Search Results (8,691)

While direct current (DC) ice-melting is currently adopted for some transmission lines, its application to 10 kV distribution transformers—often located in remote and rugged terrain—presents significant operational challenges. Disconnecting these transformers prior to ice-melting is a complex procedure that incurs substantial labor, material, and financial costs. Leaving transformers connected risks DC current flowing into idle windings, potentially causing damage. Furthermore, existing mobile DC ice-melting power supplies are bulky and impose stringent transportation requirements, rendering them unsuitable for use on mountain roads. To overcome these limitations, this paper proposes a compact, lightweight variable-frequency ice-melting device. The operating principle and output characteristics of the variable-frequency method are investigated in detail. Using Simulink, system modeling and simulation analyses are performed to obtain the voltage and current output characteristics, along with harmonic spectra. Simulation results demonstrate that the proposed device achieves significant miniaturization compared with conventional solutions: within the typical parameter range of conventional devices, the volume can be reduced by 44–58% and the weight by 43–52%. In addition, the selected LC filter parameters (L = 10.39 mH, C = 86.62 μF) represent an optimized compromise solution that effectively suppresses input harmonics while maintaining the output current total harmonic distortion (THD) within an acceptable limit of 3.6%. Experimental results further validate the feasibility of the variable-frequency ice-melting current. Based on a matrix converter topology, the proposed device enables flexible adjustment of the output melting voltage and frequency, exhibits excellent low-frequency performance and dynamic response, and maintains low output harmonic content—fully meeting the application requirements for variable-frequency ice-melting. The key novelty lies in a compact matrix-converter-based de-icing device with systematic low-frequency performance analysis, offering superior portability and adaptability over traditional DC solutions. Full article

High-temperature proton exchange membrane fuel cells (HT-PEMFCs) coupled with methanol reforming hold promise for distributed energy systems, yet channel hydrodynamics and geometry optimization remain underexplored. This study develops a 3D multiphysics model to investigate coupled behaviors in HT-PEMFCs fueled by methanol reformate. Results reveal bifurcation-induced Dean vortices have dual effects: they cause flow maldistribution (15–18% velocity deviation) and contribute 50% of inlet pressure loss, while generating a lateral pumping effect that enhances local mass transfer. A continuous parametric sweep of channel widths (0.9–1.9 mm) identifies a voltage-dependent performance crossover—narrower channels (1.3 mm) excel at high voltages by improving electronic conduction, whereas wider channels (1.5 mm) perform better at low voltages by mitigating mass transfer limitations. These findings provide quantitative design criteria for optimizing flow field geometry in HT-PEMFC stacks. Full article

Transformers are key devices in the new electricity system, and the entire life cycle is associated with a considerable resource consumption and carbon footprint (CF). Understanding CF is essential for accelerating the low-carbon transition of the industry. Therefore, a systematic CF model for transformers is constructed in this study based on life cycle assessment (LCA). The results indicate that the operation stage is the overwhelmingly dominant phase for CF of transformer, with electricity acting as the main carbon source. The CF at the raw-material stage mainly originates from steel and copper. Through analysis, eight key impact factors were identified, leading to the formulation of three-dimensional carbon reduction pathways. It was observed that a 10% reduction in total losses of a transformer results in an approximate 10% decline in CF. At the same time, the transition of the electricity grid to clean energy helps reduce CF during operation. In addition, the effectiveness of a multi-factor carbon reduction pathway was examined. The results showed that, under this integrated pathway, the CF across all transformer rated voltages could be reduced by 9.75%. Based on this, a system pathway centered on enhancing operational energy efficiency is proposed, supported by green materials and processes, and coordinated through smart operation and maintenance, and circular recycling. This provides quantitative evidence and decision support for the green transition of transformers, contributing to the broader goals of sustainability development in electricity system. Full article

This paper presents a 2-GS/s voltage–time hybrid pipelined analog-to-digital converter (ADC) with a 14-bit digital output, implemented in a 28-nm CMOS process. To alleviate the gain–bandwidth–power trade-off in deeply scaled technologies, the proposed architecture employs a SHA-less front-end and a low-gain inverter-based push–pull RA for energy-efficient coarse quantization. The residue is then transferred to the time domain via a highly linear constant-current voltage-to-time converter (CC-VTC) and digitized by a four-channel time-interleaved gated-ring-oscillator (GRO) TDC. To recover dynamic linearity degraded by low-gain amplification and interleaving mismatches, a multiplier-less digital background calibration engine is implemented. Leveraging mean absolute value (MAV) statistics and dither-injected least-mean-squares (LMS) algorithms, it effectively compensates for inter-channel and interstage errors with minimal hardware overhead. The prototype occupies an active area of 0.16 mm². At 2 GS/s, the ADC achieves a Nyquist SNDR of 63.42 dB and an SFDR of 73.71 dB, corresponding to an ENOB of 10.24 bits. Consuming 86.9 mW from a 1-V supply, it achieves a Walden FoM of 35.9 fJ/conv.-step. Measurement results from multiple chips under a wide range of operating conditions verify the robustness of the proposed ADC. Full article

This paper presents a lightweight method for assessing the resilience of power distribution systems that integrates climate and infrastructure data through impact chains and a probabilistic approach, while minimizing data integration and implementation complexity. The method is demonstrated for heatwave hazards by combining network characteristics, failure probabilities of heat-sensitive components (e.g., medium-voltage cable joints), and location-specific climate projections to generate spatial maps of failure risk and network resilience. These maps support the identification and prioritization of critical components requiring intervention. Critical segments are then further analyzed using probabilistic resilience metrics to compare alternative adaptation strategies. Overall, this work contributes a practically applicable, low-complexity methodology for identifying the weakest portions of distribution networks, along with a more in-depth probabilistic approach for assessing their climate resilience. The com-prehensive framework is illustrated through a case study of a representative portion of the Italian electricity distribution system in the urban area of Rome. It is implemented in a test environment that reflects realistic distribution network data structures and automatically integrates climate data from established online repositories. Full article

The accelerated low-carbon transition of power systems and the widespread integration of Electric Vehicles (EVs) present both severe operational challenges and substantial flexible regulation potential for Active Distribution Networks (ADNs). This paper provides an integrative review of the coordinated control and multi-market bidding mechanisms for EV-centric Technical Virtual Power Plants (TVPPs). Moving beyond descriptive surveys, this review systematically synthesizes the fragmented literature across three critical dimensions: (1) the physical-economic bidirectional mapping, which considers nonlinear power flow constraints and node voltage limits within the TVPP framework; (2) multi-market coupling mechanisms, evolving from unilateral energy bidding to coordinated participation in carbon trading and ancillary services; and (3) real-time control strategies, critically evaluating the trade-offs between optimization techniques (e.g., Model Predictive Control) and cutting-edge artificial intelligence approaches (e.g., Deep Reinforcement Learning) in mitigating battery degradation. Furthermore, a transparent review methodology is adopted to ensure literature rigor. By explicitly outlining the boundaries between TVPPs, Commercial VPPs (CVPPs), and EV aggregators, this paper identifies core unresolved trade-offs among aggregation fidelity, market complexity, and communication latency, providing evidence-backed pathways for future engineering demonstrations and V2G applications. Full article

Background/Objectives: Electroanatomic mapping (EAM) provides high-resolution spatial and electrogram information, but the prognostic utility of quantitative EAM features has not been systematically evaluated with contemporary artificial intelligence (AI) methods. We investigated whether an AI analysis of quantitative EAM exports from the CARTO system enhances the prediction of major arrhythmic events (MAEs). Methods: In this retrospective, multicenter cohort study, 248 consecutive patients undergoing left ventricular EAM at four tertiary electrophysiology centers were analyzed. Numerical EAM descriptors (spatial coordinates, unipolar/bipolar voltages, local activation time, impedance) were transformed into derived metrics, including local activation heterogeneity (GR), late-potential extent (LAT), bipolar–unipolar discrepancy (VLT), and low-amplitude scar extent (Scar Areas), and were spatially normalized via spherical projection. Clinical, anamnestic, and imaging variables were integrated. Machine learning and deep learning models were trained with an 80:20 train/test split and evaluated using three-fold cross-validation. Performance metrics included area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision. Results: Models incorporating both clinical and AI-processed EAM features achieved high discriminatory performance (test AUC up to 0.92; accuracy up to 0.896). Specificity was consistently high (≈0.97–0.998), whereas sensitivity remained modest (≈0.39–0.58). Among the EAM-derived features, GR was the most consistently informative predictor across algorithms and analyses; VLT, LAT, and Scar Areas also contributed substantially. Regionally, basal sub-mitral, subaortic, and posterolateral basal-to-mid zones exhibited the strongest associations with MAEs. Conclusions: AI-driven quantitative analysis of left ventricular EAM exports augments risk stratification for MAEs beyond conventional clinical and binary EAM descriptors. Reflecting local conduction heterogeneity, GR emerged as the dominant EAM predictor. Prospective validation in larger, disease-specific cohorts and real-time integration within EAM platforms are warranted. Full article

Background/Objectives: Transcatheter ablation assisted by three-dimensional (3D) electroanatomical mapping (EAM) is the elective treatment for atrioventricular nodal reentrant tachycardia (AVNRT) in children and adolescents. In this population of patients, the most frequently employed EAM strategies are the low-voltage bridge (LVB) strategy and sinus rhythm propagation mapping (SRPM). However, the exact pathophysiology and anatomy of the AVNRT reentrant circuits are still poorly understood. The aim of this study was to investigate the relationship between SRPM and LVB and to shed light on nodal physiology in children and adolescents affected by AVNRT. Methods: We retrospectively collected data on pediatric patients who underwent cryoablation for AVNRT assisted by high-density 3D EAM by using the LVB strategy; maps were reviewed by two independent electrophysiologists and the SRPM was described. SRPM was defined as typical when only one collision area was identified and atypical whenever either no or ≥ two collision areas were localized. Results: Twenty-eight consecutive patients (11.3 ± 3.3 years) were enrolled. All procedures were acutely successful. Overall, atypical SRPM was present in 10 patients (35.7%), and it did not correlate with the presence of multiple SPs or electrophysiological data. Moreover, we observed an imperfect concordance between SRPM and LVB (only in 10/18 patients). When SRPM and LVB were assessed in different locations, the LVB identified the effective cryoablation site in more cases than SRPM (4/8 vs. 1/8). Lastly, in cases of double collision, one collision area co-localized with the LVB and the effective cryoablation spot, whereas the other was located superiorly, closer to the His bundle. Conclusions: Atypical sinus rhythm propagation in the Koch’s triangle is a frequent finding in pediatric AVNRT patients. In this series, LVB showed closer concordance with the successful cryolesion site than retrospectively reconstructed SRPM. Full article

This paper proposes a non-overlapping planar cross-arranged ultra-wideband shared-aperture base station antenna array targeting the 2 to 6 GHz application bandwidth. The low-frequency module (double-layer parasitic coupling) and the high-frequency module (chamfered slotted patch) are independently designed, and metal baffles are introduced around the antenna elements to reshape the boundary conditions and physically block the electromagnetic coupling paths. Both simulation and experimental results demonstrate that the fabricated prototype successfully exceeds the targeted 2–6 GHz spectrum, achieving an actual continuous coverage from 1.84 to 6.3 GHz. Specifically, the antenna achieves a gain higher than 5.9 dBi in the measured low-frequency band (1.84–3.72 GHz) and higher than 6.1 dBi in the high-frequency band (3.63–6.3 GHz), with a voltage standing wave ratio (VSWR) below 2 across the entire band. The metal baffles successfully correct the high-frequency radiation pattern distortion and ensure stable directional radiation over the full operating bandwidth. This design provides an efficient, robust, and manufacturable solution for 5G offshore wind power multi-band base station antennas. Full article

The threshold voltage (Vth) of p-GaN gate enhancement-mode (E-mode) high electron mobility transistors (HEMTs) on silicon substrates grown by metal–organic chemical vapor deposition (MOCVD) is often limited to 1.0–1.5 V. Apart from the low Mg acceptor activation rate, the non-uniform vertical Mg distribution in thin p-GaN layers is also a key bottleneck limiting Vth. This work reveals that the vertical distribution (not only magnitude) of Mg doping fundamentally influences Vth by modulating the charge centroid and electric field coupling to the heterointerface. Through bis(cyclopentadienyl)magnesium (Cp₂Mg) flow modulation, surfactant-assisted growth, and growth rate adjustment, the vertical Mg doping uniformity within the 80 nm p-GaN layer was improved while effectively suppressing Mg out-diffusion. A short-cycle gate-first self-aligned process was used to fabricate the devices, and the results showed that the improved Mg vertical distribution led to a significant Vth enhancement by 0.75 V. Technology Computer-Aided Design (TCAD) simulations further demonstrated that the uniform doping profile builds a stronger negative space charge field beneath the gate, raising the energy band and increasing Vth. This work not only presents practical strategies, but also establishes a direct physical link between vertical Mg doping distribution and Vth in Si-based E-mode HEMTs. Full article

This paper presents a novel voltage differencing transconductance amplifier (VDTA)-based mixed-mode inverse filter capable of operating in voltage mode, transadmittance mode, transimpedance mode, and current mode using a single topology. The proposed configuration employs only three VDTAs with two resistors and three capacitors, offering low component count, high input/output impedance flexibility, and no requirement for component matching. It simultaneously realizes first-order inverse lowpass and highpass, as well as second-order inverse bandpass responses. A comprehensive non-ideal analysis, which includes the effects of VDTA parasitic impedances, determines the practical operating frequency range. The design is validated through PSPICE simulations using 0.18 μm CMOS technology, showing close alignment between theoretical predictions and simulation results, with cutoff frequencies of approximately 1.60 MHz and low power consumption of 0.972 mW. Further analyses confirm orthogonal tuning capability, acceptable temperature stability, and robustness against component tolerances. In a practical application, the proposed inverse filter is employed to implement a mixed-mode PID controller, which significantly improves transient response characteristics by reducing rise time, settling time, and steady-state error. These findings highlight the effectiveness and versatility of the proposed design for analog signal processing and control system applications. Full article

High-voltage bushings, the fault-prone key electrical components of transformers, are critical for real-time and high-accuracy fault monitoring and management. Intelligent fault detection via infrared images is plagued by low classification accuracy due to massive interference from similar tubular objects and small target characteristics. This study proposes a lightweight deep learning model, MTrip–YOLO, an improved YOLO11n integrated with Mamba-2 (Structured State Space Duality, SSD) and Triplet Attention, to achieve efficient fault monitoring in complex backgrounds. The training and validation dataset comprises open-source images, on-site data from a substation, and field-collected infrared images, categorized into four types: normal bushings, poor contact, oil shortage, and high dielectric loss faults. Mamba-2 captures the long-range global context of infrared features with its linear-complexity long-range modeling capability to enhance feature extraction, while Triplet Attention suppresses complex background radiation noise through cross-dimensional interaction without dimensionality reduction, enabling the model to focus on small targets and accurately classify bushings from morphologically similar strip-shaped objects. Experimental results show that MTrip–YOLO achieves a top mAP50 of 91.6% and a minimal parameter count of 1.9 M, outperforming Faster R-CNN, RT-DETR, and YOLO26n across all evaluated metrics and being potentially suitable for edge deployment on UAV-mounted or handheld infrared platforms, pending hardware validation on embedded computing devices. Ablation experiments verify the independent contributions of Mamba-2 (0.8027% mAP50 improvement) and Triplet Attention (0.89327% mAP50 improvement), with a synergistic effect from their combination. MTrip–YOLO provides a potential edge-deployable solution for high-voltage bushing fault monitoring, offering important application value for the intelligent operation and maintenance of substations. Full article

Background/Objectives: Pulmonary vein isolation (PVI) is the gold standard for atrial fibrillation (AF) ablation. Recently, a randomized study showed that adding voltage-guided ablation (VGA) in persistent AF cases was beneficial. The aim of the present study was to evaluate the safety, efficacy and predictors of success of redo procedures after VGA in an exclusively persistent AF cohort. Methods: Data are derived from the prospective Erfurt AF ablation registry. Starting in 2015, ablation procedures were performed using CARTO3D and VGA. Patients receiving their first redo procedure between 01/2015 and 08/2022 were included. Follow-up included 72 h Holter ECG or device interrogation, ECG, symptom-triggered event recording, and questioning at 3 and 12 months after the redo procedure. The primary endpoint was freedom of recurrence of AF or atrial tachycardia (AT) without drugs between 3 and 12 months. Results: Altogether, 683 patients received a first VGA between January 2015 and May 2022, and 77 patients had their first redo procedure occurring 20 ± 17 months after the first procedure. During the first redo procedure, reconnected PVs were found in 44%, reconnected lines in 23% and new or progressive LVZs in 57% of patients. Complications occurred in two patients (2.6%). During follow-up one patient died, and one did not participate due to aphasia. It was found that 69% were free of recurrence and 61% were free of recurrence off drugs. Patients with recurrence were older than those without recurrence off drugs (73 ± 6 versus 69 ± 9 years, p = 0.049). Conclusions: Redo procedures after VGA in persistent AF have comparatively good results; although, many patients have progressive fibrosis. Full article

Direct urea–hydrogen peroxide fuel cells (DUHPFCs) are promising for sustainable power generation, but their performance is governed by highly nonlinear material and operating interactions. This study develops a machine-learning framework employing a multi-output artificial neural network (ANN) to predict cell voltage, power density (PD), and substrate-based energy efficiency (SEE) of DUHPFCs. The ANN exhibits excellent predictive accuracy, achieving coefficients of determination (R²) above 0.995 and normalized root mean square errors (NRMSE) below 1.75 × 10⁻² for all outputs. Model interpretability is enhanced by using Shapley additive explanations and partial dependence plots, which identify current density as the dominant factor affecting DUHPFC performance, followed by temperature and anolyte composition. The ANN is coupled with a multi-objective Pareto-search algorithm optimization (PAO) to resolve the trade-offs among competing performance metrics. Under different optimization objectives, a DUHPFC with an Ni_0.2Co_0.8/Ni-foam anode is predicted to achieve a maximum PD of 45.6 mW/cm² with a low SEE of 2.6% or a maximum SEE of 15.2% with a moderate PD of 40.9 mW/cm². Additionally, a balanced operating regime is identified, achieving a PD of 43.1 mW/cm² and an SEE of 13.9%. Overall, the proposed framework provides an effective decision-support tool for optimizing DUHPFC performance under competing objectives. Full article

The increase in utility-scale PV generation and the displacement of synchronous machines reduce system strength, reactive power headroom, voltage resilience, and overall power system stability, motivating a robust comparison of various mitigation technologies beyond static load-flow or PV assessments. RMS time-domain simulations are performed for balanced and unbalanced contingencies, and performance is quantified using post-fault voltage dip depth, undervoltage area (V < 0.9 pu.), recovery time to nominal, and RoCoF. These metrics are aggregated into a single weighted composite severity score, which is then normalised to the baseline to form the dynamic voltage resilience index (DVRI) and the Frequency Disturbance Relative Index (FDRI). The results show that the converter-based reactive power support devices deliver the fastest and most controllable post-fault voltage restoration, with the STATCOM achieving the lowest composite penalty and best DVRI under severe fault conditions but the poorest FDRI during PV plant trip/reconnection events. The synchronous condenser (SC) improves post-fault recovery through excitation driven reactive capability and increased short-circuit contribution, but its recovery to nominal voltage levels is slower and can produce negative-sequence current under unbalanced fault conditions whilst producing the smallest frequency disturbance and best FDRI. The SVC provides effective steady-state regulation but becomes less effective during extremely low voltages due to the voltage-dependent reactive power output, and its FDRI remains close to baseline. The BESS-GFM is dependent on the inverter current limits and the control priorities, which influence both voltage recovery and response times, achieving an FDRI scoring second to the SC. These metrics are combined into baseline normalised composite indices (DVRI and FDRI) using explicitly dimensionless sub-metrics (dip magnitude, exposure area, and recovery delay for voltage and deviation magnitude, windowed RoCoF, and exposure for frequency). Equal weights are used as a neutral baseline, and a weight sensitivity study is included to confirm that technology rankings are robust to plausible variations in weighting choice. Full article