Search Results (74)

Non-Intrusive Load Monitoring (NILM) enables appliance-level classification from aggregate electrical measurements and supports efficient energy management in smart buildings. However, the accuracy of existing NILM methods is often limited by the inability of conventional feature extraction techniques to capture nonlinear steady-state behavior. This study proposes a novel feature extraction framework for appliance classification, which integrates phase-space reconstruction (PSR) with 2-D Fourier series to derive geometry-based descriptors of appliance current waveforms. Unlike traditional signal-processing methods, the proposed approach utilizes the nonlinear geometric structure revealed by PSR and encodes it through Fourier descriptors, offering a discriminative, low-dimensional feature space suitable for classification using supervised machine learning algorithms. The method is evaluated on the high-resolution controlled single-appliance recordings from the COOLL dataset using the K-Nearest Neighbor (KNN) classifier. Extension to aggregated multi-appliance NILM scenarios would require additional stages such as event detection and load separation. Sensitivity analysis demonstrates that classification performance depends strongly on the choice of time delay and harmonic order, with optimal settings yielding an accuracy of up to 99.52% using KNN. The results confirm that larger time delays and a small number of harmonics effectively capture appliance-specific signatures. The findings highlight the effectiveness of PSR–Fourier-based geometric features as a robust alternative to conventional NILM feature extraction strategies. Full article

With the evolution of new power systems, harmonic sources in distribution networks have become increasingly dispersed, thus requiring lower-cost harmonic mitigation devices suitable for large-scale deployment. With its simple control architecture, the one-cycle controlled active power filter (APF) is better adapted to meet the aforementioned requirements. That said, under non-ideal voltage conditions like voltage distortion or unbalance, the compensating target current of the APF that relies on traditional one-cycle control (OCC) will undergo distortion as well, resulting in a substantial reduction in the compensation effect. This paper introduces a modified OCC method based on a positive-sequence filter, which allows for the control of a reduced-switch three-phase APF. This control method eliminates the negative sequence and harmonic components in the target current of the APF, and makes the compensated current maintain a good sinusoidal waveform. A one-cycle control equation applied to the reduced-switch APF was derived. The modified one-cycle control method allows the active filter to retain a favorable compensation effect when operating under non-ideal voltage conditions. Meanwhile, it preserves the inherent advantages of traditional one-cycle control, including the elimination of a phase-locked loop (PLL), a fixed switching frequency, and a straightforward control structure. Finally, an APF simulation model and a dSPACE-based APF experimental circuit were built to verify the proposed control method. In simulation, with the adoption of the modified OCC, the THD of the current was reduced from 8.25% before improvement to 3.79% after improvement. In experiments, according to the spectrum analysis function of the oscilloscope, the third-order current harmonic caused by voltage distortion was decreased from 500 mA to 100 mA, representing a reduction of 80%. Both simulation and experimental results verify that the proposed modified one-cycle control method can effectively solve the problem that control performance is susceptible to voltage quality. Full article

In the context of power electronic interfaces in photovoltaic (PV), fuel cell, battery, and microgrid applications, the low output voltage of the DC source necessitates a voltage-boosting inverter. This paper proposes a single-source seven-level switched-capacitor boost inverter, particularly for low-voltage applications. The proposed inverter has the capability to produce seven different output voltage levels, i.e., intermediate boosted levels, with a total gain of three times the input voltage. The inverter has the advantage of a reduced number of power switches, diodes, and a switched-capacitor unit, which allows for single-stage operation without the need for a second DC-DC converter. The operating principle of the proposed inverter is explained in detail with a complete switching state analysis, conduction path analysis, and output voltage generation. The capacitor size is calculated using a charge balance-based equation. The self-balancing capability is validated for mismatched initial voltages with a bounded steady-state ripple. To evaluate the performance of the proposed inverter in a more realistic scenario, the effects of non-ideal device characteristics are considered, and the efficiency of the inverter is estimated using a loss model. A predictive current control technique is applied to control the output current under inductive load conditions. The simulation results obtained in MATLAB/Simulink software validate the proper seven-level operation of the inverter, the self-balancing capability of the capacitors, improved output waveform quality, and current control. The proposed inverter can be extended to grid-connected applications, where conventional output filters can be applied to meet the harmonic standards. Full article

In permanent magnet synchronous motor (PMSM) drive systems, the nonlinearity of the inverter and non-sinusoidal nature of back EMF generate harmonics in the stator current, resulting in torque ripple and reduced motor efficiency. Although the proportional resonant (PR) controller is widely employed for harmonic suppression, the standard resonant controller is constrained by its narrow bandwidth and can only suppress a single harmonic order. To address these issues, an adaptive harmonic suppression strategy using a proportional multi-resonant (PMR) controller based on the generalized frequency selector (GFS) is proposed. Firstly, the sources and characteristics of the stator current harmonics were analyzed based on the mathematical model of PMSM. Subsequently, a proportional resonance controller was designed according to the tracking filtering characteristics of the GFS, and a proportional multi-resonance controller targeting multi-order harmonics was constructed. The stability of the current closed-loop system under the algorithm was analyzed. Finally, simulation and experimental results demonstrated that the proposed algorithm effectively suppressed current harmonics and significantly improved the current waveform. Full article

With the large-scale integration of power electronic converters, non-linear loads, and renewable energy generation, voltage and current waveform distortion in modern power systems has become increasingly severe, making harmonic resonance amplification and non-stationary distortion more prominent. Accurate and robust harmonic-level prediction and detection have become essential foundations for power quality monitoring and operational protection. However, traditional harmonic analysis methods remain highly dependent on pre-designed time–frequency transformations and manual feature extraction. They are sensitive to noise interference and operational variations, often exhibiting performance degradation under complex operating conditions. To address these challenges, a Unified Physics-Transformer-based harmonic detection scheme is proposed to accurately forecast harmonic levels in offshore wind farms (OWFs). This framework utilizes real-world wind speed data from Bozcaada, Turkey, to drive a high-fidelity electromagnetic transient simulation, constructing a benchmark dataset without reliance on generative data expansion. The proposed model features a Feature Tokenizer to project continuous physical quantities (e.g., wind speed, active power) into high-dimensional latent spaces and employs a Multi-Head Self-Attention mechanism to explicitly capture the complex, non-linear couplings between meteorological inputs and electrical states. Crucially, a Multi-Task Learning (MTL) strategy is implemented to simultaneously regress the Total Harmonic Distortion (THD) and the characteristic 5th Harmonic (H5), effectively leveraging shared representations to improve generalization. Comparative experiments with Random Forest, LSTM, and GRU systematically evaluate the predictive performance using metrics such as root mean square error (RMSE) and mean absolute percentage error (MAPE). Results demonstrate that the Physics-Transformer significantly outperforms baseline methods in prediction accuracy, robustness to operational variations, and the ability to capture transient resonance events. This study provides a data-efficient, high-precision approach for harmonic forecasting, offering valuable insights for future renewable grid integration and stability analysis. Full article

Power supply for traction substations (TSs) of AC railways has traditionally been provided by 110–220 kV overhead transmission lines (OHL). These OHLs can be damaged during strong winds and ice formation. Furthermore, these lines generate significant electromagnetic fields (EMFs), which adversely affect maintenance personnel, the public, and the environment. Mitigating the resulting damages requires the establishment of protection zones, necessitating significant land allocation. Enhancing the reliability of power supply to traction substations and reducing EMF levels can be achieved through the use of gas-insulated lines (GIL), whose application in the power industry of many countries is continuously increasing. The aim of the research presented in this article was to develop computer models for determining the EMF of a GIL supplying a group of traction substations, taking into account actual traction loads characterized by non-sinusoidal waveforms and asymmetry. To solve this problem, an approach implemented in the Fazonord AC-DC software package, based on the use of phase coordinates, was applied. This allowed for the correct accounting of the skin effect and proximity effect in the massive current-carrying parts of the GIL, as well as the influence of asymmetry and harmonic distortions. The simulation results showed that the use of GIL brings the voltage unbalance factors at the 110 kV busbars of the traction substations within the permissible range, with the maximum values of these coefficients not exceeding 2%. The results of the harmonic distortion assessment demonstrated a significant reduction in harmonic distortion factors in the 110 kV network for the GIL compared to the OHL. The performed electromagnetic field calculations confirmed that the GIL generates magnetic field strengths one order of magnitude lower than those of the OHL. The obtained results lead to the conclusion that the use of gas-insulated lines for powering traction substations is highly effective, ensuring increased reliability, improved power quality, and a reduced negative impact of EMF on personnel, the public, the environment, and electronic equipment. Full article

This study presents an optimal design combined with comprehensive multiphysics validation to enhance the torque density of a coaxial magnetic gear (CMG) incorporating an overhang structure. Four high non-integer gear-ratio CMG configurations exceeding 1:10 were designed using different pole-pair combinations, and three-dimensional finite element method (3D FEM) was employed to accurately capture axial leakage flux and overhang-induced three-dimensional effects. Eight key geometric design variables were selected within non-saturating limits, and 150 sampling points were generated using an Optimal Latin Hypercube Design (OLHD). Multiple surrogate models were constructed and evaluated using the root-mean-square error (RMSE), and the Kriging model was selected for multi-objective optimization using a genetic algorithm. The optimized CMG with a 1:10.66 gear ratio achieved a 130.76% increase in average torque (65.75 Nm) and a 162.51% improvement in torque density (117.14 Nm/L) compared with the initial design. Harmonic analysis revealed a strengthened fundamental component and a reduction in total harmonic distortion, indicating improved waveform quality. To ensure the feasibility of the optimized design, comprehensive multiphysics analyses—including electromagnetic–thermal coupled simulation, high-temperature demagnetization analysis, and structural stress evaluation—were conducted. The results confirm that the proposed CMG design maintains adequate thermal stability, magnetic integrity, and mechanical robustness under rated operating conditions. These findings demonstrate that the proposed optimal design approach provides a reliable and effective means of enhancing the torque density of high gear-ratio CMGs, offering practical design guidance for electric mobility, robotics, and renewable energy applications. Full article

At-rest PPG signals have been explored for detecting atrial fibrillation (AF), yet current signal-processing techniques do not achieve perfect accuracy even under low-motion artifact (MA) conditions. This study evaluates the effectiveness of a single-degree-of-freedom time–frequency (SDOF-TF) method in analyzing at-rest PPG signals for AF detection. The method leverages the influence of MA on the instant parameters of each harmonic, which is identified using an SDOF model in which the tissue–contact–sensor (TCS) stack is treated as an SDOF system. In this model, MA induces baseline drift and time-varying system parameters. The SDOF-TF method enables the quantification and removal of MA and noise, allowing for the accurate extraction of the arterial pulse waveform, heart rate (HR), heart rate variability (HRV), respiration rate (RR), and respiration modulation (RM). Using data from the MIMIC PERform AF dataset, the method achieved 100% accuracy in distinguishing AF from non-AF cases based on three features: (1) RM, (2) HRV derived from instant frequency and instant initial phase, and (3) standard deviation of HR across harmonics. Compared with non-AF, the RM for each harmonic was increased by AF. RM exhibited an increasing trend with harmonic order in non-AF subjects, whereas this trend was diminished in AF subjects. Full article

This paper develops a compact and scalable mathematical model of an AC circuit with an uncontrolled diode bridge rectifier, formulated using dimensionless variables. The model captures the joint influence of supply inductance, resistance, and load parameters on current waveform distortion, harmonic content, and reactive power exchange, which are often simplified or addressed separately in existing studies. Experimental validation confirms the applicability of the model over a wide range of operating conditions and grid strengths. The results provide quantitative characteristics that support the interpretation of power quality measurements and the assessment of how nonlinear loads interact with non-stiff supply sources. The proposed formulation offers an efficient analytical tool for harmonic analysis in distribution networks, particularly where a balance between modelling accuracy and computational effort is required. Full article

The increasing demand for reliable DC fast-charging stations in electric vehicle (EV) infrastructure necessitates efficient fault detection mechanisms to ensure operational stability and user safety. This paper will present the development of a diagnostic method for identifying open-circuit faults and short-circuit faults in DC charging stations by leveraging Total Harmonic Distortion (THD) analysis combined with a Second-Order Generalized Integrator (SOGI). The proposed approach uses the THD method to detect anomalies in the current and voltage waveforms, while the Frequency Locked Loop (FLL) serves to track the frequency of the grid and keep the SOGI tuned to it, and SOGI-FLL provides the rectifier with the capability of tracking the frequency, amplitude, voltage, and phase of the grid and monitoring these parameters of the grid. The ability to measure the THD is the kernel of the detection of faults. Detailed simulation confirms the method’s high sensitivity and robustness in detecting open/short circuit faults with minimal false positives. This technique offers a cost-effective, non-invasive diagnostic solution suitable for modern DC charging systems, contributing to improved reliability and efficiency of EV charging infrastructure. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that significantly affects motor functions, including speech production. Voice analysis offers a less invasive, faster and more cost-effective approach for diagnosing and monitoring PD over time. This research introduces an automated system to distinguish between PD and non-PD individuals based on speech signals using state-of-the-art signal processing and machine learning (ML) methods. A publicly available voice dataset (Dataset 1, 81 samples) containing speech recordings from PD patients and non-PD individuals was used for model training and evaluation. Additionally, a small supplementary dataset (Dataset 2, 15 samples) was created although excluded from experiment, to illustrate potential future extensions of this work. Features such as Mel-frequency cepstral coefficients (MFCCs), spectrograms, Mel spectrograms and waveform representations were extracted to capture key vocal impairments related to PD, including diminished vocal range, weak harmonics, elevated spectral entropy and impaired formant structures. These extracted features were used to train and evaluate several ML models, including support vector machine (SVM), XGBoost and logistic regression, as well as deep learning (DL)architectures such as deep neural networks (DNN), convolutional neural networks (CNN) combined with long short-term memory (LSTM), CNN + gated recurrent unit (GRU) and bidirectional LSTM (BiLSTM). Experimental results show that DL models, particularly BiLSTM, outperform traditional ML models, achieving 97% accuracy and an AUC of 0.95. The comprehensive feature extraction from both datasets enabled robust classification of PD and non-PD speech signals. These findings highlight the potential of integrating acoustic features with DL methods for early diagnosis and monitoring of Parkinson’s Disease. Full article

Non-contact vital signs detection of the survivors based on bio-radar to identify their life states is significant for field search and rescue. However, when transportation is interrupted, rescue workers and equipment are unable to arrive at the disaster area promptly. In this paper, we report a hovering airborne radar for non-contact vital signs detection to overcome this challenge. The airborne radar system supports a wireless data link, enabling remote control and communication over distances of up to 3 km. In addition, a novel framework based on blind source separation is proposed for vital signals extraction. First, range migration caused by the platform motion is compensated for by the envelope alignment. Then, the respiratory waveform of the human target is extracted by the joint approximative diagonalization of eigenmatrices algorithm. Finally, the heartbeat signal is recovered by respiratory harmonic suppression through a feedback notch filter. The field experiment results demonstrate that the proposed method is capable of precisely extracting vital signals with outstanding robustness and adaptation in more cluttered environments. The work provides a technical basis for remote high-resolution vital signs detection to meet the increasing demands of actual rescue applications. Full article

The proliferation of next-generation renewable energy systems has driven widespread adoption of electronic devices and nonlinear loads, causing grid distortion that degrades waveform quality in grid-forming (GFM) converters. Additionally, unbalanced grid faults exacerbate overcurrent risks and transient stability challenges when employing conventional virtual impedance strategies. While existing studies have separately examined these challenges, few have comprehensively addressed non-ideal grid conditions. To bridge this gap, a novel control strategy is proposed that reshapes the output current waveforms and enhances transient stability in GFM converters under such conditions. First, a sliding mode controller with an improved composite reaching law to achieve rapid reference tracking while eliminating chattering is designed. Second, a multi-quasi-resonance controller incorporating phase compensation is introduced to suppress harmonic distortion in the converter output current. Third, an individual-phase fuzzy adaptive virtual impedance strategy dynamically reshapes the current amplitude during unbalanced faults and improves the system’s transient stability. Validated through PSCAD/EMTDC simulations and hardware-in-the-loop experiments, the proposed strategy demonstrates superior transient stability and fault ride-through capability compared to state-of-the-art methods, ensuring reliable GFM converter operation under severe harmonic and unbalanced grid conditions. Full article

A split-phase three-level LCL grid-connected inverter is proposed to match the single-phase three-wire split-phase output power grids in countries such as those in North America. However, influencing factors such as grid impedance and background harmonics in non-ideal power grids may lead to distortion and even instability of the output waveform of the grid-connected inverter. To address the aforementioned issues, through a stability analysis of the dual-feedback system of inverter-side current control and capacitor current active damping, a composite active damping strategy is put forward to enhance the stability of the LCL grid-connected inverter. This composite active damping strategy encompasses a standardized method for designing the robust capacitor current feedback coefficient and a method of embedding leading-phase correction to improve system stability. The strategy proposed in this paper is more streamlined and standardized when calculating the capacitor current feedback coefficient, enabling the system to operate stably under a wide range of grid impedance variations. Moreover, an analysis of the mechanism by which grid background harmonics affect the grid-connected current waveform is conducted, and the PR controller is replaced with a multiple proportional-resonant (MPR) controller. The MPR controller can achieve infinite gain at specific harmonics, thereby suppressing specific low-order harmonics in the grid and reducing the total harmonic distortion (THD) of the grid-connected current. Finally, the effectiveness of the proposed control strategy is verified on a 12 kW experimental platform. The results indicate that, compared with the inverter-side current feedback active damping (ICFAD) method, the composite active damping strategy proposed in this paper exhibits stronger robustness, and the added MPR controller significantly enhances the anti-interference ability of the grid-connected inverter against grid harmonics. Full article

In power systems, various power quality disturbances are present, including voltage deviation, voltage unbalance, and voltage waveform distortions. Voltage waveform distortions are usually identified with harmonics, but in some systems, subharmonics (subsynchronous interharmonics) and interharmonics may also occur—that is, components of frequency less than the fundamental frequency, or not an integer multiple of it. This study examines torque pulsations of an induction motor under voltage subharmonics combined with voltage unbalance. The motor and the driven DC generator vibrations were analysed under the power quality disturbances. Investigations were carried out using finite element and empirical methods. Experimental tests were performed for the maximal levels of the power quality disturbances specified or proposed in the relevant standards. For the investigated motor, under voltage subharmonics or voltage unbalance occurring as a single power quality disturbance, the vibration level was within the prescribed limit. However, under unbalance combined with subharmonics, the level could be accepted for only a limited time. Consequently, the permissible level of voltage subharmonics in non-generation installations should be interconnected with the voltage unbalance in the power system. Full article