACE2–RBD interactions, while M82I showed reduced centrality of zinc and chloride-coordinating residues, hinting at impaired communication pathways. Overall, our findings show that hACE2 polymorphisms affect S BA.4/5 RBD stability and modulate spike RBD–hACE2 interactions, potentially influencing SARS-CoV-2 infectivity—key insights for vaccine and therapeutic development. Full article

A fuzzy cascaded PI−PD (FCPIPD) controller is proposed in this paper to optimize load frequency control (LFC) in the linked electrical network. The FCPIPD controller is composed of fuzzy logic, proportional integral, and proportional derivative with filtered derivative mode controllers. Utilizing renewable energy sources (RESs), a dual-area hybrid AC/DC electrical network is used, and the FCPIPD controller gains are designed via secretary bird optimization algorithm (SBOA) with aid of a novel objective function. Unlike the conventional objective functions, the proposed objective function is able to specify the desired LFCs response. Under different load disturbance situations, a comparison study is conducted to compare the performance of the SBOA-based FCPIPD controller with the one-to-one (OOBO)-based FCPIPD controller and the earlier LFC controllers published in the literature. The simulation’s outcomes demonstrate that the SBOA-FCPIPD controller outperforms the existing LFC controllers. For instance, in the case of variable load change and variable RESs profile, the SBOA-FCPIPD controller has the best integral time absolute error (ITAE) value. The SBOA-FCPIPD controller’s ITAE value is 0.5101, while sine cosine adopted an improved equilibrium optimization algorithm-based adaptive type 2 fuzzy PID controller and obtained 4.3142. Furthermore, the work is expanded to include electric vehicle (EV), high voltage direct current (HVDC), generation rate constraint (GRC), governor dead band (GDB), and communication time delay (CTD). The result showed that the SBOA-FCPIPD controller performs well when these components are equipped to the system with/without reset its gains. Also, the work is expanded to include a four-area microgrid system (MGS), and the SBOA-FCPIPD controller excelled the SBOA-CPIPD and SBOAPID controllers. Finally, the SBOA-FCPIPD controller showed its superiority against various controllers for the two-area conventionally linked electrical network. Full article