Search Results (1,673)

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

Extreme fast charging (XFC) infrastructure is becoming increasingly necessary as the number of electric vehicles continues to grow. However, deploying such stations introduces several challenges related to power quality and compliance with regulatory standards. This work presents an alternative XFC station designed for charging multiple vehicles while ensuring low harmonic distortion in the grid currents, without the need for sinusoidal filters, by employing the Zero Harmonic Distortion (ZHD) converter. The proposed system offers galvanic isolation for each charging interface and supports additional functionalities, including the integration of Distributed Energy Resources (DERs) and the provision of ancillary services. These features are enabled through the combination of a bidirectional grid-connected active front-end operating at low switching frequency with high-frequency silicon carbide (SiC)-based dc/dc converters on the vehicle side. Hardware-in-the-loop (HIL) simulation results demonstrate a total demand distortion (TDD) of 1.12% for charging scenarios involving both 400 V and 800 V battery systems, remaining within the limits specified by IEEE 519-2022. Full article

In this paper, we study the Ricci-harmonic flow under the assumption that the scalar curvature is bounded. First, we establish a time-derivative bound for solutions to the heat equation along the flow. Based on this estimate, we derive a short-time distance-distortion estimate and prove the existence of suitable cutoff functions. Using these results, we obtain Gaussian-type upper and lower bounds for the heat kernel along the Ricci-harmonic flow. Our results generalize the previous work of Bamler–Zhang on Ricci flow to the Ricci-harmonic flow setting, and can be used to study the regularity theory of Ricci-harmonic flow. Full article

Harmonic distortion in power systems, primarily caused by nonlinear loads, leads to significant power quality issues such as increased losses, reduced power factor, and equipment malfunctions. To mitigate these effects, passive power filters (PPFs) are widely employed due to their cost-effectiveness and simplicity. This paper presents an optimized design of a single-tuned passive filter (STPF) using the Firefly Algorithm (FFA) and its multi-objective extension, the Multi-Objective Firefly Algorithm (MOFA). The optimization aims to minimize both voltage total harmonic distortion (VTHD) and power loss and to maximize the power factor (PF) while complying with IEEE 519-2014 standards. The study evaluates the proposed method under two different industrial case studies with varying system parameters and harmonic profiles. Simulation results demonstrate that the proposed FFA-based optimization outperforms the Mixed Integer Distributed Ant Colony Optimization (MIDACO) method, achieving superior VTHD reduction, power loss minimization, and power factor enhancement. The MOFA approach provides a Pareto-optimal front, offering trade-offs among competing objectives. Comparative analysis confirms the efficiency, robustness, and faster convergence of FFA-based optimization, making it a promising approach for optimal filter design in power systems. Full article

Regarding the problems of fifth and seventh order characteristic harmonics existing in the operation of the dual three-phase permanent magnet synchronous motor, repetitive control is often used to improve the steady-state accuracy. However, traditional RC mostly adopts a fixed forward-learning gain and is set through trial-and-error methods, which requires a lot of time. Therefore, this paper proposes an improved repetitive control strategy based on fuzzy dynamic gain scheduling. This strategy precisely extracts the comprehensive distortion characteristic values of the target suppressed harmonics and the warning harmonics online; it designs a fuzzy adaptive adjustment mechanism to actively increase the gain to achieve rapid suppression when the target harmonic is severe, and rapidly reduce the gain to ensure the safety of operation when a low-frequency oscillation trend is detected. Simulation results show that the proposed method effectively reduces the total harmonic distortion of the current while maintaining the stability of the system and improves the harmonic suppression accuracy. Full article

Quasi-single-stage AC/DC converters offer the advantages of fewer power devices, simplified control, and high power density in single-phase front-end applications. This paper presents a novel quasi-single-stage AC/DC topology employing magnetically integrated differential-mode coupled inductors to address the low power factor and large input current harmonics commonly observed in conventional single-phase quasi-single-stage converters. In addition, a burst mode switch is introduced to widen the operating range of the converter by regulating the DC link voltage under light-load conditions. The operating principles and power flow of the proposed converter in both normal and burst modes are analyzed, and the operating modes and equivalent circuit of the front-end power factor correction stage are discussed in detail. A 400 W experimental prototype is built to verify the feasibility of the proposed circuit. Under a 220 V AC input at full load, the prototype achieves a measured efficiency of 91.9%, a power factor greater than 0.99, and low input current total harmonic distortion. These results demonstrate that the proposed quasi-single-stage AC/DC converter can achieve high power factor and high efficiency with reduced component count and improved electromagnetic interference characteristics. Full article

This study investigates the primary electromagnetic sources of acoustic noise in single-phase induction motors and proposes design-oriented strategies for noise reduction. A 370 W, four-pole, 80-frame single-phase induction motor was designed, analyzed, and experimentally validated. Finite Element Method (FEM) simulations were conducted using Ansys Maxwell 2D to examine the effects of magnetic field distortion, magnetic saturation, and rotor eccentricity on torque ripple and inductance variation. The results demonstrate that these factors significantly increase electromagnetic force harmonics acting on the stator teeth and frame, leading to vibration and acoustic noise generation. In addition, inductance fluctuations caused by interphase magnetic coupling and air-gap harmonics were found to increase current harmonic content and potentially excite structural resonances. The influence of capacitor selection and winding configuration on magnetic saturation, phase displacement, and torque ripple was systematically evaluated. Prototype motors were manufactured and acoustic noise measurements were performed to experimentally validate the simulation results. Unlike previous studies that often investigate these parameters separately, this work presents a coupled analysis that explicitly links capacitor selection, winding configuration, and rotor eccentricity to inductance variation, torque ripple, and acoustic noise generation. The findings provide practical design guidelines for the development of low-noise single-phase induction motors and contribute to reducing electromagnetic vibration and acoustic emissions in electric machine design. Full article

The i_p-i_q harmonic detection method, which is based on instantaneous reactive power theory, involves cumbersome and complex computations. In addition, the adoption of a low-pass filter (LPF) degrades the dynamic response performance of harmonic detection. To achieve accurate and fast detection of grid harmonic currents for efficient power grid compensation, this paper proposes a total current harmonic detection method using a dual second-order generalized integrator (DSOGI). This method eliminates the calculation steps of the active and reactive components of load current that are required in the conventional i_p-i_q method. More importantly, it replaces the LPF in the traditional detection scheme with a positive-sequence fundamental component extraction structure based on the DSOGI. Simulations and experimental tests are conducted on the proposed method under balanced grid conditions; the total harmonic distortion (THD) is approximately 2%, and the system stabilizes within 0.04 s. The detection speed and accuracy of the proposed method are superior to those of the traditional i_p-i_q harmonic detection method, the sinusoidal amplitude integrator (SAI)-based method, and the complex coefficient filter (CCF)-based method. Full article

This paper presents a distributed V2G-enabled multiport DC charging system with a hierarchical charging management strategy. Unlike conventional architectures based on centralized power converter cabinets, the proposed system distributes bidirectional power converters within individual multiport dispensers, each equipped with a local charging power management device. This architecture improves system scalability, fault tolerance, and operational flexibility while enabling vehicle-level charging and V2G services. A hierarchical control framework is introduced, consisting of high-level optimal charging scheduling, mid-level power coordination among distributed dispensers, and low-level converter control. Key elements include modular power units that can be dynamically configured and expanded, providing a cost-effective and adaptable solution for growing EV markets. Experimental results obtained from a 45 kW modular DC charging prototype demonstrate an efficiency improvement of up to 2% at rated power compared to a non-modular charger. In contrast, the optimized charging strategy achieves an overall charging cost reduction of approximately 11% and a peak load demand reduction of up to 31%. Furthermore, stable bidirectional power flow, effective power sharing, and total harmonic distortion within regulatory limits are experimentally validated during both charging and V2G operation. The prototype is implemented to validate the proposed charging system in the laboratory environment. Full article

Fast charging of electric vehicles can introduce phase-dependent harmonic distortion and voltage unbalance in low-voltage feeders, which may reduce admissible charging capacity even when voltage magnitudes remain within conventional limits. This paper proposes a phase-aware predictive scheduling framework for harmonic hosting management in feeders with a high penetration of electric vehicle charging. The proposed method formulates feeder operation as a predictive decision problem that jointly determines charging power levels, phase allocation, and the selective activation of multifunctional compensation resources under harmonic distortion, voltage unbalance, and neutral-current constraints. Unlike previous studies centered on harmonic characterization, static hosting assessment, or local converter-level mitigation, the proposed approach treats harmonic hosting as an active feeder-level network management problem. The framework is evaluated through time-series harmonic power-flow simulations using charger harmonic emission profiles and realistic feeder parameters. The numerical results indicate that coordinated phase-aware scheduling can increase admissible charging capacity, improve compliance margins for power-quality indices, and reduce mitigation efforts with respect to uncontrolled charging and non-coordinated compensation strategies. Overall, the results support the use of phase-aware scheduling as a feeder-level strategy to improve electric vehicle charging integration under harmonic and unbalanced constraints. Full article

The large-scale integration and grid connection of renewable energy sources and charging stations introduce a multitude of nonlinear and impact loads, resulting in more severe distortion and higher complexity of disturbance signals in power systems. As a consequence, power quality disturbances (PQDs) in active distribution networks, including overvoltage and harmonics, display greater randomness and diversity, which increases the challenge of PQD identification. To tackle this problem, this study presents a dual-channel early-fusion approach for PQD recognition based on Spatial Post-MultiScale Fusion Entropy (SMFE). SMFE is used as an entropy-based feature-construction pipeline in which a time–frequency representation is formed prior to spatial post-multiscale aggregation to produce a compact complexity map complementary to waveform morphology. Subsequently, a dual-channel model is constructed by integrating waveform-morphology input with SMFE-derived complexity features for joint learning. By leveraging the ConvNeXt architecture and a Squeeze-and-Excitation (SE) mechanism, a multimodal channel-recalibration model is implemented to emphasize informative feature responses during PQD recognition. Experimental verification with simulated signals shows that the proposed approach achieves an identification accuracy of 97.83% under an SNR of 30 dB, indicating robust performance under the tested noise settings. Full article

The increasing penetration of rooftop photovoltaic (RTPV) systems in low-voltage (LV) distribution networks introduces challenges such as voltage rises, reverse power flow, and reduced hosting capacity, thereby necessitating effective active power regulation (APR) in module-level micro-inverters. This paper proposes a dual-layer control framework for a 250 watt-peak (Wp) three-switch rooftop PV micro-inverter, integrating quantum-behaved particle swarm optimization with reinforcement learning (QPSO-RL) for accurate maximum power point tracking (MPPT) and a linear quadratic regulator (LQR) for reserve-aware APR. The QPSO-RL algorithm improves available-power estimation under varying irradiance, temperature, and partial-shading conditions, while the LQR-based controller ensures fast, well-damped, and grid-compliant power regulation. The proposed framework was developed and validated using MATLAB/Simulink 2024 for simulation studies and LabVIEW with NI myRIO 2022 for real-time hardware implementation. Both simulation and experimental results confirm that the proposed method achieves 99.5% MPPT accuracy, convergence within 20 ms, grid-injected current total harmonic distortion (THD) below 3%, and a near-unity power factor. In addition, the reserve-based regulation strategy improves feeder compliance and reduces converter stress, thereby supporting reliable rooftop PV integration. These results demonstrate that the proposed QPSO-RL + LQR framework offers a practical and intelligent solution for high-performance, grid-supportive rooftop PV micro-inverter applications. Full article

With the increasing penetration of converter-based devices, harmonic distortion has become a major challenge for power quality monitoring in large-scale power systems. This study presents a systematic review of methods for modeling harmonic sources and their applicability to real-time monitoring of power distribution systems. The review was conducted following PRISMA guidelines, considering literature published between 2000 and 2026. Searches were performed across Scopus, IEEE Xplore, Web of Science, ScienceDirect, and MDPI using predefined keywords. A total of 128 peer-reviewed journal articles were included. Potential sources of bias were qualitatively assessed, including selection, retrieval, and classification bias; however, residual bias may still arise from database selection, keyword design, and study classification. A structured comparative framework is introduced, based on a six-dimension coverage scoring scheme and maturity analysis, enabling consistent evaluation across both methodological and deployment aspects. The robustness of this framework was evaluated using leave-one-out and perturbation analyses, indicating low variability in coverage scores and stable rankings across both corpora. A taxonomy of harmonic source modeling approaches is proposed. Comparative synthesis indicates that measurement-based approaches, particularly those leveraging distribution-level PMUs, show strong potential for real-time monitoring. Key challenges include D-PMU placement, data integration, and computational scalability. Future work should focus on physics-informed AI and digital twin-based monitoring. Full article

Quasi-resonant (QR) flyback inverters suffer from significant performance degradation under varying thermal conditions. This is because the thermal drift of passive components’ parameters deviates the switching instants from their optimal valley points, leading to increased switching losses and higher grid current distortion. To address this challenge, we propose an online self-tuning control strategy based on a Recurrent Neural Network (RNN) designed for embedded implementation. The RNN model continuously observes a sequence of non-intrusive operational data, including input voltage, input current, and grid current, and directly predicts the optimal time-delay compensation for the valley-switching logic. This end-to-end approach eliminates the need for online parameter identification, complex physical model calculations, or dedicated thermal sensors. The proposed framework was validated through comprehensive MATLAB/Simulink simulations. The results demonstrate that when operating across a wide temperature range (e.g., from 25 °C to 85 °C), the self-tuning control scheme enhances conversion efficiency by over 3.0% and reduces the grid’s current Total Harmonic Distortion (THD) from 5.8% to below 2.0%, thereby significantly improving the inverter’s lifetime performance and reliability. Full article

Modern grids’ dual-high characteristics elevate the role of wideband impedance measurement in operational risk assessment. In thyristor-based line-commutated converter-based high-voltage direct-current (LCC-HVDC) systems, where severe waveform distortion and high harmonic content prevail, nonintrusive wideband techniques rely on precise spectral estimation. Accurate identification of harmonic parameters (frequency, amplitude, and phase) is therefore essential. This work presents a Hann-window-based three-point interpolated discrete Fourier transform (I3pDFT) for precise harmonic parameter estimation. The method suppresses long-range spectral leakage, enhances frequency resolution, and employs robust amplitude and phase estimators that are resilient to noise and negative-frequency interference. Extensive simulations across frequency deviations, noise levels, sampling rates, and record lengths show that the proposed approach outperforms two classical I3pDFT variants in accuracy while maintaining low computational loads suitable for embedded implementation. These results confirm the effectiveness and practicality of the proposed I3pDFT-Hann method for real-world harmonic measurements in LCC-HVDC systems. Full article