Showing papers in "IEEE Transactions on Industry Applications in 2017"

Emerging Power Quality Challenges Due to Integration of Renewable Energy Sources

Abstract: Renewable energy becomes a key contributor to our modern society, but their integration to power grid poses significant technical challenges. Power quality is an important aspect of renewable energy integration. The major power quality concerns are: 1) Voltage and frequency fluctuations, which are caused by noncontrollable variability of renewable energy resources. The intermittent nature of renewable energy resources due to ever-changing weather conditions leads to voltage and frequency fluctuations at the interconnected power grid. 2) Harmonics, which are introduced by power electronic devices utilized in renewable energy generation. When penetration level of renewable energy is high, the influence of harmonics could be significant. In this paper, an extensive literature review is conducted on emerging power quality challenges due to renewable energy integration. This paper consists of two sections: 1) Power quality problem definition. Wind turbines and solar photovoltaic systems and their power quality issues are summarized. 2) Existing approaches to improve power quality. Various methods are reviewed, and the control-technology-based power quality improvement is the major focus of this paper. The future research directions for emerging power quality challenges for renewable energy integration are recommended.

Deep Learning Based Approach for Bearing Fault Diagnosis

Abstract: Bearing is one of the most critical components in most electrical and power drives. Effective bearing fault diagnosis is important for keeping the electrical and power drives safe and operating normally. In the age of Internet of Things and Industrial 4.0, massive real-time data are collected from bearing health monitoring systems. Mechanical big data have the characteristics of large volume, diversity, and high velocity. There are two major problems in using the existing methods for bearing fault diagnosis with big data. The features are manually extracted relying on much prior knowledge about signal processing techniques and diagnostic expertise, and the used models have shallow architectures, limiting their capability in fault diagnosis. Effectively mining features from big data and accurately identifying the bearing health conditions with new advanced methods have become new issues. This paper presents a deep learning-based approach for bearing fault diagnosis. The presented approach preprocesses sensor signals using short-time Fourier transform (STFT). Based on a simple spectrum matrix obtained by STFT, an optimized deep learning structure, large memory storage retrieval (LAMSTAR) neural network, is built to diagnose the bearing faults. Acoustic emission signals acquired from a bearing test rig are used to validate the presented method. The validation results show the accurate classification performance on various bearing faults under different working conditions. The performance of the presented method is also compared with other effective bearing fault diagnosis methods reported in the literature. The comparison results have shown that the presented method gives much better diagnostic performance, even at relatively low rotating speeds.

Operation of a Grid-Connected Lithium-Ion Battery Energy Storage System for Primary Frequency Regulation: A Battery Lifetime Perspective

Abstract: Because of their characteristics, which have been continuously improved during the last years, Lithium-ion batteries have been proposed as an alternative viable solution to present fast-reacting conventional generating units to deliver the primary frequency regulation service. However, even though there are worldwide demonstration projects, where energy storage systems based on Lithium-ion batteries are evaluated for such applications, the field experience is still very limited. In consequence, at present, there are no very clear requirements on how the Lithium-ion battery energy storage systems should be operated, while providing frequency regulation service and how the system has to reestablish its state of charge (SOC) once the frequency event has passed. Therefore, this paper aims to investigate the effect on the lifetime of the Lithium-ion batteries energy storage system of various strategies for reestablishing the batteries’ SOC after the primary frequency regulation is successfully delivered.

Small-Signal Stability Assessment of Power Electronics Based Power Systems: A Discussion of Impedance- and Eigenvalue-Based Methods

Abstract: This paper investigates the small-signal stability of power electronics-based power systems in frequency domain. A comparison between the impedance-based and the eigenvalue-based stability analysis methods is presented. A relation between the characteristics equation of the eigenvalues and poles and zeros of the minor-loop gain from the impedance-based analysis have been derived analytically. It is shown that both stability analysis methods can effectively determine the stability of the system. In the case of the impedance-based method, a low phase-margin in the Nyquist plot of the minor-loop gain indicates that the system can exhibit harmonic oscillations. A weakness of the impedance method is the limited observability of certain states given its dependence on the definition of local source-load subsystems, which makes it necessary to investigate the stability at different subsystems. To address this limitation, the paper discusses critical locations where the application of the method can reveal the impact of a passive component or a controller gain on the stability. On the other hand, the eigenvalue-based method, being global, can determine the stability of the entire system; however, it cannot unambiguously predict sustained harmonic oscillations in voltage source converter (VSC) based high voltage dc (HVdc) systems caused by pulse-width modulation (PWM) switching. To generalize the observations, the two methods have been applied to dc-dc converters. To illustrate the difference and the relation between the two-methods, the two stability analysis methods are then applied to a two-terminal VSC-based HVdc system as an example of power electronics-based power systems, and the theoretical analysis has been further validated by simulation and experiments.

Performance Improvement of Model-Predictive Current Control of Permanent Magnet Synchronous Motor Drives

Abstract: Model-predictive current control (MPCC) is widely recognized as a high-performance control strategy of permanent magnet synchronous machine (PMSM) drives due to its quick response and simple principle. It uses a cost function to select the best voltage vector minimizing the current error between the reference value and the feedback value. However, as only one voltage vector is applied during one control period, it fails to give satisfactory performance due to the limited voltage vectors, especially in the case of two-level converters. This paper proposes an improved MPCC strategy for PMSM drives, which first estimates the back electromotive force (EMF) based on the past value of stator voltage and currents and then applies the estimated EMF in the stator current prediction. To achieve steady-state performance improvement, a null vector along with the active vector obtained from conventional MPCC is applied during one control period. Two methods are proposed to achieve optimal vector selection and vector duration. The first one requires six predictions and the calculation of current differentiation, while the second one only requires one prediction to obtain the best voltage vector and its optimal duty can be obtained in a very efficient way. The proposed methods are comparatively studied and compared to conventional MPCC and deadbeat control with space vector modulation. Both simulation and experimental results confirm the effectiveness of the proposed methods in achieving good steady-state performance while maintaining quick dynamic response.

Sensorless Control of Permanent Magnet Synchronous Machine Based on Second-Order Sliding-Mode Observer With Online Resistance Estimation

Abstract: In this paper, a supertwisting algorithm based second-order sliding-mode observer (STA-SMO) with online stator resistance ( $ R_{s}$ ) estimation for sensorless control of a nonsalient permanent magnet synchronous machine is proposed. A stator current observer is designed based on an STA to estimate the back electromotive force. A discontinuous sign function in the conventional SMO is replaced by a supertwisting function. The chattering problem, unavoidable in conventional SMO, is eliminated by reducing the amplitude of switching function of an STA-SMO. Meanwhile, a parallel online $ R_{s}$ estimation scheme is presented based on a modified SMO. Because mismatch between actual and set resistance may lead to estimation error and even system instability. The Lyapunov stability theorem is used to obtain the stable conditions of the proposed online $ R_{s}$ observer at both motoring and generating mode. With the help of online $ R_{s}$ observer, resistance uncertainties caused by temperature variation can be taken into account, which means robustness and stability of an STA-SMO can be improved. At the same time, higher position and speed estimation accuracy is obtained and operation range of sensorless control is extended. Finally, the proposed method is validated and compared with a conventional method by simulations and experiments.

Model Predictive Control for Shunt Active Filters With Fixed Switching Frequency

Abstract: This paper presents a modification to the classical Model Predictive Control (MPC) algorithm and its application to active power filters. The proposed control is able to retain all the advantages of a finite control set MPC while improving the generated waveforms harmonic spectrum. In fact, a modulation algorithm, based on the cost function ratio for different output vectors, is inherently included in the MPC. The cost function-based modulator is introduced and its effectiveness on reducing the current ripple is demonstrated. The presented solution provides an effective and straightforward single loop controller, maintaining an excellent dynamic performance despite the modulated output and it is self-synchronizing with the grid. This promising method is applied to the control of a shunt active filter for harmonic content reduction through a reactive power compensation methodology. Significant results obtained by experimental testing are reported and commented, showing that MPC is a viable control solution for active filtering systems.

A Robust Observer-Based Method for IGBTs and Current Sensors Fault Diagnosis in Voltage-Source Inverters of PMSM Drives

Abstract: Permanent magnet synchronous motors (PMSMs) drives using three-phase voltage-source inverters (VSIs) are currently used in many industrial applications. The reliability of VSIs is one of the most important factors to improve the reliability and availability levels of the drive. Accordingly, this paper presents a robust fault diagnostic method for multiple insulated gate bipolar transistors (IGBTs) open-circuit faults and current sensor faults in three-phase PMSM drives. The proposed observer-based algorithm relies on an adaptive threshold for fault diagnosis. Current sensor and open-circuit faults can be distinguished and the faulty sensors and/or power semiconductors are effectively isolated. The proposed technique is robust to machine parameters and load variations. Several simulation and experimental results using a vector-controlled PMSM drive are presented, showing the diagnostic algorithm robustness against false alarms and its effectiveness in both IGBTs and current sensors fault diagnosis.

Load Shedding and Smart-Direct Load Control Using Internet of Things in Smart Grid Demand Response Management

Abstract: This paper proposes the use of a novel algorithm for smart-direct load control (S-DLC) and load shedding to minimize power outages in sudden grid load changes and reduce the peak-to-average ratio. The algorithm utilizes forecasting, shedding, and S-DLC. It also uses the Internet of Things and stream analytics to provide real-time load control, and generates a daily schedule for customers’ equipped with intelligent electronic devices based on their demands, thermal comfort, and the forecasted load model. The demand response techniques are utilized for real-time load control and optimization. To test the algorithm, a simulation system was developed, which takes into account 100 customers owning randomly selected appliances. The results indicated that load shedding using autoregressive integrated moving average time-series prediction model, and applying S-DLC and Internet of Things can significantly reduce customers’ power outage.

Control of a Hybrid AC/DC Microgrid Involving Energy Storage and Pulsed Loads

Abstract: This paper presents a real-time coordinated control of the hybrid ac/dc microgrids involving energy storage and pulsed loads. Grid-isolated hybrid microgrid applications require special considerations due to the intermittent generation, online energy storage control, and pulsed loads. In this study, we introduce a comprehensive frequency and voltage control scheme for a hybrid ac/dc microgrid consisting of a synchronous generator, solar generation emulator, and bidirectional (ac/dc and dc/dc) converters. A bidirectional controlled ac/dc converter with an active and reactive power decoupling technique is used to link the ac bus with the dc bus, while regulating the system voltage and frequency. A dc/dc boost converter with a maximum power point tracking function is implemented to maximize the intermittent energy generation from solar generators. Current-controlled bidirectional dc/dc converters are applied to connect each lithium-ion battery bank to the dc bus. Lithium-ion battery banks act as energy storage devices that serve to increase the system resiliency by absorbing or injecting power. Experimental results are presented for verification of the introduced hybrid ac/dc power flow control scheme.

Demagnetization Modeling and Fault Diagnosing Techniques in Permanent Magnet Machines Under Stationary and Nonstationary Conditions: An Overview

Abstract: Permanent magnet (PM) machines are widely used in industrial processes due to their merits such as high power density and torque and low losses (high efficiency). These machines operate frequently under harsh conditions; therefore, they expose different types of faults. These faults can be diagnosed in initial stages using different techniques and prevent the faults' progress to catastrophic stages. One of the most important PM machine faults in terms of occurrence rate is demagnetization fault, whose causes can be heat, electrical, environmental or combinations. This may lead to efficiency drop, poor performance, and low reliability of the system. This paper attempts to review and summarize the demagnetization fault diagnosis methods in PM machines. First the fault generating factors and their impacts on the performance of the motor are discussed. Then, the recently developed techniques for demagnetization fault under stationary and nonstationary conditions in two separate sections are addressed. Presented methods are compared; their weaknesses and strengths are noted. Finally, suggestions for further research are proposed.

Power Flow Management of a Grid Tied PV-Battery System for Electric Vehicles Charging

Abstract: The prospective spread of electric vehicles (EV) and plug-in hybrid EV raises the need for fast charging rates. High required charging rates lead to high power demands, which may not be supported by the grid. In this paper, an optimal power flow technique of a PV-battery powered fast EV charging station is presented to continuously minimize the operation cost. The objective is to help the penetration of PV-battery systems into the grid and to support the growing need of fast EV charging. An optimization problem is formulated along with the required constraints and the operating cost function is chosen as a combination of electricity grid prices and the battery degradation cost. In the first stage of the proposed optimization procedure, an offline particle swarm optimization (PSO) is performed as a prediction layer. In the second stage, dynamic programming (DP) is performed as an online reactive management layer. Forecasted system data is utilized in both stages to find the optimal power management solution. In the reactive management layer, the outputs of the PSO are used to limit the available state trajectories used in the DP and, accordingly, improve the system computation time and efficiency. Online error compensation is implemented into the DP and fed back to the prediction layer for necessary prediction adjustments. Simulation and 1 kW prototype experimental results are successfully implemented to validate the system effectiveness and to demonstrate the benefits of using a hybrid grid tied system of PV-battery for fast EVs charging stations.

Lithium-Ion Battery Charge Equalization Algorithm for Electric Vehicle Applications

Abstract: The lithium-ion batteries are commonly used in electric vehicle (EV) applications due to their better performances as compared with other batteries. However, lithium-ion battery has some drawbacks such as the overcharged cell which has a risk of explosion, the undercharged cell eventually reduces the life cycle of the battery, and unbalanced charge in series battery gradually reduces overall charge capacity. This paper presents a battery charge equalization algorithm for lithium-ion battery in EV applications to enhance the battery's performance, life cycle, and safety. The algorithm is implemented in series-connected battery cells of 15.5 Ah and 3.7 V nominal each using a battery monitoring integrated circuit for monitoring and equalization of an 8-cell battery pack using a bidirectional flyback dc–dc converter as the channel for charging and discharging of the battery cell. The obtained results show that the developed charge equalization controller algorithm performs well in equalizing both undercharged and overcharged cells, and equalizes the cell within the safety operation range of 3.81 V. To validate the charge equalizer performance, the proposed algorithm outperforms with other studies in terms of balancing, equalization speed, low power loss, and efficiency. Thus, the proposed battery charge equalization algorithm proves an effective and automated system to modularize the battery charge that improves the safety and life cycle of battery.

Advanced High Torque Density PM Vernier Machine With Multiple Working Harmonics

Abstract: In recent years, permanent magnet (PM) vernier machines have gained more and more attention due to their high torque density and simple mechanical structure. However, PM vernier (PMV) machines with lap windings always suffer from long end winding length, and regular nonoverlapping winding may result in torque reduction for PMV machines. In this paper, an advanced PMV machine topology with multiple working harmonics is proposed. With specially designed stator auxiliary teeth, this topology could achieve ∼20% higher torque density than that of a regular nonoverlapping winding PMV machine, with the same magnet usage. Through finite element algorithm and theoretical analysis, the production of additional flux density harmonics and their contributions to back-electromotive force (EMF) are verified. Moreover, the electromagnetic performances of this novel machine topology, such as back-EMF and output torque, are quantitatively investigated with the geometric parameters’ effect considered. Finally, analysis results are verified by experimental test on a 21 Nm prototype, which is designed to have similar volume and weight with a 14 Nm regular commercial PM machine.

Variable Flux Permanent Magnet Synchronous Machine (VF-PMSM) Design Methodologies to Meet Electric Vehicle Traction Requirements with Reduced Losses

Abstract: Variable flux permanent magnet synchronous machines (VF-PMSMs) in which the magnetization state of low coercive force permanent magnets can be actively controlled to reduce losses in applications that require wide-speed operation have been proposed recently. While prior focus has been on achieving magnetization state manipulation without oversizing the inverter and obtaining higher torque capability, this paper extends the design objectives to include the power requirements of an electric vehicle traction motor over its entire speed range. Finite-element methods are used to study the effect of combinations of low coercive-force and high coercive-force permanent magnets arranged in either series or parallel on the performance of VF-PMSMs. While both configurations help improve the torque density, only the series configuration can help improve the high speed power capability. Experimental results showing the variable magnetization state property, torque-speed capability, and loss reduction capability of a series magnet configuration VF-PMSM test machine are presented.

MPPT of Photovoltaic Systems Using Sensorless Current-Based Model Predictive Control

Abstract: Variability in the solar irradiance level and ambient temperature of photovoltaic (PV) systems necessitates the use of maximum power point tracking (MPPT) of PV systems to ensure continuous harvesting of maximum power This paper presents a sensorless current (SC) MPPT algorithm using model predictive control (MPC) The main contribution of this paper is the use of model-based predictive control principle to eliminate the current sensor that is usually required for well-known MPPT techniques such as perturb and observe (P&O) By predicting the PV system states in horizon of time, the proposed method becomes an elegant, embedded controller that allows faster response and lower power ripple in steady state than the conventional P&O technique under rapidly changing atmospheric conditions This becomes possible without requiring expensive sensing and communications equipment and networks for direct measurement of solar irradiation changes The performance of the proposed SC-MPC-MPPT with reduced load sensitivity is evaluated on the basis of industrial European Efficiency Test, EN 50530, that assesses the performance of PV systems under dynamic environmental conditions The proposed control technique is implemented experimentally using dSPACE DS1007 platform to verify the simulation results

Application of Infrared Thermography to Failure Detection in Industrial Induction Motors: Case Stories

Abstract: Infrared thermography has been extensively applied over decades to areas such as maintenance of electrical installations. Its use in electrical machinery has been mainly circumscribed to the detection of faults in static machines, such as power transformers. However, with regard to the predictive maintenance of rotating electrical machines, its use has been much more limited. In spite of this fact, the potential of this tool, together with the progressive decrease in the price of infrared cameras, makes this technique a very interesting option to at least complement the diagnosis provided by other well-known techniques, such as current or vibration data analysis. In this context, infrared thermography has recently shown potential for the detection of motor failures including misalignments, cooling problems, bearing damages, or connection defects. This work presents several industrial cases that help to illustrate the effectiveness of this technique for the detection of a wide range of faults in field induction motors. The data obtained with this technique made it possible to detect the presence of faults of diverse nature (electrical, mechanical, thermal, and environmental); these data were very useful to either diagnose or complement the diagnosis provided by other tools.

Operation and Control of an Improved Hybrid Nine-Level Inverter

Abstract: This paper proposes a new nine-level inverter for medium- and high-power applications. The proposed topology comprises of a three-level (3L) active neutral-point-clamped (ANPC) inverter connected in series with a floating capacitor (FC) fed H-bridge. Besides, two additional switches operating at line frequency are appended across the dc link of the 3L ANPC structure. Compared with conventional hybrid cascaded inverters, the primary advantage of this addition is doubling of the resulting root mean square output voltage. This amelioration is achieved while preserving the standard 3L ANPC and H-bridge structures with minimum topological modification. A simple logic-gate-based voltage balancing scheme is developed to regulate the FC voltage. The proposed voltage balancing method is independent of load power factor, inverter modulation index, and can balance the voltage across FC instantaneously. The step-by-step formulation of logical expressions for the generation of gating pulses is deliberated in detail and can be generalized for any $n$ -level inverter. Further, simulation results as well as the experimental measurements obtained from the laboratory prototype are presented to validate the effectiveness and practicability of the proposed configuration. Finally, the notable merits of the proposed inverter over the prior art topologies is established through a comprehensive comparative study.

Multiagent-Based Distributed State of Charge Balancing Control for Distributed Energy Storage Units in AC Microgrids

Abstract: In this paper, a multiagent-based distributed control algorithm has been proposed to achieve state of charge (SoC) balance of distributed energy storage (DES) units in an ac microgrid. The proposal uses frequency scheduling instead of adaptive droop gain to regulate the active power. Each DES unit is taken as an agent and it schedules its own frequency reference given of the real power droop controller according to the SoC values of all other DES units. Further, to obtain the average SoC value of DES, the dynamic average consensus algorithm is utilized by each agent. A generalized small-signal model of the proposed frequency scheduling for the proposed frequency scheduling is developed in order to verify the stability of the control system and to guide control parameters design. The convergence characteristics for the dynamic consensus adopted in the multiagent system are also analyzed to choose the proper control parameter. Experimental results verified the effectiveness, the robustness against communication topology changes, and capability of “plug & play” for the proposed multiagent system through different case studies.

Delta Power Control Strategy for Multistring Grid-Connected PV Inverters

Abstract: With a still increasing penetration level of grid-connected photovoltaic (PV) systems, more advanced active power control functionalities have been introduced in certain grid regulations. A delta power constraint, where a portion of the active power from the PV panels is reserved during operation, is required for grid support (e.g., during frequency deviation). In this paper, a cost-effective solution to realize delta power control (DPC) for grid-connected PV systems is presented, where the multistring PV inverter configuration is adopted. This control strategy is a combination of maximum power point tracking (MPPT) and constant power generation (CPG) modes. In this control scheme, one PV string operating in the MPPT mode estimates the available power, whereas the other PV strings regulate the total PV power by the CPG control strategy in such a way that the delta power constraint for the entire PV system is achieved. Simulations and experiments have been performed on a 3-kW single-phase grid-connected PV system. The results have confirmed the effectiveness of the proposed DPC strategy, where the power reserve according to the delta power constraint is achieved under several operating conditions.

Standards and Guidelines for Grid-Connected Photovoltaic Generation Systems: A Review and Comparison

Abstract: Motivated by concerns about the environment and energy shortages, considerable progress has recently been made in the development of photovoltaic (PV) and other forms of distributed generation. These developments have contributed greatly to awareness of the importance of renewable energy and governmental policies to revise energy priorities to ensure the adoption and significant growth of renewable energy. Safely and reliably interconnecting various PV generators is a major challenge in the development of modern power systems and the interconnection of PV may have effects that require close attention. Standards or guidelines for grid-connected PV generation systems considerably affect PV development. This investigation reviews and compares standards and guidelines for distributed generation, and especially for PV integration. Pertinent standards and guidelines that ensure the successful operation of PV systems are presented. This investigation serves as a reference for improving standards for grid-connected PV generation systems.

Comparison of Two-Individual Current Control and Vector Space Decomposition Control for Dual Three-Phase PMSM

Abstract: The relationship between the two-individual current control and the vector space decomposition (VSD) control for a dual three-phase permanent magnet synchronous machine (PMSM) is investigated in this paper It is found that the VSD control is more flexible in controlling the fundamental current in αβ subplane and the fifth, seventh current harmonics in z 1 z 2 subplane with different proportional and integral (PI) gains, while the two-individual current control is comparable with the VSD control in having the same PI gains in the αβ and z 1 z 2 subplanes It is also found that the two-individual current control may have potential instability issues due to the mutual coupling between the two sets of three-phase windings If the mutual coupling between the two sets is weak to some extent, then the two-individual current control could have the same dynamic performance as the VSD control without the stability issues Experiments are conducted on a prototype dual three-phase PMSM to validate the theoretical analysis

An Adaptive Overcurrent Coordination Scheme to Improve Relay Sensitivity and Overcome Drawbacks due to Distributed Generation in Smart Grids

Abstract: Distributed generation (DG) brought new challenges for protection engineers since standard relay settings of traditional system may no longer function properly under increasing presence of DG. The extreme case is coordination loss between primary and backup relays. The directional overcurrent relay (DOCR), which is the most implemented protective device in the electrical network, also suffers performance degradation in the presence of DG. Therefore, this paper proposes the mitigation of DG impact on DOCR coordination employing adaptive protection scheme (APS) using differential evolution algorithm while improving overall sensitivity of relays. The impacts of DG prior and after the application of APS are presented based on interconnected 6 bus and IEEE 14 bus system. As a consequence, general sensitivity improvement and mitigation scheme is proposed.

Comparison Between Output CM Chokes for SiC Drive Operating at 20- and 200-kHz Switching Frequencies

Abstract: The adoption of silicon carbide (SiC) MOSFETs in variable speed drives (VSDs) makes it possible to increase the inverter switching frequency up to several hundred kilohertz without incurring excessive inverter loss. As a result, the harmonic currents and related losses in the machine can be significantly reduced, and the dynamic performance of motor will also be improved. However, the high switching frequency will increase the common mode (CM) electromagnetic interference (EMI) emission of the drive system presenting new challenges on CM choke design. In the literature, chokes designed for VSDs operating above 100 kHz are rarely found. Hence, this paper presents a case study on the output CM chokes for a SiC-based VSD switching at 20 and 200 kHz. A comprehensive comparison is made between the chokes for two switching frequencies regarding design, sizing, and performance, through both calculation and experiments. The results show that the CM choke designed for 200 kHz switching frequency is significantly larger and heavier than the 20 kHz choke, due to the higher inductance value required to meet the EMI limit and the lower permeability of the core material. Meanwhile, the 200 kHz choke is also less effective in noise attenuation as a result of the larger winding capacitance compared with the 20 kHz choke.

A SiC-Based High-Efficiency Isolated Onboard PEV Charger With Ultrawide DC-Link Voltage Range

Abstract: In LLC-based onboard battery charging architectures used in plug-in electric vehicles (PEV), the dc link voltage can be actively regulated to follow the battery pack voltage so that the LLC converter can operate in proximity of resonant frequency and achieve high efficiencies over the wide range of battery pack voltage. However, conventional boost-type power factor correction (PFC) converters are unable to provide ultrawide dc link voltages since their output voltages should always be larger than their input voltages. This paper proposes a Silicon Carbide (SiC)-based onboard PEV charger using single-ended primary-inductor converter (SEPIC) PFC converter followed by an isolated LLC resonant converter. With the proposed charger architecture, the SEPIC PFC converter is able to provide an ultrawide range for dc link voltage, and consequently enhance the efficiency of the LLC stage by ensuring operation in proximity of resonant frequency. A 1-kW SiC-based prototype is designed to validate the proposed idea. The experimental result shows that the SEPIC PFC converter achieves unity power factor, 2.72% total harmonic distortion, and 95.3% peak conversion efficiency. The LLC converter achieves 97.1% peak efficiency and always demonstrates a very high efficiency across the ultrawide dc-link voltage range. The overall efficiency of the charger is 88.5% to 93.5% from 20% of the rated load to full load.

Aging Precursor Identification and Lifetime Estimation for Thermally Aged Discrete Package Silicon Power Switches

Abstract: Thermal/power cycles are widely acknowledged methods to accelerate the package related failures. Many studies have focused on one particular aging precursor at a time and continuously monitored it using custom-built circuits. Due to the difficulties in taking sensitive measurements, the reported findings are more on the quantities requiring less sensitive measurements. In this paper, two custom-designed testbeds are used to age a number of power MOSFETs and insulated gate bipolar transistors. An automated curve tracer is utilized to capture parametric variations in I – V curves, parasitic capacitances, and gate charges at certain time intervals. The results suggest that the only viable aging precursors are the on-state voltage drop/on-state resistance, body diode voltage drop, parasitic capacitances, and gate threshold voltage for die attach solder and gate-oxide degradation mechanisms. Based on the experimental results, gate threshold voltage variation is empirically modeled to estimate the remaining useful lifetime of the switches experiencing gate oxide degradation. The model parameters are found by the least squares method applied to inliers determined by the random sample and consensus outlier removal algorithm.

Early Fault Detection in Induction Motors Using AdaBoost With Imbalanced Small Data and Optimized Sampling

Abstract: Intelligent fault detection in induction motors (IMs) is a widely studied research topic. Various artificial-intelligence-based approaches have been proposed to deal with a large amount of data obtained from destructive laboratory testing. However, in real applications, such volume of data is not always available due to the effort required in obtaining the predictors for classifying the faults. Therefore, in realistic scenarios, it is necessary to cope with the small-data problem, as it is known in the literature. Fault-related instances along with healthy state observations obtained from the IM compose datasets that are usually imbalanced, where the number of instances classified as the faulty class (minority) is much lower than those classified under the healthy class (majority). This paper presents a novel supervised classification approach for IM faults based on the adaptive boosting algorithm with an optimized sampling technique that deals with the imbalanced experimental dataset. The stator current signal is used to compose a dataset with features both from the time domain and from the frequency domain. The experimental results demonstrate that the proposed approach achieves higher performance metrics than others classifiers used in this field for the incipient detection and classification of faults in IM.

A Circulating-Current Suppression Method for Parallel-Connected Voltage-Source Inverters With Common DC and AC Buses

Abstract: This paper presents a theoretical study with experimental validation of a circulating-current suppression method for parallel operation of three-phase voltage-source inverters (VSI), which may be suitable for modular parallel uninterruptible power supply systems or hybrid ac/dc microgrid applications. The basic concept of the proposed circulating-current suppression method is to modify the original current references by using the current difference among the parallel inverters. In the proposed approach, both cross circulating current and zero-sequence circulating current are considered, and are added into the conventional droop plus virtual impedance control. In the control architecture, the reference voltages of the inverters are generated by the primary control loop, which consists of a droop control and a virtual impedance. The secondary control is used to compensate the voltage drop on the virtual impedance. Furthermore, a circulating-current control loop is added to improve the average current-sharing performance among parallel VSIs. Experimental results are presented to show the effectiveness of the proposed control method to suppress both cross and zero-sequence circulating currents.

Reactive Power Management for Overvoltage Prevention at High PV Penetration in a Low-Voltage Distribution System

Abstract: A new approach for reactive power management with volt–var control, but considering inverters’ capacity and sensitivity to the critical bus is presented in this paper. The approach addresses the voltage rise and reverse power flow issues when residential renewable energy sources such as rooftop solar panels produce more energy than the local load demand. The overvoltage is controlled by selective var injection based on the inverter location, capacity, and minimum power factor limit set by regulation. This method improves the voltage regulation of a distributed system with high penetration of renewable energy sources while efficiently utilizing the inverters’ reactive power capacity. Simulation results are presented with a ten inverter network supplied by a 60 kVA distribution transformer. Experimental results are presented to validate the effectiveness of this method for overvoltage prevention of a distribution test system with three photovoltaic (PV) inverters.

Modified pq -Theory-Based Control of Solar-PV-Integrated UPQC-S

Abstract: This paper proposes a modified pq-theory-based control of a solar photovoltaic (PV)-array-integrated unified power quality conditioner (PV-UPQC-S). The system incorporates clean energy generation along with power quality improvement, thus increasing functionality of the system. The fundamental-frequency positive-sequence components of voltages at the point of common coupling (PCC) are extracted using the generalized cascaded delay signal cancellation technique, which are then used in pq-theory-based control to estimate reference signals for the PV-UPQC-S. This modification in pq theory enables its application for PV-UPQC-S control under conditions of distorted PCC voltages. The series voltage-source converter (VSC) of the PV-UPQC-S operates such that it shares a part of the reactive power of the load even under nominal grid conditions. This increases the utilization of the series VSC while reducing the rating of shunt VSC. The PV array is integrated at the dc bus of the UPQC and provides a part of active load power, thus reducing demand on the supply system. The dynamic performance of the modified pq-theory-based PV-UPQC-S is verified by simulating the system in MATLAB-Simulink with a combination of linear and nonlinear loads. The steady-state and dynamic performances of the system are then experimentally validated through extensive testing on a scaled-down laboratory prototype.