Reference Current Generation Research Articles

Improved Harmonic Mitigation and Power Injection Technique for Solar-fed DG System Using GA and PSO

This paper deals with Distributed Generation (DG) system requiring power quality features such as current harmonics, reactive power compensation, and power factor improvement in grid tied operation. The motivation is to combine DG system with the capabilities of shunt active filter to perform real power injection, current harmonics mitigation and power factor improvement. The control algorithm employed in this setup utilizes a reference current generator based on p-q theory together with a pulse width modulation controller for switching pulse generation. The control strategy utilizes PI controller with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for finding optimal PI controller parameters. The effectiveness of the proposed method is verified using MATLAB/Simulink and experimental model developed for 3kWp inverter. The PI-PSO controller injects 0.588kW active power into the grid results in sharing 54% of load power demand and the current harmonics is reduced from 23.70% to 1.63%. The obtained results demonstrate that the grid tied inverter maintains harmonic standards in accordance with the IEEE-519 standard while injecting maximum possible active power to the line.

Shunt Active Power Filters in Three-Phase, Three-Wire Systems: A Topical Review

The increasingly extensive use of non-linear loads, mostly including static power converters, in large industry, commercial, and domestic applications, as well as the spread of renewable energy sources in distribution-generated units, make the use of the most efficient power quality improvement systems a current concern. The use of active power filters proved to be the most advanced solution with the best compensation performance for harmonics, reactive power, and load unbalance. Thus, issues related to improving the power quality through active power filters are very topical and addressed by many researchers. This paper presents a topical review on the shunt active power filters in three-phase, three-wire systems. The power circuit and configurations of shunt active filtering systems are considered, including the multilevel topologies and use of advanced power semiconductor devices with lower switching losses and higher switching frequencies. Several compensation strategies, reference current generation methods, current control techniques, and DC-voltage control are pointed out and discussed. The direct power control method is also discussed. New advanced control methods that have better performance than conventional ones and gained attention in the recent literature are highlighted. The current state of renewable energy sources integration with shunt active power filters is analyzed. Concerns regarding the optimum placement and sizing of the active power filters in a given power network to reduce the investment costs are also presented. Trends and future developments are discussed at the end of this paper. For a rigorous substantiation, more than 250 publications on this topic, most of them very recent, constitute the basis of bibliographic references and can assist readers who are interested to explore the subject in greater detail.

Currents’-Physical-Component-Based Reactive Power Compensation Optimization in Three-Phase, Four-Wire Systems

In this paper, we aim to address the limited capacity of compensation devices by enhancing their utilization rate by applying the currents’ physical component (CPC) theory for reactive power optimization in three-phase four-wire systems. When reactive currents cannot be fully compensated for, we propose using CPC theory to generate reference currents for the compensation devices. Weight coefficients associated with different reactive current components are introduced, enabling flexible combinations of these independent current components. The maximum output amplitude of the three-phase current from the compensation device serves as a constraint condition, allowing for the calculation of reference currents under various compensation targets. Additionally, a reactive current optimization compensation scheme focusing on loss reduction is selected. The simulated annealing–particle swarm optimization (SA-PSO) hybrid algorithm is employed to solve the optimization mathematical model. The discussed calculations, current waveforms, and voltage waveforms are generated using the constructed mathematical model and then used for a theoretical explanation. The simulation verifies the feasibility of the proposed method.

Power Harmonic Suppression based direct vector control for robust DFIG operation during grid voltage distortions

AbstractThis paper proposes a Power Harmonic Suppression (Damping) (PHS) based reference current generation scheme, which focuses on simultaneous mitigation of harmonic pulsations in electromagnetic torque, stator real and reactive powers, and DC‐link voltage while retaining sinusoidal stator and grid currents and unity power factor at grid side. The crux of this PHS method lies in its ability to eliminate the harmonic powers developed in the DFIG stator and grid at 100Hz, 200Hz, 300Hz, 400Hz, and 600 Hz owing to second, fifth, and seventh harmonic grid voltages. This is achieved as a result of the elimination of natural fluxes developed in the DFIG air gap due to second, fifth, and seventh harmonic distortions in grid voltage. For this, a single concurrent reference current generation technique is developed for RSC and GSC to mitigate the oscillations of electromagnetic torque, stator real and reactive powers, and ripples in DC‐link voltage. Further, the reference rotor currents (positive, negative, fifth, and seventh sequence) are compared with the actual rotor currents using a PI controller to retain sinusoidal stator and grid currents. The proposed scheme's efficacy is validated with PSCAD/EMTDC simulations and using OPAL‐RT OP4510 real‐time simulator, on a 2.3 kVA DFIG.

A novel hybrid PI–backstepping cascade controller for battery–supercapacitor electric vehicles considering various driving cycles scenarios

AbstractThe integration of supercapacitors as hybrid energy storage systems in electric vehicles has attracted the attention of many researchers and has been considered as a promising solution. Bidirectional DC/DC converters (BDDCs) play a fundamental role in HESS, as they manage the power flow by controlling currents and regulating the DC bus voltage. However, they encounter the challenge of uncertainties and high fluctuation power loads, necessitating the fast dynamics, stability, and high robustness of the controller. This paper proposes a novel hybrid proportional–integral and backstepping cascade controller to regulate the DC‐bus voltage under uncertainties and load variations, and to control the current references of the on‐boarded sources. To confirm the asymptotic stability of the whole system, a nonlinear stability analysis is conducted using the Lyapunov theorem. A power management strategy is applied to distribute the power loads and generate reference currents for the BDDCs controller. Simulations results under various driving cycles using MATLAB/Simulink demonstrate the superiority of the proposed controller compared to conventional proportional–integral and backstepping controllers. A real‐time controller‐hardware‐in‐the‐loop test bench is developed to validate the effectiveness of the proposed strategy.

Low Voltage Ride Through Control Strategy for a Two-Stage Grid-Tied Solar Photovoltaic System with Grid Faults

This paper investigates a low voltage ride-through (LVRT) control strategy for a two-stage grid-tied solar photovoltaic (SPV) system with line-to-ground (L-G) and double line-to-ground (L-L-G) faults. A proportional resonant (PR) controller controls the SPV inverter based on classical and reactive power oscillation-based reference current generating techniques. The proposed method injects reactive power as an ancillary service to provide voltage support and prevent power outages, reduces the DC component injection into the grid currents, and finally injects sinusoidal currents into the grid, avoid voltage oscillations in the DC-link and limit the inverter current by operating the boost converter in non-MPPT mode during L-G & L-LG faults. Experimental results for reference current generation using classical method and proposed method are compared to highlight the proposed controller’s ability to maintain power quality during faults.

Social Media Data Mining and Mental Health Status Assessment Based on Sentiment Analysis

The usage of the word Power quality in recent times acquired intensified interest due to the complex industrial processes. The usage of intelligent tools to improve power quality is increasing day by day, as assumption of present day power system as a linear model is unsatisfactory. This paper deals with analysis of Differential Evolution (DE), Hybrid Differential Evolution (HDE) and Variable Scaling Hybrid Differential Evolution for harmonic reduction in the source current with optimal tuning of PI controller gain values. Shunt Active power Filter is one of the better solution to suppress the source current harmonics which are induced into power system because of nonlinear loads. Current controller called HBCC is considered for gating operation of switches in Voltage Source Inverter. The Intelligent tuned PQ theory is used for reference current generation. The then obtained compensating currents are injected at point of common coupling for current disturbance mitigation. Simulations of MATLAB/SIMULINK environment of the present work shows the efficacy.

Computer Modeling Analysis of Electric Vehicle's Choice Behavior Considering Latent Variables

At present, there are few researches on the influence of psychological latent variables on the choice behavior of electric vehicles, and lack of consideration of individual heterogeneity. In this study, computer modeling was used to construct not only a traditional discrete choice model that takes into account individual heterogeneity, but also a hybrid choice model,which takes into account psychological latent variables are constructed to explore the mutual effects of observable personal attributes, vehicle attributes and difficult to directly observe psychological latent variables on consumers’ choice behavior of electric vehicles. The estimation results of hybrid choice model with psychological latent variables and the traditional discrete choice model without considering psychological latent variables are compared. The result show that perceived usefulness, perceived risk and purchasing attitude have a significant impact on consumers’ choice behavior of electric vehicles. Compared with traditional discrete choice model, the hybrid choice model, which takes into account psychological latent variables has significantly higher prediction accuracy and has better interpretation ability and fitting effect. The research results can provide theoretical support for further expanding the electric vehicle market and formulating relevant policieshe usage of the word Power quality in recent times acquired intensified interest due to the complex industrial processes. The usage of intelligent tools to improve power quality is increasing day by day, as assumption of present day power system as a linear model is unsatisfactory. This paper deals with analysis of Differential Evolution (DE), Hybrid Differential Evolution (HDE) and Variable Scaling Hybrid Differential Evolution for harmonic reduction in the source current with optimal tuning of PI controller gain values. Shunt Active power Filter is one of the better solution to suppress the source current harmonics which are induced into power system because of nonlinear loads. Current controller called HBCC is considered for gating operation of switches in Voltage Source Inverter. The Intelligent tuned PQ theory is used for reference current generation. The then obtained compensating currents are injected at point of common coupling for current disturbance mitigation. Simulations of MATLAB/SIMULINK environment of the present work shows the efficacy.

Experimental Validation of the Generation of Direct and Quadratic Reference Currents by Combining the Ant Colony Optimization Algorithm and Sliding Mode Control in PMSM using the Process PIL

This article aims to enhance the control efficiency of the Permanent Magnet Synchronous Motor (PMSM) by generating optimal reference currents and using Ant Colony Optimization (ACO), while ensuring a minimal absorbed current condition to reduce energy consumption and optimize PMSM performance. The ACO algorithm is chosen for its ability to find global solutions and robustness in complex environments, while Sliding Mode Control (SMC) provides advantages in terms of robustness against disturbances and the ability to maintain the system in a desired state. The implementation of the processor-in-the-loop (PIL) technique using MATLAB software with code composer and the LAUNCHXL- F28069M board enables the controller to be implemented in real hardware (LAUNCHXL-F28069M) to test the simulation environment (inverter and PMSM). Our results demonstrate the efficiency of ACO compared to the analytical method (AM) in terms of response time and minimizing absorbed current for different load values. Artificial intelligence (AI) has successfully and efficiently addressed the non-linearity between torque and reference currents, thus reducing energy consumption. This has allowed for the optimization of PMSM performance in a straightforward and efficient manner.

Open-Phase-Tolerant Online Current References for Maximum Torque Range and Minimum Loss With Current and Torque-Ripple Limits for n-Phase Nonsalient PMSMs With Nonsinusoidal Back EMF

Multiphase permanent-magnet synchronous machines (PMSMs) with nonsinusoidal back-electromotive force (back-EMF) offer high fault tolerance and torque density for electric vehicles. Most current-reference generation methods either minimize stator copper loss (SCL) or maximize achievable torque. Optimization of both goals is accomplished by full-torque-range minimum-loss (FRML) strategies, but so far just for sinusoidal back-EMF. Thus, FRML for nonsinusoidal back-EMF should be sought. Moreover, many methods are only suitable for healthy conditions or specific machines, harmonics, or open-phase-fault (OPF) scenarios. Additionally, the torque range may be extended by permitting torque ripple or (transiently) greater rms current, but this approach is not general nor FRML yet. This paper proposes online FRML current-reference generation for multiphase PMSMs with nonsinusoidal back-EMF: nonsinusoidal-back-EMF FRML (NSBE-FRML). When the torque reference is feasible, minimum SCL is attained while maximizing the achievable torque (i.e., FRML). For higher torque references, the instantaneous torque deviation is minimized, and the torque reference is saturated in consecutive samples limiting the torque ripple to a pre-specified threshold. Furthermore, the rms current is limited after transient overload by automatically decreasing the torque reference. The NSBE-FRML is suitable for any harmonics, healthy/OPF conditions, and multiphase PMSMs with negligible saliency ratio. Experiments are performed with a six-phase PMSM.

Neural Network With Cloud-Based Training for MTPA, Flux-Weakening, and MTPV Control of IPM Motors and Drives

An interior permanent magnet (IPM) motor is a prime electric motor used in electric vehicles (EVs), robots, and electric drones. In these applications, maximum torque per ampere (MTPA), flux-weakening, and maximum torque per volt (MTPV) techniques play a critical role in the efficient and reliable torque control of an IPM motor. Although several approaches have been proposed and developed for this purpose, each has its specific limitations. The objective of this paper is to develop a neural network (NN) method to determine MTPA, flux-weakening, and MTPV operating points for the most efficient torque control of the motor over its full speed range. The NN is trained offline by using the Levenberg-Marquardt backpropagation algorithm, which avoids the disadvantages associated with online NN training. A cloud computing system is proposed for routine offline NN training, which enables the lifetime adaptivity and learning capabilities of the offline-trained NN and overcomes the computational challenges related to online NN training. In addition, for the proposed NN mechanism, training data are collected and stored in a highly random manner, which makes it much more feasible and efficient to implement lifetime adaptivity than any other methods. The proposed method is evaluated via both simulation and hardware experiments, which shows the great performance of the NN-based MTPA, MTPV, and flux-weakening control for an IPM motor over its full speed range. Overall, the proposed method can achieve a fast and accurate current reference generation with a simple NN structure, for optimal torque control of an IPM motor.

Adaptive Hybrid NFS-MSOGIQ Control Technique for Improving Power Quality in Solar PV Distributed Generation System

A two-stage circuit configuration with 3-phase utility grid assisted solar power generation system is designed. In order to track the solar PV arrays maximum peak power (MPP), a DC boost converter with Composite Incremental Conductance (InC) MPP technique is employed in first stage. In Second stage, a grid-tied four-leg DC-AC converter, is employed to provide the solar power that was extracted into the utility grid and to enhancing power quality. An adaptive hybrid Multi-Second Order Generalized Integrator-Quadrature (MSOGI-Q) control algorithm, in conjunction with Neuro Fuzzy system (NFS) is proposed for controlling this DC-AC converter. MSOGI-Q reference current generation strategy is designed to mitigate current harmonics by retrieving the fundamental constituents from non-linear load. The Neuro Fuzzy system along with PID controller, by adjusting the voltage from dc link keeps consistent power in between AC and DC sides for varying isolation condition. To get the peak power out of a PV panel even in different environmental conditions, the composite incremental conductance algorithm is used. To upgrade the dynamic performance of voltage variation at Point of Common Coupling (PCC) a feedforward descriptor for Photovoltaic contributions has been implemented. In addition, a comparison between the proposed NFS-MSOGIQ control technique and the existing adaptive control technique is done to assess the effectiveness of the proposed adaptive control technique. The proposed adaptive control technique for the distributed generation system is designed and stimulated in MATLAB/SIMULINK and the simulation outcomes verify the effectiveness of the proposed control technique under various transition circumstances. A laboratory prototype model of the proposed system is developed for theoretical analysis and its results are found to be compliant with IEEE standards. Furthermore, THD values of voltage and current are found to be within standard limits.

Power Quality Improvement based on VSHDE Algorithm Incorporating Shunt Active Power Filter

The usage of the word Power quality in recent times acquired intensified interest due to the complex industrial processes. The usage of intelligent tools to improve power quality is increasing day by day, as assumption of present day power system as a linear model is unsatisfactory. This paper deals with analysis of Differential Evolution (DE), Hybrid Differential Evolution (HDE) and Variable Scaling Hybrid Differential Evolution for harmonic reduction in the source current with optimal tuning of PI controller gain values. Shunt Active power Filter is one of the better solution to suppress the source current harmonics which are induced into power system because of nonlinear loads. Current controller called HBCC is considered for gating operation of switches in Voltage Source Inverter. The Intelligent tuned PQ theory is used for reference current generation. The then obtained compensating currents are injected at point of common coupling for current disturbance mitigation. Simulations of MATLAB/SIMULINK environment of the present work shows the efficacy.

An ultra-low quiescent current power-on reset circuit with DDPG method

An ultra-low quiescent current power-on reset (POR) circuit with double-delay pulse generation (DDPG) method is presented in this paper. The circuit is designed for non-volatile memory (NVM) systems, aiming to ensure reliable initialization and enhance overall efficiency. To address the challenge of inaccurate trigger-point voltage caused by process, voltage, temperature (PVT) and ramp time variations, a novel pulse generation method is proposed. Additionally, the circuit further improves the reliability of pulse duration through the utilization of low-cost current reference generators. Implemented in standard 40 nm CMOS technology, the delay-based POR circuit consumes only 0.24 nA quiescent current and occupies a compact area of 25.6μm×102μm. The simulation results demonstrate a typical pulse duration time of 28μs, with a temperature coefficient (TC) of 101.4 ppm/°C. The high reliability and low overhead of this circuit make it suitable for NVM systems and other fast power-on applications.

Optimum reference current generation for switched reluctance motor torque ripple minimization in electric vehicle applications.

In this paper, an optimization approach for generating reference current to minimize torque ripple in SRM for EV applications was proposed. Initially, a speed/current controller was developed using the backstepping approach, taking into account magnetic saturation. To generate an optimal current profile, control parameters were optimized using an offline method based on the PSO algorithm. The proposed control strategy was validated using the MATLAB-Simulink environment. A comparison with fixed excitation method was conducted to demonstrate the superiority and robustness of the proposed controller. It achieved reductions in both torque and current ripples of 33.71% and 27.41% respectively. These significant reductions highlighted the proposed controller’s effectiveness, particularly when applied to a driving cycle, and highlighted its overall advantages.

Grid integrated multifunctional EV charging infrastructure with improved power quality

This paper presents a grid integrated multifunctional electric vehicle (EV) charging infrastructure to power the EV batteries and simultaneously improve grid power quality. The EV charger control function is designed to operate the charger in grid-to-vehicle (G2V), vehicle-to-grid (V2G), and proposed active-filtering-mode (AFM) operating modes. In AFM mode, the proposed self-tuning filter (STF) based control algorithm effectively compensates the grid current harmonic distortions arising from nonlinear charging station load. Furthermore, the charger controller uses STF to estimate the synchronizing voltage templates for reference current generation instead of conventional phase-locked-loop (PLL) and second-order generalized integrator (SOGI) to address the nonideal grid voltage conditions. The charger controller is designed to operate in AFM operating mode simultaneously with G2V and V2G operating modes. Furthermore, to achieve these multifunctional operations in a single charger, the power electronics circuitry of the charger is developed by using an AC/DC voltage source converter and a DC/DC dual active bridge (DAB) converter. The embedded isolation in the DAB converter ensures the safety of the EV batteries from the disturbance in the AC and DC side of the charger. Furthermore, a 3.6 kVA EV charger prototype is developed in the laboratory to show the effectiveness of the control techniques.

Design-time Reference Current Generation for Robust Spintronic-based Neuromorphic Architecture

Neural Networks (NN) can be efficiently accelerated in a neuromorphic fabric based on emerging resistive non-volatile memories (NVM), such as Spin Transfer Torque Magnetic RAM (STT-MRAM). Compared to other NVM technologies, STT-MRAM offers many benefits, such as fast switching, high endurance, and CMOS process compatibility. However, due to its low ON/OFF-ratio, process variations and runtime temperature fluctuations can lead to miss-quantizing the sensed current and, in turn, degradation of inference accuracy. In this article, we analyze the impact of the sensed accumulated current variation on the inference accuracy in Binary NNs and propose a design-time reference current generation method to improve the robustness of the implemented NN under different temperature and process variation scenarios (up to 125 °C). Our proposed method is robust to both process and temperature variations. The proposed method improves the accuracy of NN inference by up to 20.51% on the MNIST, Fashion-MNIST, and CIFAR-10 benchmark datasets in the presence of process and temperature variations without additional runtime hardware overhead compared to existing solutions.

Instrumentation for Verification of Shunt Active Power Filter Algorithms.

This article presents a comprehensive system for testing and verifying shunt active power filter control methods. The aim of this experimental platform is to provide tools to a user to objectively compare the individual control methods. The functionality of the system was verified on a hardware platform using least mean squares and recursive least squares algorithms. In the experiments, an average relative suppression of the total harmonic distortion of 22% was achieved. This article describes the principle of the shunt active power filter, the used experimental platform of the controlled current injection source, its control system based on virtual instrumentation and control software and ends with experimental verification. The discussion of the paper outlines the extension of the experimental platform with the cRIO RTOS control system to reduce the latency of reference current generation and further planned research including motivation.

A Dual Fundamental Current Extraction Controller for DSTATCOM in the Distribution System for Power Quality Improvement Under Non-Ideal Source Voltage Condition

Most of the controllers often fail to work properly when encountered with power quality (PQ) issues like unbalanced and distorted grid voltage conditions in three-phase distribution system (TPDS). To address this problem, usually a dynamic static compensator (DSTATCOM) is utilized in TPDS. For enhanced performance, a novel dual fundamental component extraction (DFCE) technique is proposed for generating reference currents (RC) in a TPDS exhausting DSTATCOM. The proposed controller is highly effective for reactive power compensation and source current harmonic suppression under source unbalanced voltages condition with nonlinear load conditions. For computation of RC and phase synchronization, the controller extracts the required fundamental voltage and current at the same time. Consequently, the controller is able to control DSTATCOM operation in TPDS without any phase locked loop (PLL) and low pass filter (LPF). For generation of fundamental components of voltage and current, projected controller utilizes the self-tuning filter (STF). The efficacy of the controller is established in comparison to existing controllers like synchronous reference frame theory, p-q theory and STF-p-q under different grid voltage conditions. To enhance PQ, the suggested controller works efficiently for fundamental current component extraction without using PLL and low/high pass filter in case of grid distorted voltage condition.

General Online Current-Harmonic Generation for Increased Torque Capability With Minimum Stator Copper Loss in Fault-Tolerant Multiphase Induction Motor Drives

This paper proposes a current-reference generation method including current harmonic injection (CHI) for enhancing the torque capability of multiphase induction machines (IMs) with negligible space-harmonic effects, which is useful, e.g., during transient overload in electric vehicles. The admissible torque is increased because the harmonics reduce the phase-current peaks, so that the instantaneous peak-current constraint of the drive, usually associated with the converter ratings, is respected. The harmonics are injected in the so-called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x-y</i> subspaces of the IM, which do not produce torque, so that no torque ripple is introduced. The optimum harmonics are found online for each load, making it possible to minimize the stator copper loss (SCL) per torque in the entire torque range, ensuring full-range minimum loss (FRML). The method is suitable for healthy operation or open-phase faults, and for multiphase machines of any phase number and with either symmetrical or asymmetrical windings. Compared with FRML methods without CHI, higher torque is achieved. Although some techniques were available for increasing the torque capability by CHI, FRML was not attained, laborious offline optimization was needed, or they were only suitable for specific drives or for healthy conditions, unlike the proposal. Experimental results with a symmetrical six-phase IM are provided.