Harmonic Identification Research Articles

A Modified Variable Power Angle Control for Unified Power Quality Conditioner in a Distorted Utility Source

The distorted supply voltage degrades the control performance of a unified power quality conditioner (UPQC). This problem causes incorrect calculations in the harmonic identification and reference signal generation processes. This paper proposes a modified harmonic identification of the UPQC. The reference compensating current calculation for the shunt active power filter (shunt APF) is developed using the sliding window with the Fourier analysis (SWFA) method. In addition, the variable power angle control (PAC) is applied to operate the reference signal generation of the series APF and the shunt APF of the UPQC. Under the distorted voltage and nonlinear load conditions, the proposed approach can provide accurate reference compensating signals and successfully share the load reactive power compensation between the shunt APF and the series APF. In this work, a three-phase, three-wire power system with linear and nonlinear loads was implemented. The proposed method was validated using the processor-in-the-loop technique on an eZdsp™ F28335 board and the MATLAB/Simulink program. The testing results indicated that SWFA has excellent filtering performance and enhances harmonic identification compared to the operation without any filter or with low pass filters (LPF). With the proposed approach, the percentage of total harmonic distortion of voltage and current could be maintained within the IEEE519-2022 standard, and the magnitude of the RMS voltage across the load was in the recommended range specified by ANSI C84.1-2016.

Laplacian atom search optimization algorithm: development and application for harmonic estimator design

Harmonics, are the major source of contaminations in fundamental voltage and current signals. For consumer satisfaction and for better equipment performance, these contaminations shall be identified and mitigated. Although, for accurate identification of harmonics, several methods have been proposed, yet metaheuristic based approaches have been used and in practice, since last two decades. The work reported here is based on a newly proposed optimization algorithm named as Atom Search Optimisation (ASO). In the first phase, a variant of ASO is proposed, based on Laplacian operator based position update mechanism named as Laplacian-ASO (L-ASO) for enhancing the performance of ASO and in the next phase, application of a newly developed L-ASO is carried out on harmonic estimator design problems. The improvisation of our proposed L-ASO is validated through conducted analyses and results showcased in the discussion section.

Three novel machine learning-based adaptive controllers for a photovoltaic shunt active power filter performance enhancement

This study develops three new machine learning-based algorithms using the SVR prediction approach. The overall objective is to enhance the performance of the PV shunt active power filter (PV-SAPF) in order to successfully fulfil its multi-functionality in terms of PV power generation along with power quality upgrades. The first technique, named "SVR-INC MPPT", incorporates an ML-based duty cycle prediction function, which is intended to speed up the MPP finding process. The algorithm then switches to the INC approach, guaranteeing an accurate steady-state response. The second and third techniques are the ML-based Adaline for DC voltage regulation, and the ML-based Adaline SRF strategy for reference currents generation. The adopted approaches are based on the prediction of two weights performing the actions of the proportional and integral of DC voltage controller, and nine weights for the fundamental currant extraction. The advantage lies in overcoming the Adaline-based algorithm's limitations, requiring an on-line large number of iterations. Three simulation scenarios along with six controllers based on classical and intelligent techniques, are adopted to prove the effectiveness of the proposed ML-controllers. The results display (i) an accurate and immediate ML-based harmonics identification (minimizing the extraction error by up to 99% compared to the Adaline approach). (ii) a response time reduction range from 65% to 100%, of the ML-based DC voltage output controller compared to the PI-based one. (iii) a THD range from 2.41% to 4.45%. (iv) 20 ms and 0% of PV power response time and overshoot, respectively (v) DC voltage overshoot range from 0.04% to 1.1%. Consequently, these three ML-based controllers offer the best options for a powerful PV-SAPF system in terms of performance tracking and harmonic attenuation. Moreover, the obtained metrics comply with IEEE-519 standard.

Erratum to “Sideband Harmonics Identification and Application for Slip Estimation of Induction Motors Based on a Self-Adaptive Wiener Filter”

Erratum to “Sideband Harmonics Identification and Application for Slip Estimation of Induction Motors Based on a Self-Adaptive Wiener Filter”

Challenges of ANN in Adapting to Abrupt Parameters Variations for Shunt Active Filter

The purpose of the shunt active power filter (SAPF) goes beyond simply improving power factor; it also aims to mitigate unwanted harmonic currents generated by nonlinear loads. This research introduces a SAPF equipped with an identification and control method utilizing artificial neural networks (ANN). Various techniques are employed for harmonic identification, including traditional p-q theory and the relatively recent approach of artificial neural networks. Achieving satisfactory identification and control characteristics is challenging when dealing with the nonlinearity of the system, particularly in situations involving rapid nonlinear load fluctuations. This study represents a systematic effort to address this challenge by enhancing the SAPF with a method for harmonics identification and DC link voltage control based on ANN. This approach is tested on the SAPF under conditions of fast, nonlinear load variations. The study includes both computer simulations and experimental results, which provide evidence of the viability and effectiveness of the proposed active power filter.

New Technology and Method for Monitoring the Status of Power Systems to Improve Power Quality—A Case Study

The identification and analysis of harmonics, frequency, and transient events are essential today. It is necessary to have available data relating to harmonics, frequency, and transient events to understand power systems and their proper control and analysis. Power quality monitoring is the first step in identifying power quality disturbances and reducing them and, as a result, improving the performance of the power system. In this paper, while presenting different methods for measuring these quantities, we have made some corrections to them. These reforms have been obtained through the analysis of power network signals. Finally, we introduce a new monitoring system capable of measuring harmonics, frequency, and transient events in the network. In addition, these values are provided for online and offline calculations of harmonics, frequency, and transient events. In this paper, two new and practical methods of the “algebraic method” are used to calculate network harmonics and wavelet transform to calculate transient modes in the network. Furthermore, the proposed monitoring system is able to reduce the amount of data-storage memory. The results of the simulations performed in this article show the superiority of using the new method presented for online and offline monitoring of power quality in electric power systems.

Characterizing Anomalous High-Harmonic Generation in Solids.

Anomalous high-harmonic generation (HHG) arises in certain solids when irradiated by an intense laser field, originating from a Berry-curvature-induced perpendicular anomalous current. The observation of pure anomalous harmonics is, however, often prohibited by contamination from harmonics stemming from interband coherences. Here, we fully characterize the anomalous HHG mechanism, via development of an abinitio methodology for strong-field laser-solid interaction that allows a rigorous decomposition of the total current. We identify two unique properties of the anomalous harmonic yields: an overall yield increase with laser wavelength; and pronounced minima at certain laser wavelengths and laser intensities around which the spectral phases drastically change. Such signatures can be exploited to disentangle the anomalous harmonics from competing HHG mechanisms, and thus pave the way for the experimental identification and time-domain control of pure anomalous harmonics, as well as reconstruction of Berry curvatures.

A Mathematical Framework, Simulation, and Measurement of Harmonic Identification Systems

A Mathematical Framework, Simulation, and Measurement of Harmonic Identification Systems

Sideband Harmonics Identification and Application for Slip Estimation of Induction Motors Based on a Self-Adaptive Wiener Filter

Sideband Harmonics Identification and Application for Slip Estimation of Induction Motors Based on a Self-Adaptive Wiener Filter

Acceleration harmonic identification for an electro-hydraulic shaking table based on the Simulated Annealing-Particle Swarm Optimization algorithm

Nonlinear factors exist in electro-hydraulic shaking table and may distort the response signal when a sinusoidal acceleration is inputted. To obtain accurate harmonics, a harmonic identification strategy for the acceleration of the electro-hydraulic shaking table based on the SA-PSO (Simulated Annealing-Particle Swarm Optimization) algorithm was proposed. First, the criterion function of harmonic identification was built with the least square method. Then, the PSO algorithm was introduced into the internal circulations of the SA algorithm to speed up the local search speed to construct the harmonic identification strategy. To verify the performance of the identification strategy, the SA algorithm, PSO algorithm, and SA-PSO algorithm were successively used to identify the response signal. And the convergence rate, accuracy, and stability of the three algorithms were compared. Finally, the harmonic regeneration was carried out after the amplitude and phase of each harmonic were obtained. Experimental results show that the harmonic identification strategy has fast identification speed and high identification accuracy.

Propagation Characteristics and Identification of High-Order Harmonics of a Traction Power Supply System

High-order harmonics in the traction power supply show negative effects on the safe and stable operation of the railway transportation system. There is a fixed resonant frequency in the traction network. When the harmonic current frequency produced by the locomotive matches the resonant frequency of the traction network, it will cause high-frequency resonant overvoltage. The propagation path of the high-order harmonics of the traction load is analyzed based on a V/v wiring traction transformer. The propagation characteristics of high-order harmonics on self-used equipment at 380 V low-voltage side and 27.5 kV high-voltage side are expounded. A simulation model for the low-voltage self-consumption power system is established and the singular value decomposition algorithm is proposed to identify the harmonic impedance. The simulation results show that the proposed method can reduce the error to within 0.1%. Under realistic conditions, the overvoltage caused by high-order harmonics is difficult to identify. To solve this problem, an overvoltage identification algorithm for Electric Multiple Units based on a convolutional neural network is proposed. The ShuffleNet neural network model is then used to identify high-order harmonics overvoltage and other types of overvoltage. The overall accuracy of the proposed classification model can be improved from 97.12% to 98.44%. Better recognition and classification performances can also be achieved.

Evaluation of the VLSS-LMS Method Parameters’ Influence on the Effective Estimation of Power System Current and Voltage Harmonics Content

Nowadays, power quality is considered as a major concern that is faced by electrical energy producer, consumers, industries and researchers. Whereas one among the main issues in such concern is the current and voltage harmonics detection, mitigation and compensation. Indeed, the proliferation of harmonics in power system can create serious problems within all levels and their impacts along the whole power system from the production to the end users can lead to critical technical and economic situations. Therefore, their accurate detection in real time is of great importance and interest where many techniques have been proposed for solving such major problem. The work presented in this paper deals with the evaluation of a technique that has been proposed for the estimation of harmonic content in a signal based on iterative computing technique. This technique is based on several keystone parameters, which have major influences on the accuracy of the identification of the different harmonics without the need of a costly computation, and that can be easily implemented and performed in real-time. It is worthy to clarify that the technique under investigation in this paper is the based on the idea of adaptive filtering process called the Variable length Step Size- Least mean squares method (VLSS-LMS), it is basically very sensitive to three main parameters such as the sampling frequency, the step size value and the measurement window. The evaluation of the effects of these parameters have been assessed based on simulation testes of a specific original signal containing harmonics components. The obtained simulation results clearly prove the optimal choices of the aforementioned parameters in ensuring precise estimation of the harmonics content and the reconstruction of the estimated signal with high precision and minimized average error.

The Electromagnetic Losses Analysis of Inverter-Fed Induction Motor Accounting for Interbar Current and Rotor Slip Frequency

Compared with the fundamental loss, the harmonic losses become very complicated because of the coupling between the power supply harmonics and the motor harmonics. To dispose of this problem, a multislice 2-D finite element model considering the interbar currents and a fast rotor harmonics identification method is employed to identify the harmonics of the rotor current density and flux density of the inverter-fed induction motor (IM). Considering the complex coupling phenomenon of time–space harmonics, a two-term iron model with piecewise-defined variable coefficients (PVCIL model) and a finite element analysis (FEA)-based copper loss method are then used to calculate the iron and copper loss components of the inverter-fed IM. Finally, based on the introduced methods, both the electromagnetic field and different losses terms of the same 5.5-kW inverter-fed IM under different load and supply conditions are calculated and analyzed. The experimental validation of those two losses’ calculation methods is performed on a 5.5-kW IM with different operating conditions. The results obtained in this article can provide the theoretical basis for targeted harmonic elimination and loss reduction in the design phase of the inverter-fed IM.

Identification of Even-Order Harmonics Injected by Semiconverter into the AC Grid

In this study, the feedback effects of a three-phase half-controlled rectifier (also known as a semiconverter) to three-phase AC power grid was analyzed. Special attention was paid to the identification of harmonic order of the phase current. As a reference point for analysis, the mathematical model of an uncontrolled rectifier was used. The harmonic order of the phase current was identified by displaying the measurement results as well as using a mathematical model that is easily applicable, although this is unusual for harmonic analysis because it is based on time domain data. For this purpose, laboratory models of uncontrolled and half-controlled rectifiers were assembled. For both converters, the results obtained by practical laboratory measurements were compared to the mathematically obtained results, with the commutation in the mathematical model being ignored. The effects of commutation were analyzed in more detail for the laboratory model. For the semiconverter, the characteristic waveforms were studied for few different firing angles of the thyristor. Additionally, total power factor and total harmonic distortion of phase current were determined for all chosen firing angles. Finally, a comprehensive conclusion was drawn based on theoretically and practically obtained results on the appearance of even-order current harmonics, which should be taken into consideration when designing input filters and which contributes to power quality of the AC power grid.

Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive

This paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component is calculated using recursive DFT (RDFT) and Goertzel DFT (GDFT), applied instead of the full spectrum calculations required in the most popular FFT algorithm. The simulation model of an inverter sensorlessly controlled induction motor drive is linked with the induction machine rotor fault model for testing the sensitivity of the GDFT- and RDFT-based fault diagnosis to state variable estimation errors. According to the presented simulation results, the accuracy of the direct identification of a fault-related harmonic is sensitive to the quality of fault harmonic frequency estimation. The sensitivity analysis with respect to RDFT and GDFT algorithms is included. Based on the experimental setup with a sensorlessly controlled induction motor drive with the investigated rotor fault, fault diagnosis algorithms were implemented in the microprocessor by integration with the control system in one microcontroller and experimentally verified. The RDFT and GDFT approach has shown accurate and fast direct automated fault identification at a significantly decreased number of arithmetical operations in the microcontroller, which is convenient for the frequency-domain fault diagnosis in electric drives and supports fault-tolerant control system implementation.

Locally optimized chirplet spectrogram for condition monitoring of induction machines in transient regime

The locally optimized chirplet spectrogram (LOCS) is a novel method proposed in this work for generating a high-resolution and cost-effective spectrogram of the induction machine (IM) current, suitable for the identification of fault-related harmonics in transient conditions. Its distinctive novelty is that it optimizes automatically the parameters of the analysing window used for building the current spectrogram, at each point of the time–frequency plane, with the computational cost of a conventional, non-optimized spectrogram. It is based on the definition of a large dictionary of different chirplet windows, which are combined into a single, complex time window. A single short time Fourier transform with this new window generates in parallel the spectrograms of all the dictionary windows, and the LOCS chooses among them the locally optimized values in an automatic way. The proposed technique is applied to the diagnosis of two commercial induction motors with bar breakages and mixed eccentricity faults.

Harmonics estimator design with Trigonometric function inspired Grey Wolf Optimiser

The harmonic estimator design problem is more meaningful in the emerging power systems as quality of power is closely interlinked with consumer satisfaction and electricity price. For designing estimators, bio-inspired algorithms have been employed by researchers. This paper addresses the problem of estimating harmonic components in terms of phase and amplitude of complex waves. Although, for accurate identification of harmonics, several methods have been proposed, yet metaheuristic-based approaches have been used and in practice since the last two decades. Taking inspiration from these, the work presented in the manuscript is a proposal for a harmonic estimator design based on proposed Trigonometric function inspired Grey Wolf Optimiser (T-GWO). To validate the performance of T-GWO, we tested the proposed variant on conventional benches and then a harmonic estimator design is executed. We can observe the satisfactory performance of T-GWO as compared with the other state-of-the-art approaches existed in literature.

Dynamic behavior with comparative study of the parallel active filter commande

The aim of this article relates to the comparison between two strategies for identifying harmonic currents, namely the instantaneous active and reactive power method and the instantaneous currents method, faced with a dynamic non-linear load. This work particularly concerns the study by digital simulation of a parallel active filter intended to filter the harmonic currents generated by a non-linear load and to compensate for reactive energy. Our study focuses on the identification of harmonics and inverter control. The step of identifying harmonic currents is fundamental in the filtering process.

An Extended Model for Ripple Analysis of 2–4 Phase Resonant Electrostatic Induction Motors

Electrostatic motors are promising forms of actuation for future robotic devices. The study of their different implementations should accelerate their adoption. Current models for resonant electrostatic induction motors were found not to be able to properly describe their behavior, namely, with regard to changes with position. This paper reports a new analytical model for these motors, aiming to address this issue. The model is based on identification of all capacitance harmonics, through a simplified method. Using these, equations for different motor parameters, notably, thrust force, were obtained and compared to previous literature. The new equations model position dependent properties, such as force ripple. The outputs of this model were validated through experimentation with a prototype, with the results confirming the new model better describes motor behavior. An analysis into how to decrease this ripple was also discussed and tested. We concluded that the use of a higher number of harmonics resulted in a much more accurate model, capable of adequately characterizing motor outputs with changes in position.

Three-Phase Phase-Locked Loop Algorithms Based on Sliding Modes

This article proposes a family of phase-locked loop schemes based on sliding modes. The use of sliding mode algorithms ensures fast response and global stability. In particular, two new algorithms are presented, both based on a complex framework for representing three-phase signals. This article compares the obtained algorithms with the traditional schemes, and a faster response is obtained when sliding modes are used. Additionally, as an application example, the algorithm is combined with a complex-coefficient filter that allows an easy identification of both positive and negative sequence harmonics. The proposed algorithms are illustrated by numerical simulations and experimentally validated using a digital signal processor.