Search Results (999)

The increasing integration of nonlinear loads in modern power systems has made harmonic pollution a critical challenge to the operational safety of power cables. This study develops a frequency-dependent high-voltage cable system model using the ATP-EMTP (Alternative Transients Program-Electro Magnetic Transient Program) electromagnetic transient simulation platform, systematically investigating the amplification mechanisms and propagation characteristics of grounding currents under multi-type harmonic disturbances. A frequency-dependent parameter correction model is established by integrating the conductor skin effect and the dielectric relaxation properties of the insulation layers. This model incorporates the multi-structure combination among conductors, insulation, and metallic screen. It effectively overcomes the limitations of conventional lumped-parameter models in higher frequency harmonic analysis. Key findings are as follows: (1) The combined influence of harmonic frequency and amplitude leads to a grounding current amplification of up to 445 times (at 1950 Hz with 30% distortion level). Notably, current-source excitation produces significantly greater amplification than voltage-source excitation. (2) The distributed capacitance of long-distance cables (>8 km) exacerbates resonance risks within specific frequency bands (750–1250 Hz), resulting in a maximum harmonic amplification factor of 34.73 (observed for the 17th harmonic in a 15 km cable). (3) The contribution of voltage-source harmonics diminishes to less than 5% of the total current at high frequencies (≥1250 Hz), indicating a pattern of current-dominated harmonic superposition. Full article

To address the problem whereby traditional model predictive control suffers from mismatches between the model and actual parameters due to system parameter variations in the capacitor voltage-balancing control of a neutral-point-clamped (NPC) five-level inverter, an improved model-free predictive control strategy based on particle swarm optimization and the deadbeat principle is proposed. Firstly, an ultra-local model of the inverter is established, and a particle swarm optimization algorithm with an adaptive inertia coefficient is employed to self-tune the control gain of the ultra-local model, thereby reducing current control error. Secondly, the electrical angle of the reference voltage is calculated using the deadbeat principle, and a simplified vector set is constructed for voltage vector traversal. Control is applied only to the capacitor with the largest voltage deviation from the balance value, which reduces computational burden while achieving current tracking and capacitor voltage balancing. Finally, the simulation results show that under steady-state conditions, the output current total harmonic distortion (THD) is 0.28%, and the DC-side capacitor voltage fluctuation is 0.01%, demonstrating a significant improvement in control performance compared with the extremum-seeking control and Kalman filtering methods. Under transient conditions, the proposed control strategy achieves a response time of 0.7 ms while maintaining good control performance and strong robustness. These results verify the effectiveness of the proposed control strategy. Full article

To mitigate environmental impact, specifically the CO₂ emissions associated with conventional thermal and nuclear facilities, renewable energy sources are increasingly being adopted as primary alternatives. However, integrating these renewable sources into the utility grid poses a significant challenge, primarily due to the stochastic and nonlinear nature of weather. Consequently, it is imperative that power systems operate under an intelligent control model to ensure energy output meets strict power quality standards. In this context, accurate forecasting is a cornerstone of smart power management, particularly in off-grid architectures, where predicting Power Quality Parameters (PQPs) is fundamental for system optimization and error correction. This study conducts a comprehensive comparative evaluation of nine different predictive architectures for estimating PQPs. The algorithms analyzed include $LSTM$, $GRU$, $DNN$, $CNN1D\text{-}LSTM$, $BiLSTM$, attention mechanisms, $DT$, $SVM$, and $XGBoost$. The central objective is to develop a reliable basis for the automated regulation and enhancement of electrical quality in isolated systems. The specific parameters investigated are power voltage (U), Voltage Total Harmonic Distortion ($TH{D}_u$), Current Total Harmonic Distortion ($TH{D}_i$), and short-term flicker severity ($P_{st}$). Data for this investigation were acquired from an experimental off-grid setup at VSB-Technical University of Ostrava (VSB-TUO), Czech Republic. To assess model performance, we utilized root mean square error ($RMSE$) as the primary accuracy metric, while simultaneously evaluating computational efficiency in terms of processing speed and memory consumption during testing. Full article

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

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

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

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

The integration of photovoltaic (PV) generation with bidirectional electric vehicle (EV) fast-charging systems offers a promising pathway toward sustainable transportation and grid support. However, the dynamic coupling between maximum power point tracking (MPPT) perturbations and grid-side power quality presents a fundamental challenge in such multi-converter architectures. This paper addresses this challenge through a coordinated design and optimization framework for a grid-connected, PV-assisted bidirectional off-board EV fast charger. The system integrates a 184.695 kW PV array via a DC-DC boost converter, a common DC link, a three-phase bidirectional active front-end rectifier with an LCL filter, and a four-phase interleaved bidirectional DC-DC converter for the EV battery interface. A comparative evaluation of three MPPT algorithms establishes the Fuzzy Logic Variable Step-Size Perturb & Observe (Fuzzy VSS-P&O) as the optimal strategy, achieving 99.7% tracking efficiency with 46 μs settling time. However, initial integration of this high-performance MPPT reveals system-level harmonic distortion, with grid current total harmonic distortion (THD) reaching 4.02% during charging. To resolve this coupling, an Artificial Bee Colony (ABC) metaheuristic algorithm performs coordinated optimization of all critical PI controller gains. The optimized system reduces grid current THD to 1.40% during charging, improves DC-link transient response by 43%, and enhances Phase-Locked Loop (PLL) synchronization accuracy. Comprehensive validation confirms robust bidirectional operation with seamless mode transitions and compliant power quality. The results demonstrate that system-wide intelligent optimization is essential for reconciling advanced energy harvesting with stringent grid requirements in next-generation EV fast-charging infrastructure. Full article

This paper presents a systematic experimental comparison of three sliding-mode-based current control strategies—traditional sliding mode control (SMC), fast terminal sliding mode control (FTSMC), and super-twisting sliding mode control (STSMC)—applied to a grid-connected five-level active neutral point clamped flying capacitor (5L-ANPC-FC) inverter. Unlike existing studies that typically investigate a single controller or topology, this work provides a fair, hardware-validated benchmark under identical operating conditions, enabling a clear assessment of convergence speed, harmonic performance, robustness, and implementation complexity. All controllers are designed within a unified framework and their stability is rigorously analyzed using Lyapunov theory. Experimental evaluations are conducted under steady-state operation, step changes in reference current, grid-voltage sag/swell, and DC-link voltage variations. The results demonstrate that while all three controllers ensure robust current tracking and inherent DC-side capacitor voltage balancing without additional control loops, FTSMC achieves the lowest grid-current total harmonic distortion (THD) and fastest convergence. STSMC effectively suppresses chattering, and traditional SMC offers a simple yet reliable baseline solution. The presented findings provide practical design guidelines for selecting appropriate sliding-mode controllers in high-performance multilevel inverter applications. Among the assessed control techniques, FTSMC has the most rapid dynamic response, characterized by a rise time of 0.1 ms and a minimal grid-current THD of 1.95%, indicating exceptional steady-state and transient performance. STSMC markedly diminishes chattering and ripple, attaining a THD of 2.04% with enhanced waveform smoothness relative to traditional SMC. Conversely, traditional SMC offers a more straightforward implementation but demonstrates elevated ripple and THD levels of around 2.29%, along with a peak current inaccuracy of 6–8%. The results underscore the trade-offs between implementation simplicity, dynamic responsiveness, and harmonic performance of the evaluated control techniques. Full article