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

Comparison of two three-phase pll systems for more electric aircraft

The More Electric Aircraft power system is characterized by variable supply frequency, in general between 360Hz and 900Hz. All equipment on board the aircraft have to operate delivering high performance under this variable frequency condition. In particular, power electronic converters need accurate control algorithms able to track the fundamental phase and frequency in real time, both in normal and unusual conditions. Phase Locked Loop (PLL) based algorithms are commonly used in traditional single and three phase power systems to provide phase and frequency estimations of the supply. Despite the simplicity of those algorithms, large estimation errors can arise when power supply voltage has variable frequency or amplitude, presents unbalances or is polluted with harmonics. To improve the quality of the phase and frequency real-time estimations, a robust PLL algorithm, based on a prediction-correction filter, is presented in this paper and compared with a Discrete Fourier Transform (DFT) based procedure. The performances of the two algorithms, implemented in a floating-point DSP, have been compared through an experimental validation obtained on a laboratory power converter prototype

Modeling, Control and Characterization of Aircraft Electric Power Systems

A study model of advanced aircraft electric power system (AAEPS) corresponding to B767 Aircraft is developed in the PSIM9 software environment. The performance characteristics of the system under consideration for large sharing of non-linear loads are studied. A comprehensive mathematical model describing system dynamics is derived where the GSSA technique is applied for reduced-order system approximation. The transient and steady-state performance of the hybrid PEM-FC/battery APU integrated to the aircraft electric network is analyzed while different loading scenarios are taken into account. In addition, dynamic bifurcation analysis is employed to characterize the systems stability performance under multi-parameters condition. Also, the power quality of the system is assessed under various loading configurations, and the effect of installing active/passive power filters (APF/PPF) on power quality of the system is investigated for a wide range of operating frequencies

A novel control technique for active shunt power filters for aircraft applications

The More Electric Aircraft is a technological trend in modern aerospace industry to increasingly use electrical power on board the aircraft in place of mechanical, hydraulic and pneumatic power to drive aircraft subsystems. This brings major changes to the aircraft electrical system, increasing the complexity of the network topology together with stability and power quality issues. Shunt active power filters are a viable solution for power quality enhancement, in order to comply with the standard recommendations. The aircraft electrical system is characterized by variable supply frequency in the range 360-900Hz, hence the harmonic components occur at high and variable frequencies, compared to the terrestrial 50/60Hz systems. In this kind of system, fast and accurate algorithms for the detection of the reference signal for the active filter control and robust high-bandwidth control techniques are needed, in order for the active filter to perform the harmonic elimination successfully. In this thesis, two novel algorithms are proposed. The first algorithm is a frequency and harmonic detection technique, particularly suitable for tracking the variable supply frequency and the harmonic components of voltages and currents in the aircraft electrical system. Complete identication of the reference signal for the active filter control is possible when applying this technique. The second algorithm is a control technique based on the use of multiple rotating reference frames. Only the measurement of the voltage at the Point of Common Coupling and the active filter output current are needed, hence no current sensors are required on the distorting loads. Both the techniques have been validated by means of simulation and experimental analysis. The results show that the proposed methods are effective for a successful harmonic compensation by means of active shunt filters, in the More Electric Aircraft environment

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

Evaluation of two fundamental positive-sequence detectors for highly distorted and unbalanced systems

This paper presents an evaluation of the performance of two different Positive-Sequence Detectors. This evaluation is made by comparing a PLL (Phase-Locked- Loop), combined with Lagrange Multipliers Method, with an Adaptive Filter. Both algorithms aim to detect the positive sequence at the fundamental frequency on a given three-phase system voltages or currents. The purpose of this evaluation is to assess the better Positive-Sequence Detector for custom power devices, such as Active Power Filters. The comparative analysis was based on the evaluation of a series of steady state performance arameters (phase and amplitude errors, THD and unbalance) and on the response time. The tests were made to study the behavior of both approaches when working with highly distorted and unbalanced signals. This work was carried out using the computer simulation tool PSCAD/EMTDC.Fundação para a Ciência e a Tecnologia (FCT) - PTDC/EEA-EEL/104569/2008.FEDER Funds - Operational Programme for Competitiveness Factors – COMPET

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