A simple predictive method of critical flicker detection for human healthy precaution

Interharmonics and flickers have an interrelationship between each other. Based on International Electrotechnical Commission (IEC) flicker standard, the critical flicker frequency for a human eye is located at 8.8 Hz. Additionally, eye strains, headaches, and in the worst case seizures may happen due to the critical flicker. Therefore, this paper introduces a worthwhile research gap on the investigation of interrelationship between the amplitudes of the interharmonics and the critical flicker for 50 Hz power system. Consequently, the significant findings obtained in this paper are the amplitudes of two particular interharmonics are able to detect the critical flicker. In this paper, the aforementioned amplitudes are detected by adaptive linear neuron (ADALINE). After that, the critical flicker is detected by substituting the aforesaid amplitudes to the formulas that have been generated in this paper accordingly. Simulation and experimental works are conducted and the accuracy of the proposed algorithm which utilizes ADALINE is similar, as compared to typical Fluke power analyzer. In a nutshell, this simple predictive method for critical flicker detection has strong potential to be applied in any human crowded places (such as offices, shopping complexes, and stadiums) for human healthy precaution purpose due to its simplicity

On Deep Machine Learning Based Techniques for Electric Power Systems

This thesis provides deep machine learning-based solutions to real-time mitigation of power quality disturbances such as flicker, voltage dips, frequency deviations, harmonics, and interharmonics using active power filters (APF). In an APF the processing delays reduce the performance when the disturbance to be mitigated is tima varying. The the delays originate from software (response time delay) and hardware (reaction time delay). To reduce the response time delays of APFs, this thesis propose and investigate several different techniques. First a technique based on multiple synchronous reference frame (MSRF) and order-optimized exponential smoothing (ES) to decrease the settling time delay of lowpass filtering steps. To reduce the computational time, this method is implemented in a parallel processing using a graphics processing unit (GPU) to estimate the time-varying harmonics and interharmonics of currents. Furthermore, the MSRF and three machine learning-based solutions are developed to predict future values of voltage and current in electric power systems which can mitigate the effects of the response and reaction time delays of the APFs. In the first and second solutions, a Butterworth filter is used to lowpass filter the\ua0 dq\ua0 components, and linear prediction and long short-term memory (LSTM) are used to predict the filtered\ua0 dq\ua0 components. The third solution is an end-to-end ML-based method developed based on a combination of convolutional neural networks (CNN) and LSTM. The Simulink implementation of the proposed ML-based APF is carried out to compensate for the current waveform harmonics, voltage dips, and flicker in Simulink environment embedded AI computing system Jetson TX2.\ua0In another study, we propose Deep Deterministic Policy Gradient (DDPG), a reinforcement learning (RL) method to replace the controller loops and estimation blocks such as PID, MSRF, and lowpass filters in grid-forming inverters. In a conventional approach it is well recognized that the controller tuning in the differen loops are difficult as the tuning of one loop influence the performance in other parts due to interdependencies.In DDPG the control policy is derived by optimizing a reward function which measure the performance in a data-driven fashion based on extensive experiments of the inverter in a simulation environment.\ua0Compared to a PID-based control architecture, the DDPG derived control policy leads to a solution where the response and reaction time delays are decreased by a factor of five in the investigated example.\ua0Classification of voltage dips originating from cable faults is another topic addressed in this thesis work. The Root Mean Square (RMS) of the voltage dips is proposed as preprocessing step to ease the feature learning for the developed\ua0 LSTM based classifier. Once a cable faults occur, it need to be located and repaired/replaced in order to restore the grid operation. Due to the high importance of stability in the power generation of renewable energy sources, we aim to locate high impedance cable faults in DC microgrid clusters which is a challenging case among different types of faults. The developed Support Vector Machine (SVM) algorithm process the maximum amplitude and\ua0 di/dt\ua0 of the current waveform of the fault as features, and the localization task is carried out with\ua0 95 %\ua0 accuracy.\ua0Two ML-based solutions together with a two-step feature engineering method are proposed to classify Partial Discharges (PD) originating from pulse width modulation (PWM) excitation in high voltage power electronic devices. As a first step, maximum amplitude, time of occurrence, area under PD curve, and time distance of each PD are extracted as features of interest. The extracted features are concatenated to form patterns for the ML algorithms as a second step. The suggested feature classification using the proposed ML algorithms resulted in\ua0 95.5 %\ua0 and\ua0 98.3 %\ua0\ua0 accuracy on a test data set using ensemble bagged decision trees and LSTM networks

DFT-based recursive group-harmonic energy distribution approach for power interharmonic identification

AbstractThe Discrete Fourier Transform (DFT) is still a widely used tool for analyzing and measuring both stationary and transient signals in power system harmonics. However, the misapplications of DFT can lead to incorrect results caused by some problems such as the aliasing effect, spectral leakage and picket-fence effect. The strategy of a DFT-based recursive Group-harmonic Energy Distribution (GED) algorithm is developed for system-wide harmonic/interharmonic evaluation in power systems. The proposed algorithm can restore individual dispersing spectral leakage energy caused by the DFT, and thus retrieve respective real harmonic/interharmonic value. Every distribution of energy minimizing iteration procedure for harmonic/interharmonic evaluation can be convergent fast, and therefore guarantee each harmonic/interharmonic magnitude and respective frequency approaches its actual value. Consequently, not only can high precision in integer harmonic measurement be retained, but also the interharmonics can be identified accurately, particularly under system frequency drift. A numerical example is presented to verify the proposed algorithm in terms of robust, fast and precise performance

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

An Analysis of Harmonic and Interharmonic Contribution of Electric Arc Furnace by Using Periodogram

Fast and accurate detection of the harmonic and interharmonic contribution of electric arc furnace (EAF) is crucial in identifying and to mitigate the undesired effects to the system.  In this paper, periodogram, a fast and accurate technique is introduced for the analysis of the contribution. Based on a rule-based classifier and the threshold settings that referred to the IEEE Standard 1159 2009, the analysis of the harmonic and interharmonic contribution of EAF are carried out successfully. Moreover, the impact of contribution is measured using total harmonic distortion (THD) and total non-harmonic distortion (TnHD). In addition, periodogram also gives 100 percent correct detection and able to analyze the contribution impact. It is proven that the proposed method is accurate, fast and cost efficient for analyzing the impact of harmonic and interharmonic of EAF

Instrument Transformers for Power Quality Measurements: a Review of Literature and Standards

Measurements of Power Quality (PQ) are gaining more importance due to increasing presence of switching power converters that deform the waveform of the distributed voltage further and further away from a sine wave. Especially at medium and high voltage levels, PQ measurements are carried out by means of Instrument Transformers (ITs). A recently started European metrology project, EMPIR 19NRM05 IT4PQ, aims at establishing the methods and procedures for assessing the accuracy of ITs used for PQ measurements. This paper, that is written in the framework of the IT4PQ project, presents a thorough review of the current state-of-the-art of literature and international standards about ITs and PQ. The main results from several papers and the main information from IT and PQ related international standards are summarized

Interharmonics: Basic concepts and techniques for their detection and measurement

Abstract The term interharmonics refer to those frequencies that are not integral harmonics of the supply fundamental frequency. Although international organizations defined the terminology and proposed measurement guidelines, difficulties still exist in its detection and measurement with acceptable accuracy. When interharmonic components appear in a spectrum, it is still debatable if they really exist and, if the answer is yes, what are the actual frequencies and magnitudes of the components. This paper reviews the mathematical basis of the interharmonics and discusses the difficulties in detecting and measuring interharmonics. A few practical rules are proposed to assist the measurement of interharmonics. Simulations, laboratory experiment and field test results are provided to illustrate the difficulties in interharmonics analysis.