Key technologies of active power filter for aircraft: a review

Active Power Filter (APF) is not only an advanced technology to improve power quality and purify power system pollution but also a good approach to solve electrical problems of an advanced aircraft such as harmonic, reactive power and unbalanced load. However, there are still some specific problems for the application of aeronautic APF in practice. Based on current research on aeronautic APF, this paper reviews three key technologies where APF can be used in aircraft AC power supply system, including the acquisition method of reference current, the strategy of APF current control and the main circuit topology.  Consecutively, the features of current aeronautic APF research are summarized, and the future research directions are also suggested

Universal fractional-order design of linear phase lead compensation multirate repetitive control for PWM inverters

Repetitive control (RC) with linear phase lead compensation provides a simple but very effective control solution for any periodic signal with a known period. Multirate repetitive control (MRC) with a downsampling rate can reduce the need of memory size and computational cost, and then leads to a more feasible design of the plug-in repetitive control systems in practical applications. However, with fixed sampling rate, both MRC and its linear phase lead compensator are sensitive to the ratio of the sampling frequency to the frequency of interested periodic signals: (1) MRC might fails to exactly compensate the periodic signal in the case of a fractional ratio; (2) linear phase lead compensation might fail to enable MRC to achieve satisfactory performance in the case of a low ratio. In this paper, a universal fractional-order design of linear phase lead compensation MRC is proposed to tackle periodic signals with high accuracy, fast dynamic response, good robustness, and cost-effective implementation regardless of the frequency ratio, which offers a unified framework for housing various RC schemes in extensive engineering application. An application example of programmable AC power supply is explored to comprehensively testify the effectiveness of the proposed control scheme

Virtual variable sampling discrete fourier transform based selective odd-order harmonic repetitive control of DC/AC converters

This paper proposes a frequency adaptive discrete Fourier transform (DFT) based repetitive control (RC) scheme for DC/AC converters. By generating infinite magnitude on the interested harmonics, the DFT-based RC offers a selective harmonic scheme to eliminate waveform distortion. The traditional DFT-based selective harmonic RC, however, is sensitive to frequency fluctuation since even very small frequency fluctuation leads to a severe magnitude decrease. To address the problem, virtual variable sampling method, which creates an adjustable virtual delay unit to closely approximate a variable sampling delay, is proposed to enable the DFT-based selective harmonic RC to be frequency adaptive. Moreover, a selective odd-order harmonic DFT filter is developed to deal with the dominant odd order harmonic. Because it halves the number of sampling delays in the DFT filter, the system transient response gets nearly 50% improvement. A comprehensive series of experiments of the proposed VVS DFT-based selective odd-order harmonic RC controlled programmable AC power source under frequency variations are presented to verify the effectiveness of the proposed method

A Comprehensive Survey on Different Control Strategies and Applications of Active Power Filters for Power Quality Improvement

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Power quality (PQ) has become an important topic in today’s power system scenario. PQ issues are raised not only in normal three-phase systems but also with the incorporation of different distributed generations (DGs), including renewable energy sources, storage systems, and other systems like diesel generators, fuel cells, etc. The prevalence of these issues comes from the non-linear features and rapid changing of power electronics devices, such as switch-mode converters for adjustable speed drives and diode or thyristor rectifiers. The wide use of these fast switching devices in the utility system leads to an increase in disturbances associated with harmonics and reactive power. The occurrence of PQ disturbances in turn creates several unwanted effects on the utility system. Therefore, many researchers are working on the enhancement of PQ using different custom power devices (CPDs). In this work, the authors highlight the significance of the PQ in the utility network, its effect, and its solution, using different CPDs, such as passive, active, and hybrid filters. Further, the authors point out several compensation strategies, including reference signal generation and gating signal strategies. In addition, this paper also presents the role of the active power filter (APF) in different DG systems. Some technical and economic considerations and future developments are also discussed in this literature. For easy reference, a volume of journals of more than 140 publications on this particular subject is reported. The effectiveness of this research work will boost researchers’ ability to select proper control methodology and compensation strategy for various applications of APFs for improving PQ.publishedVersio

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

Suppression of Second-Order Harmonic Current for Droop-Controlled Distributed Energy Resource Converters in DC Microgrids

Droop-controlled distributed energy resource converters in dc microgrids usually show low output impedances. When coupled with ac systems, second-order harmonics typically appear on the dc-bus voltage, causing significant harmonic currents at the converters resource side. This paper shows how to reduce such undesired currents by means of notch filters and resonant regulators included in the converters control loops. The main characteristics of these techniques in terms of harmonic attenuation and stability are systematically investigated. In particular, it is shown that the voltage control-loop bandwidth is limited to be below twice the line frequency to avoid instability. Then, a modified notch filter and a modified resonant regulator are proposed, allowing to remove the constraint on the voltage loop bandwidth. The resulting methods (i.e., the notch filter, the resonant regulator, and their corresponding modified versions) are evaluated in terms of output impedance and stability. Experimental results from a dc microgrid prototype composed of three dc-dc converters and one dc-ac converter, all with a rated power of 5kW, are reported