Search

This paper proposes a novel dual input nine-level inverter (DINLI) topology which requires only seven controllable devices. The dual inputs are un-identical DC voltage sources in the ratio 1:3. A simple control scheme is derived by appropriately modifying the phase disposition pulse width modulation technique to generate high-quality 9-level output from the DINLI topology. At any given instant, a maximum of four switches conduct out of which only a maximum of two switches operate at high frequency, bringing down the switching and conduction losses significantly and improving the overall system efficiency. The bidirectional DINLI (BDINLI) topology with reactive power capability can be realized by replacing the unidirectional devices with the controlled switches (i.e., total nine switches). In addition, the proposed DINLI topology does not require extra voltage balancing circuits which further improves the efficiency. The DINLI operation is verified through MATLAB simulations for grid-connected applications and its extension to an n-level, 3-phase application is also investigated. Experiments performed on a 1KVA laboratory prototype to validate the theoretical claims. [ABSTRACT FROM AUTHOR]

Emerging device based spiking neural network (SNN) hardware design has been actively studied. Especially, energy and area efficient synapse crossbar has been of particular interest, but processing units for weight summations in synapse crossbar are still a main bottleneck for energy and area efficient hardware design. In this paper, we propose an efficient SNN architecture with stochastic spin-orbit torque (SOT) device based multi-bit synapses. First, we present SOT device based synapse array using modified gray code. The modified gray code based synapse needs only N devices to represent 2N levels of synapse weights. Accumulative spike technique is also adopted in the proposed synapse array, to improve ADC utilization and reduce the number of neuron updates. In addition, we propose hardware friendly algorithmic techniques to improve classification accuracies as well as energy efficiencies. Non-spike depression based stochastic spike-timing-dependent plasticity is used to reduce the overlapping input representation and classification error. Early read termination is also employed to reduce energy consumption by turning off less associated neurons. The proposed SNN processor has been implemented using 65nm CMOS process, and it shows 90% classification accuracy in MNIST dataset consuming 0.78μJ/image (training) and 0.23μJ/image (inference) of energy with an area of 1.12mm2. [ABSTRACT FROM AUTHOR]

Renewable energy is an advisable choice to reduce fuel consumption and $\rm CO_{2}$ emission. Therein, wind energy and solar energy are the most promising contributors to reach this goal. Although the hybrid wind/solar system has been widely studied, the real-time current sharing based on their maximum capacities is rarely achieved in terms of seconds. Based on this, this paper proposes an accurate current sharing and voltage regulation approach in hybrid wind/solar systems, which is based on distributed adaptive dynamic programming approach. Firstly, the equivalent wind/solar model is built, which is an indispensable preprocessing to achieve the complementary between wind energy and solar energy. Therein, the wind energy and solar energy can output relative current according to their respective capacity ratio, which ensure the maximum utilization ratio of renewable energy source. Furthermore, current sharing and voltage regulation problem is switched into optimal control problem. Under this effect, each source agent aims to obtain the optimal control variable and achieve accurate current sharing/voltage regulation. Moreover, an adaptive dynamic programming approach based on Bellman principle is proposed. It can achieve accurate current sharing and voltage regulation. Finally, the simulation results are provided to illustrate the performance of the proposed adaptive dynamic programming approach. [ABSTRACT FROM AUTHOR]

Channel estimation is one of the main challenges for implementing reconfigurable intelligent surface (RIS)-aided communication system with a large number of antennas at the base station (BS) because RIS is equipped with many passive reflective elements without active transmitting/receiving and signal processing abilities. In this paper, we focus on the channel estimation in a general RIS-aided multi-user mmWave communication system. Specifically, a novel two-phase channel estimation scheme consisting of on-line and off-line phases is proposed to estimate the BS-RIS channel, RIS-user channel, and BS-user channel, respectively. Inspired by the characteristics of few scatterers in mmWave communication systems, the antenna domain channels are converted into the virtual angular domain channels by using the discrete Fourier transform (DFT) matrix. Thus, the estimation problem can be formulated as a compressed sensing (CS) problem, and solved by using efficient vector approximate message passing (VAMP) algorithm with expectation-maximization (EM) to learn unknown parameters and obtain the estimates simultaneously. Simulation results show that, the above algorithm with two choices of prior distributions in the proposed mmWave RIS-aided multi-user system has fast convergence speed and desirable estimation performance. [ABSTRACT FROM AUTHOR]

Personalized venues recommendation is essential to help people find attractive venue to visit as growth of location-based social networks. Existing approaches never distinguish user individual interests from her social preferences, which leads to a bottleneck of modeling user check-in behaviors accurately. In this paper, we find the differences between user interests and her social preferences clearly and investigate the time law of user check-in behaviors in depth. Consequently, we propose a social-period-aware topic model (SPATM) to learn the influence weights of both user interests and her social preferences on making-decision for each check-in time automatically. Especially, we model latent topic by leveraging smaller size of dynamic activities instead of static categories, which can alleviate the data sparsity problem by using more co-occurrent activities information. Moreover, our approach can automatically judge whether a user’s social preference is periodic or aperiodic and learn the periodicity of periodic one. Furthermore, the Alias Sampling based training approach is introduced to improve sampling efficiency. The results demonstrate our proposed model is effective and outperforms the state-of-the-art approaches in terms of effectiveness and efficiency. Besides, SPATM can learn semantically coherent latent topics and geographically dispersed latent social topics which are useful to explain recommendation. [ABSTRACT FROM AUTHOR]

Most microgrid protection schemes found in published literature suffer from a lack of generality in that they work well for the assumed topology, including type and placement of sources. Other generic protection schemes tend to be too complicated, too expensive, or both. To overcome these drawbacks, a topology-agnostic, scalable, and cost-aware protection based on fundamental principles that work in the presence of high penetration of inverter-based resources (IBRs) is developed and tested in this paper. The protection system also implements stable automatic reconfiguration of the healthy sections of the system after clearance of fault, thus increasing resilience by self-healing. To achieve this ambitious goal, stable inverter models are developed that operate in unbalanced networks in grid-connected and islanded modes, even with 100% IBRs, share power without conflicting controls, and can ride through faults while limiting fault currents. The scheme is tested for primary and backup protection and reconfiguration on the IEEE 123-node feeder in grid-connected and islanded modes with 15 IBRs connected to the system. [ABSTRACT FROM AUTHOR]

Different from typical circuit breakers, breakers used to switch AC filters in convertor stations have to operate frequently according to the real-time operation mode and daily load changes. Therefore, the performance of filter breakers decreases very quickly, which leads to frequent accidents. Both preinsertion resistors and controlled switching devices can suppress switching transients. In this paper, a comparative analysis of whether a controlled switching device and preinsertion resistor should be adopted is carried out using PSCAD. The transient is calculated as the combined result of the switching angle and preinsertion resistor value, and the optimal configurations are proposed. After determining the resistor value and whether a controlled switching device should be included, the reference voltage of the arrester should be reevaluated. [ABSTRACT FROM AUTHOR]

This paper proposes a new passive Islanding detection approach for the Inverter Interfaced Distributed Generators (IIDGs) operating under different control modes. First, a novel index is formulated using Root Mean Square (RMS) value of the voltage and the frequency information, acquired at the Point of Common Coupling (PCC) of the target DG. The index is then post-processed by estimating the number of peaks and valleys $(N_{p_{k}-v})$ in a cycle using the sliding window concept, which indicates the occurrence of an event. Finally, the nature of the event, i.e., Islanding or non-Islanding, is decided by exploiting the two statistical features viz., Square of RMS $(S_{RMS})$ of $N_{p_{k}-v}$ and Average Crest Factor $(ACF^{m})$ of the proposed index. The performance of the proposed method (P-IDM) is demonstrated through comprehensive studies in PSCAD/EMTDC for the single-bus and IEEE 34-bus Active Distribution System (ADS). Also, the real-time validation is performed for the IEEE 34-bus using Controller Hardware-in-the-Loop (CHIL) setup comprising of Real-Time Digital Simulator (RTDS) and dSPACE1104. The simulation and hardware results for different test systems indicate that the proposed scheme, being generic in nature, sustains its efficacy under various interface controls of IIDGs. Finally, a comparative assessment with the other existing Signal Processing (SP) based passive methodologies shows the supremacy of the proposed method in terms of accuracy and faster detection. [ABSTRACT FROM AUTHOR]

This paper presents a combined control scheme that consists of two complementary control strategies, namely hierarchical control and autonomous control to handle contingencies in a multi-terminal high voltage direct current (MTDC) system. The proposed hierarchical control considers three optimal targets, i.e., equal or proportional power sharing, minimizations of transmission loss and total DC voltage variation. The primary control layer implements the droop control for voltage source converters (VSCs). While in the secondary control layer, voltage reference setpoints of the VSCs in droop control scheme are calculated by the proposed optimal power flow method with the equal or proportional power sharing as equality constraints. As the hierarchical control relies on communication system, the autonomous control for power sharing can be activated during communication system malfunctioning or rapid power variation caused by renewable energy sources. The combined control strategy can greatly increase the reliability of the MTDC system. The simulation results of a five-terminal MTDC network conducted in the MATLAB/Simulink software verify the performance of the proposed combined control strategy. [ABSTRACT FROM AUTHOR]

Voltage source converters (VSCs) have been extensively used in power systems for interfacing renewable energies and other modern loads. Because of their nonlinear nature, a proper harmonic model of VSC devices must be established when conducting harmonic analyses in power systems. This is especially true for low-order harmonics, which are routinely encountered in present power systems. To this end, an analytical harmonic model that represents the low-order harmonic characteristics of VSCs is developed in this paper. The new model takes both the control loop and power loop (i.e., DC-link capacitor) of the VSC into account through rigorous mathematical derivations. The final result has shown that the VSC can be represented by a harmonically coupled impedance matrix at harmonic frequencies, which can be easily used for harmonic analyses of large-scale power systems. It also shows that the DC-link capacitor has a more noticeable impact on the harmonic impedance of VSCs with a smaller DC-link capacitance and low-order harmonics. The appropriateness of the new model was verified using EMT simulations and lab experiments. A complete procedure to construct the proposed VSC model is also established based on the research findings. [ABSTRACT FROM AUTHOR]

This paper proposes a sound separation methodology based on deep learning neural network (DLNN) to extract useful diagnostic material in non-invasive audio-based On-Load Tap Changer (OLTC) diagnostics. The proposed methodology has been experimentally verified on both artificial mixtures (created by reproducing the targeted data by the speakers placed next to the active transformers) and actual mixtures (recorded by the microphone during OLTC live operation in the field). The results show that the method produces high-quality estimates (correlation to referent fingerprints $\rho > 0.9$) compared to other sound separation methods, e.g. Independent Component Analysis (ICA). The proposed framework can also perform source separation from a monaural mixture (mixture recorded with a single microphone only), which is impossible for ICA methods. Moreover, the results show that DLNN trained with healthy OLTC data produces diagnostically valuable estimates even when fed with a faulty OLTC audio mixture. For that reason, once trained, the DLNN can produce the diagnostic signal estimates from monaural mixtures that can be used with existing vibration-based diagnostic methods. [ABSTRACT FROM AUTHOR]

Line-commutated converters are extensively used as the interface between ac grids and classic HVDC systems. At the inverter side, commutation failure of switches is one of the most common faults that can pose threats to the system operation. Practical and reliable study of such phenomena relies on accurate and efficient converter models for simulations. Recently, a parametric average-value model (PAVM) has been presented for ac–dc rectifiers, which considers the internal faults of the converter. In this paper, the PAVM methodology is extended to the dc–ac inverter systems, including the commutation failure of switches. The proposed PAVM also augments an automatic fault detection technique to determine the faulty switches. Using comprehensive simulation studies, the developed model is verified to accurately predict the commutation failure of switches and reconstruct the waveforms consistent with the detailed switching models of inverters while being computationally more efficient. The proposed PAVM is envisioned to be an efficient and accurate asset for simulation of HVDC systems and inevitable when faults of switches need to be considered. [ABSTRACT FROM AUTHOR]

High penetration level of single-phase solar PVs in low voltage distribution systems has raised concern about the Voltage Unbalance (VU) level. Real-time phase reconfiguration using Dynamic Switching Devices (DSD) has been proposed as a cost-effective solution to mitigate the excessive level of Voltage Unbalance. DSDs are fast power electronics devices that could change the phase connection of a solar PV with minimum disturbances. Most of the proposed methodologies for controlling DSDs are based on a central controller and the assumption of availability of Advanced Metering Infrastructure (AMI) and a communication system. In this paper, we propose a distributed control methodology to control DSDs based on the measurement from the local node only and using the sensitivity of nodal voltage to power injection. Each DSD decides on phase swapping if it rectifies the unbalance index of the local node. We show that decreasing the Voltage Unbalance Factor (VUF) of individual nodes will improve the unbalance situation of the whole feeder. The proposed scheme does not require a communication system nor a central controller. The result of simulations confirms the efficacy of the proposed methodology. [ABSTRACT FROM AUTHOR]

VSC-HVDC systems are being increasingly employed in the power systems. The recently installed HVDC systems have a power capacity similar to traditional power plants. Hence, they are expected to have a similar behaviour as traditional synchronous generators during faults in AC grid, within their limits of course. Recent grid codes require HVDC converter stations to incorporate fault ride-through (FRT) capabilities in order to avoid HVDC converter station disconnection from AC grid for certain fault characteristics. In this paper, two FRT mechanisms are suggested for the two converter stations of an HVDC system. One FRT mechanism is added to the DC voltage control loop of the master converter station, while the other FRT mechanism is added to the active power control loop of the slave converter station. The objective is to ensure the stable operation of the HVDC system during faults that may occur in AC grids located on both sides of the HVDC system. The performance and stability of the suggested FRT mechanisms are tested considering the pre-fault power flow direction and all possible types of balanced and unbalanced faults. Simulation results confirm the effectiveness of the FRT mechanisms and revealed the critical modes during FRT operation. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) and cell-free (CF) massive multiple-input multiple-output (MIMO) are two promising technologies for realizing beyond-fifth generation (5G) networks. In this paper, we study the uplink spectral efficiency (SE) of a practical spatially correlated RISs-aided CF massive MIMO system over Rician fading channels. Specifically, we derive the closed-form expression for characterizing the uplink SE of the system, which shows that increasing the number of RIS elements can improve the system performance. Moreover, the results unveil that the spatial correlation of RIS has a significant impact on the system while leading to the best performance gain at a half wavelength spacing. Finally, the accuracy of our analytical results are verified by Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

Miniaturization and low cost contribute to the development and popularization of wireless power transfer (WPT). Reducing the number of power conversion stages can reduce the volume and cost of the WPT converter, and even make it possible to improve the efficiency. A single-stage WPT converter with constant current (CC) and constant voltage (CV) output and its asymmetric modulation method are proposed in this paper. A direct AC-AC converter is applied to the primary side of the WPT converter to directly convert line-frequency AC to high-frequency AC. The applied direct AC-AC converter that can replace the commonly used multi-stage primary converter reduces the number of circuit devices, thereby reducing the volume and cost of primary converter. The proposed WPT converter can realize zero voltage switching (ZVS) and power factor correction (PFC). In order to achieve CC and CV output, a switchable hybrid compensation topology is applied to the proposed WPT converter. A 720-W experimental prototype was manufactured to verify the rationality of the proposed WPT converter and the correctness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

Mixed-criticality (MC) scheduling becomes popular in real-time systems as it supports different criticality levels in a resource-efficient manner. Although it has been well established (i) how to guarantee MC schedulability offline, existing studies have paid less attention to achieve (ii) how to minimize deadline misses of low-criticality tasks at runtime; in addition, it has not matured yet how to address (ii) without compromising (i). In this paper, we propose $\mathsf{MC{-}FLEX}$ MC - FLEX , which employs a task-level mode transition mechanism (as opposed to system-level one). $\mathsf{MC{-}FLEX}$ MC - FLEX not only determines time instants at which each high-criticality task enters and exits the critical mode in a task level, but also selects time instants and target low-criticality task(s) to be dropped and resumed for each task-level mode switch of individual high-criticality tasks, yielding the achievement of both (i) and (ii). Via simulation results, we demonstrate that the proposed framework reduces the job deadline miss ratio of low-criticality tasks at runtime (by over 54.8% compared to the existing work), without compromising offline MC schedulability. [ABSTRACT FROM AUTHOR]

Erasure coding becomes increasingly popular in distributed storage systems (DSSes) for providing high reliability with low storage overhead. However, traditional random data placement induces massive cross-rack traffic and severely imbalanced load during failure recovery, which degrades the recovery performance significantly. In addition, various erasure codes coexisting in a DSS exacerbates the above problems. In this paper, we propose PDL, a PBD-based Data Layout, to optimize failure recovery performance in DSSes. PDL is constructed based on Pairwise Balanced Design, a combinatorial design scheme with uniform mathematical properties, and thus presents a uniform data layout for mixed erasure codes. Then we propose rPDL, a failure recovery scheme based on PDL. rPDL reduces cross-rack traffic effectively and provides nearly balanced cross-rack traffic distribution by uniformly choosing replacement nodes and retrieving determined available blocks to recover the lost blocks. We implemented PDL and rPDL in Hadoop 3.1.1. Compared with the existing data layout and recovery scheme in HDFS, experimental results show that rPDL achieves much higher recovery throughput, $6.27\times$ 6. 27 × on average for single-node failures, $5.14\times$ 5. 14 × for multi-node failures and $1.48\times$ 1. 48 × for single-rack failures, respectively. It also reduces degraded read latency by an average of 62.83 percent, and provides better support to front-end applications in case of component failures. [ABSTRACT FROM AUTHOR]

This paper proposes a novel data driven framework for detecting topology transitions in a distribution network. The framework analyzes data from phasor measurement units (PMUs) and relies on the fact that changes in network topology results in changes in the structure and admittance of the network. Using voltage and current phasors recorded by PMUs, the proposed method approximates network parameters using an ensemble-based deep learning model and thus, it does not require any knowledge of network parameters and load models. Using the prediction error of the proposed model, a connectivity matrix which shows the status of switches is constructed. In contrast to other methods, this proposed framework does not require a library of voltage and current transients associated with possible network transitions. It can also detect simultaneous switching actions and is robust to noise and load variations. The model yields a lower error detection rate, and its performance is validated using a modified version of the IEEE 33 bus network and a real feeder located in Queensland, Australia, under full and partial observability conditions. The proposed model has also been compared with another data driven method in terms of inference time and error detection rates. [ABSTRACT FROM AUTHOR]

Free viewpoint videos (FVVs) provide immersive experiences for end-users, and they have been applied in many applications, such as movies, sports, and TV shows. However, the development of quantifying the quality of experience (QoE) of FVVs is still relatively slow due to the high costs of data collection and limited public databases. In this paper, we conduct a comprehensive study on FVV QoE. First, we construct the largest, to the best of our knowledge, FVV QoE database called Youku-FVV from two complex real scenarios, i. e., entertainment and sports. Specifically, Youku-FVV originates from the videos captured by dozens of real cameras arranged annularly. We use these videos to generate virtual viewpoints, which make up FVVs together with real views. In constructing the FVV QoE database, we consider both internal and external influencing factors of QoE, which correspond to FVV generation and playback, respectively. Besides, we make an initial attempt to train an efficient no reference FVV QoE prediction model using this database, where several sparse frame sampling strategies are validated. And we demonstrate the feasibility of striving for the balance between effectiveness and efficiency of FVV QoE prediction. The proposed FVV QoE database and source codes are publicly available at https://github.com/QTJiebin/FVV_QoE [ABSTRACT FROM AUTHOR]

This paper describes new, simple, recursive methods of construction for orientable sequences, i.e. periodic binary sequences in which any $n$ -tuple occurs at most once in a period in either direction. As has been previously described, such sequences have potential applications in automatic position-location systems, where the sequence is encoded onto a surface and a reader needs only examine $n$ consecutive encoded bits to determine its location and orientation on the surface. The only previously described method of construction (due to Dai et al.) is somewhat complex, whereas the new techniques are simple to both describe and implement. The methods of construction cover both the standard ‘infinite periodic’ case, and also the aperiodic, finite sequence, case. Both the new methods build on the Lempel homomorphism, first introduced as a means of recursively generating de Bruijn sequences. [ABSTRACT FROM AUTHOR]

In this paper, we present two new families of APN functions. The first family is in bivariate form $\big (x^{3}+xy^{2}+ y^{3}+xy, x^{5}+x^{4}y+y^{5}+xy+x^{2}y^{2} \big)\,\,\vphantom {_{\int _{\int }}}$ over ${\mathbb F}_{2^{m}}^{2}$. It is obtained by adding certain terms of the form $\sum _{i}(a_{i}x^{2^{i}}y^{2^{i}},b_{i}x^{2^{i}}y^{2^{i}})$ to a family of APN functions recently proposed by Gölo&gcaron;lu. The $\vphantom {_{\int _{\int }}}$ second family has the form $L(z)^{2^{m}+1}+vz^{2^{m}+1}$ over ${\mathbb F}_{{2^{3m}}}$ , which generalizes a family of APN functions by Bracken et al. from 2011. By calculating the $\Gamma $ -rank of the constructed APN functions over ${\mathbb F}_{2^{8}}$ and ${\mathbb F}_{2^{9}}$ , we demonstrate that the two families are CCZ-inequivalent to all known families. In addition, the two new families cover two known sporadic APN instances over ${\mathbb F}_{2^{8}}$ and ${\mathbb F}_{2^{9}}$ , which were found by Edel and Pott in 2009 and by Beierle and Leander in 2021, respectively. [ABSTRACT FROM AUTHOR]

Due to the forecasted fast increasing cellular traffic and the already highly congested licensed spectrum, it is critical to exploit and utilize the unlicensed spectrum resources for the fifth-generation (5G) and beyond networks. A challenging problem is the coexistence of 5G and other networks with fair, reliable, and efficient sharing of the unlicensed spectrum. In this paper, we propose a blockchain-enhanced distributed spectrum sharing scheme for coexisting multiple operators and multiple WiFi APs. We design a novel lightweight and efficient consensus mechanism, named Proof of Strategy (PoG). In this consensus mechanism, the problem of spectrum sharing is used as a consensus puzzle, and the part of the unlicensed spectrum is used as the ‘fee’ of miners. With such a design, the computing overhead of the consensus process is expected to be reduced significantly. We develop a non-cooperative game to analyze the behavior of the miners and obtain a symmetric Bayesian Nash equilibrium under the uniform distribution of mining cost estimation. It can be found mathematically and experimentally that the strategy of the winner tends to maximize the system revenue by sharing the unlicensed spectrum resource. Furthermore, to reduce the impact of heavy interactions on system throughput, the operation of WiFi APs in the proposed scheme can be adaptively switched between ‘contention mode’ and ‘blockchain mode’ according to the network traffic load. The dynamic behavior is constructed as an evolutionary game, and the existence and uniqueness of equilibrium points are proved by theoretical analysis. Simulations demonstrated the fairness and effectiveness of the proposed blockchain-based scheme and the mode switching method for distributed spectrum sharing by heterogeneous wireless networks. [ABSTRACT FROM AUTHOR]

The use of the emerging hybrid analog-digital structure for future millimeter-wave communications has attracted much attention. Although this structure can reduce the power consumption considerably, the spatial covariance matrix (SCM), as the core of subspace-based direction of arrival (DOA) estimation algorithms, cannot be obtained directly. The beam sweeping algorithm (BSA) was proposed for SCM reconstruction from compressed measurements. However, the BSA is computationally intensive owing to the high-dimensional matrix-to-matrix multiplication and matrix inversion. To address this issue, a BSA algorithm with high accuracy and low computational-cost using the submatrix multiplication (BSASM) is proposed in this paper. By appropriately adjusting the weight, which consists of a switch and a phase shifter, connected to each antenna, the SCM can be accurately reconstructed with low-dimensional matrix-to-vector multiplication and 2-dimensional matrix inversion, thus reducing the computational-cost significantly. After SCM reconstruction, various DOA estimation algorithms can be exploited to obtain the DOA information. Simulation experiments are conducted to verify the performance of the proposed algorithm. The results indicate that using a substantially lower computational-cost, BSASM can reconstruct SCM more accurately than BSA. [ABSTRACT FROM AUTHOR]

The effect of reduction in the terminal voltage of a grid-tied inverter together with minimization in total harmonic distortion (THD) of terminal voltage and current, in the presence of dead-band in the switching remains always challenging for the researchers. With high switching frequency, this issue increases by many folds. The grid-tied inverter used for harmonic compensation acts as a shunt active power filter (SAPF). The implementation of the dead-band elimination technique is based on output current polarity detection, suffers from multiple zero-crossing due to the generation of high frequency switching harmonics during SAPF operation. This paper deals with a dead band elimination methodology together with harmonic compensation using SAPF under non-linear and unbalanced loading conditions. Here, SAPF uses a dual fundamental component extraction (DFCE) scheme with modified complex coefficient filter (MCCF) to extract fundamental components for reference current generation to implement an indirect current control PWM scheme. MCCF extracts fundamental components even in the presence of dc offset and unbalancing at the input. For incorporating dead-band elimination in control, exact polarity detection is done separately through SAPF output current estimation using sensed load current, and modified CCF computed reference source current. Since the estimated SAPF output current contains no high-frequency switching harmonics, the dead-band elimination technique can be correctly implemented. To synchronize the zero-crossing of the estimated and actual SAPF current, an adaptive delay control is used. The proposed MCCF based control logic’s performance together with the dead-band elimination technique is validated for SAPF operating under non-linear, unbalance, and dynamic load conditions. The proposed dead-band elimination scheme based SAPF model is developed and simulated using MATLAB/ SIMULINK. The simulation results show a significant reduction in source current harmonics due to the elimination of odd harmonic injection into the system by incorporating dead-band elimination in SAPF operation. The real-time simulation of the proposed method is also validated using OPAL-RT OP4510 real-time platform. [ABSTRACT FROM AUTHOR]

The missing capability of DC fault current limitation is an inherent disadvantage in the typical half-bridge modular multilevel converter (MMC), which restricts its application in long-distance high voltage direct current (HVDC) systems. The full-bridge submodule (FBSM) and clamped double submodule (CDSM) topologies allow for fault current self-clearing, but also suffer from additional hardware cost and power losses. In this paper, an improved submodule topology utilizing the new reverse-blocking insulated gate bipolar transistor (RB-IGBT) is proposed to improve system economy without compromising its performance. The operating principles and DC fault characteristics of the proposed topology are analyzed in details, including comparison with various topologies in terms of cost, losses, fault current clearing speed and thermal. Compared with the traditional CDSM topology, the proposed RBSM can clear DC faults faster with reduced cost of switching devices. A DC fault protection strategy for MMC-HVDC system is also presented. Simulation results under normal operating, permanent and transient fault conditions are carried out to verify the effectiveness of the proposed topology. [ABSTRACT FROM AUTHOR]

The conventional model predictive power control suffers from heavy computational burden and large power ripple. To address the problem, this paper proposes a simplified three-vector-based model predictive direct power control, which can greatly optimize the control set. Firstly, a switching table is designed to exclude the redundant virtual voltage vectors (VVs). Only half of the candidate VVs are retained. Then, the effect of each VV on power is analyzed in detail. The deviation of reactive power is used as the evidence to further simplify the control set. In this way, the prediction behavior is reduced from 12 to 2, which effectively reduces the computational burden. In addition, the concept of power deadbeat is employed to determine the duty cycles of the two virtual VVs and one zero VV. Thus, the power ripples and current harmonics can be considerably suppressed. With this proposed method, the calculation complexity is reduced, and the steady-state performance is improved. The simulation and experimental results are given to verify the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a finite-control-set model predictive direct torque control (FCS-MPDTC) method is proposed to reduce the torque ripple of a segmented switched reluctance motor (SSRM) at the low-speed stage. Firstly, the prediction dynamic model is established, and the phase torque can be predicted by detecting phase current and rotor position signals. Then, the principle of power converter and selection of voltage vectors are introduced and presented. Considering torque ripple reduction, flux tracking performance and copper losses reduction, the cost function with phase torque, the amplitude of flux linkage and phase current, is established to select optimal voltage vector to control the power converter. In addition, the torque sharing function (TSF) is employed to distribute total torque to phase torque for further torque ripple reduction. Finally, the direct torque control (DTC) is selected as the comparison method, performance of MPDTC is verified by simulation and experiment results. It can be found that the proposed MPDTC can achieve lower torque ripple and copper losses, and high robustness. [ABSTRACT FROM AUTHOR]

This paper presents a dual-hysteresis band control method for multi-drive systems based on a nine-switch inverter. The drive system contains two independent three-phase induction motors fed by a nine-switch inverter. Independent control of torque, speed, and stator current of two load stages is achieved. The proposed strategy offers a reliable control operation of both induction machines under individual load profiles. Instead of using independent sets of three-phase voltage source converters, the nine-switch inverter is used to drive separate machines. Thus, the volume and size of the power stage are noticeably reduced due to the use of fewer semiconductors. The theoretical concept and design steps of the proposed method are presented. The performance of the closed-loop independent motor control scheme is experimentally validated using a 3.2 kW lab-scaled nine-switch inverter prototype and Altera Cyclone IV Field-programmable gate array. [ABSTRACT FROM AUTHOR]

In this paper, a circulating-current-excited switched reluctance generator system with the diode rectifier is comparatively studied with a field-current-separated switched reluctance generator. By using a DC power source connected in series with the winding to provide the circulating current, a controllable excitation field is established in the proposed generator. To highlight the influence of this DC voltage source, the injected field current of the field-current-separated generator is kept the same as the circulating current of the circulating-current-excited generator. Then, both advantages and disadvantages of the generators are summarized. The circulating-current-excited switched reluctance generator system inherits both the advantages of good reliability of the separated-winding generator by using the diode rectifier and low copper loss of the integrated-winding machine by combining the AC and DC current in one set of windings. Furthermore, two more practically conventional field-current-separated generators are also compared with the proposed generator in terms of the external characteristics. These two conventional generators have different winding configurations. At last, the analysis is verified by experiments. [ABSTRACT FROM AUTHOR]

Consistent distribution of shadows on the surface of the shaded PV array enhances the array’s harvested capacity. Therefore, in this paper, an Image processing inspired Chaos Map reconfiguration is proposed to mitigate the effect of shading. The proposed reconfiguration is aimed at achieving uniform row current when compared with the other conventional configurations with physical relocation of panels without changing the electrical connections. The efficacy of the proposed method is tested on Short Wide, Short Narrow, Long Wide and Long Narrow shading conditions on the basis of both software and hardware results. The proposed method enhanced output metrics under partially shaded conditions and gives most effective dispersion of shading over entire PV array. This proposed method is also compared with other existing static reconfiguration techniques for the above said shading conditions and the results show tremendous increment in output power under both hardware and software platforms. The results replicate that the proposed configuration can be generalized for any size of an SPV Array and output parameters can be enhanced by physical relocation under any sort of shading conditions. [ABSTRACT FROM AUTHOR]

The main challenges for Finite Set-model Predictive Torque and Flux Control (MPTC) include huge calculation amount, large torque ripple, and the selection of weighting factor. To deal with these challenges and achieve the fastest torque response, a novel MPTC strategy with virtual voltage vector-based pattern is proposed in this paper. In each control period, a desired voltage vector is computed based on the maximum torque variation rate. The virtual desired voltage vector is combined by using basic voltage vectors with the minimum switching times. The switching pattern between two adjacent control periods is optimized by using a cost function in realtime. Compared with the traditional MPTC approach, the novel strategy has multifaceted improved performances: faster torque response, less calculation amount, lower switching frequency, reduced torque ripple, higher efficiency and no weighting factor. The proposed method is contrasted with traditional MPTC method and a well-known generalized multiple-vector-based MPC method via experiments. [ABSTRACT FROM AUTHOR]

Modern-day graph workloads operate on huge graphs through pointer chasing which leads to high last-level cache (LLC) miss rates and limited memory-level parallelism (MLP). Simultaneous Multi-Threading (SMT) effectively hides the memory access latencies for multi-threaded graph workloads provided that sufficient threads are supported in hardware. Unfortunately, providing a sufficiently large number of physical threads incurs an unjustifiably high hardware cost for commodity SMT processors which typically implement only two physical hardware threads. Ideally, we would like to achieve aggressive-SMT performance when running graph workloads on modest commodity processors. In this paper, we propose Virtualized Multi-Threading (VMT), a low-overhead multi-threading paradigm for accelerating graph workloads on commodity processors. Unlike prior multi-threading paradigms, VMT virtualizes both the physical hardware threads and the architecture state: VMT maps a large number of logical software threads to a small number of physical hardware threads, while maintaining the architecture state of the logical threads in the processor's cache hierarchy. Implemented on top of a quad-core 2-way SMT processor, VMT achieves an average speedup of 1.74× for a set of representative graph workloads, while incurring minimal hardware cost (195 bytes per core to support up to 32 logical threads). VMT's low hardware cost paves the way for implementation in commodity processors. [ABSTRACT FROM AUTHOR]

Malware developers continually attempt to modify the execution pattern of malicious code hiding it inside apparent normal applications, which makes its detection and classification challenging. This article proposes an ensemble detector, which exploits the capabilities of the main analysis algorithms proposed in the literature designed to offer greater resilience to specific evasion techniques. In particular, the article presents different methods to optimally combine both generic and specialized detectors during the analysis process, which can be used to increase the unpredictability of the detection strategy, as well as improve the detection rate in presence of unknown malware families and provide better detection performance in the absence of a constant re-training of detector needed to cope with the evolution of malware. The paper also presents an alpha-count mechanism that explores how the length of the observation time window can affect the detection accuracy and speed of different combinations of detectors during the malware analysis. An extended experimental campaign has been conducted on both an open-source sandbox and an Android smartphone with different malware datasets. A trade-off among performance, training time, and mean-time-to-detect is presented. Finally, a comparison with other ensemble detectors is also presented. [ABSTRACT FROM AUTHOR]

Since the wide application of virtual synchronous generators (VSGs), the power grid faces great challenges in the safe and stable operation due to their limited thermal capacity and weak anti-disturbance ability. During transient period, for example, a fault occurs in the transmission line, the VSG may lose the transient angle stability and provoke the current hard limit. Even if the fault is cleared by tripping of line, it still faces the problem of instability and voltage dips. To address this problem, in this paper, the post-fault large-signal model of VSG is derived first via the travelling waves based fault information acquisition. Subsequently, with the effect of both active and reactive power loops taken into account, a two-stage simultaneous control scheme is proposed for improving the transient stability of VSG, while considering the current limitation during fault state and voltage support after fault clearance. This method is fulfilled by mode switching and an additional feedback control based on the fault signal. Finally, the effectiveness of the proposed method under both symmetrical and asymmetrical faults is verified. Moreover, the application of the proposed method in a multiple VSGs system is also verified. Besides, the robustness to parameter mismatch and the feasible operating region for the method are discussed. [ABSTRACT FROM AUTHOR]

The reliable operation of a power distribution system relies on a good prior knowledge of its topology and its system state. Although crucial, due to the lack of direct monitoring devices on the switch statuses, the topology information is often unavailable or outdated for the distribution system operators for real-time applications. Apart from the limited observability of the power distribution system, other challenges are the nonlinearity of the model, the complicated, unbalanced structure of the distribution system, and the scale of the system. To overcome the above challenges, this paper proposes a Bayesian-inference framework that allows us to simultaneously estimate the topology and the state of a three-phase, unbalanced power distribution system. Specifically, by using the very limited number of measurements available that are associated with the forecast load data, we efficiently recover the full Bayesian posterior distributions of the system topology under both normal and outage operation conditions. This is performed through an adaptive importance sampling procedure that greatly alleviates the computational burden of the traditional Monte-Carlo (MC)-sampling-based approach while maintaining a good estimation accuracy. The simulations conducted on the IEEE 123-bus test system and an unbalanced 1282-bus system reveal the excellent performances of the proposed method. [ABSTRACT FROM AUTHOR]

Volt/VAr Optimization (VVO) is becoming increasingly crucial in distribution management systems with renewable sources that require setting their reactive power in coordination with legacy voltage and reactive power control devices. This paper presents a VVO method that operates in complex variables based on the Wirtinger calculus; it employs a penalty method that keeps voltage magnitudes and controller parameters within limits together with a probabilistic rounding technique for handling switched device variables. The complex variable implementation permits using the compensation technique when solving the Karush-Kuhn Tucker (KKT) system, thus achieving a significant speedup due to limiting the number of linear system factorizations. The proposed method is contrasted with a classical VVO implementation employing discrete coordinate search from the current operating point and an enhanced version that uses sensitivity information. Numerical results on distribution networks having up to 3147 nodes show that the proposed method is significantly faster than classical methods and gives operating points free of voltage magnitude violations and lower power loss. [ABSTRACT FROM AUTHOR]

The synchronization requirement is a bottleneck of many distributed optimization algorithms, particularly for solving problems with computationally heterogeneous subproblems and during the occurrence of communication failure/delay. This paper presents a double-loop learning-aided asynchronous alternating direction method of multipliers (LA-ADMM) that has information prediction capability and handles a considerable level of asynchrony between subproblems. A momentum-extrapolation prediction-correction technique is developed to enable subproblems to predict their neighbors missing shared variable information instead of using the latest received values. An online streaming-based anomaly classification is designed to observe the performance of predicted data and control Lagrange multipliers update over the course of iterations. The proposed LA-ADMM reduces under-utilization of computation resources, especially if subproblems are computationally heterogeneous. This algorithm also enhances distributed optimization robustness against communication failure/delay that may result in a considerable level of asynchrony between subproblems. LA-ADMM is applied to solve the optimal power flow problem for several test systems. Promising results are obtained as compared to the classical synchronous ADMM and asynchronous ADMM without the anomaly switch control. [ABSTRACT FROM AUTHOR]

This paper proposes an aggregation method for proliferated small-size data networks to apply data networks’ spatial load regulation potentials for demand response (DR). First, each data network is modeled as a virtual power network, where the Internet data center load is modeled as a set of linear constraints. Second, an aggregated virtual power network (AVPN) is proposed to demonstrate the aggregation method potentials in power systems and to emulate DR applications for multiple virtual power networks in wholesale markets. The coupling of AVPN and power network would develop a linear load model for an aggregated Internet data center. Furthermore, the supply curves representing AVPN DR are formulated to capture heterogeneous regulation costs of virtual power networks, which guarantees limited welfare losses in AVPN DR compared with the individual DR of virtual power networks. Last, an AVPN DR implementation mechanism is deduced to reveal the potentials of the aggregation method in power system applications. Simulation results verify the efficiency of the proposed aggregation method for spatially-coupled DR resources, where, the computing time of the AVPN-based OPF without welfare loss is reduced by 99.94% when there are 3×104 data networks. The proposed aggregation strategy implies that the proliferation of small-size data networks will offer a reasonable DR for enhancing the power system operation in wholesale electricity markets. [ABSTRACT FROM AUTHOR]

A multi-level boost topology based on a flying capacitor is compared in this work with the hybrid, multi-level, partial power processing topology already presented in the literature for use as a highly efficient and compact dc/dc stage in 1500-V, two-stage, grid-connected PV systems. Different variations of the resonant stage of the hybrid topology are analyzed and compared in terms of losses, volume and complexity. Full multivariable optimization is conducted for the multi-level boost topology with different number of levels and for all the analyzed variations of the resonant stage of the hybrid topology. Appropriately rated new classes of 650-V and 900-V WBG devices are included in the optimization algorithm. It is concluded that due to the dominant conduction losses and gap in the voltage rating of the commercially available WBG devices between 650V and 200V, increase of the number of levels over 4 leads to the deteriorated loss and volume performances. All the analysis related to the resonant stage of the hybrid topology is confirmed by detailed and comprehensive measurements of two prototypes of 4kW of nominal and 7kW of maximal power. Additionally, all the loss models applied in the optimization algorithms presented in this paper are confirmed by detailed measurements, thermal calibration and finite element thermal simulations of the wide bandgap devices and inductor designs employed in this work. [ABSTRACT FROM AUTHOR]

The aim of this article is to develop a new cooperative path following control scheme for a team of autonomous underwater vehicles (AUVs) which track one curve with nonlinear uncertainties. Individual path-following controllers are designed to guarantee that each AUV meets the desired tracking performance. For the cooperative path following, a containment control approach is incorporated into the design, where each AUV is forced to evenly disperse on a path that is parameterized by a continuous variable over a communication network. The main features of the paper that unlike the existing designs are that: first, by employing the command filtered control technique, the assumption of second-order derivative of the reference path is removed. Second, a globally uniformly ultimately bounded (GUUB) path following control structure is proposed that enables two kinds of controllers to switch under different cases. Third, coordination between multiple AUVs is achieved through a containment design, and a path variable containment cooperative path following controller is derived that enables multiple AUVs to be evenly dispersed and guided by the virtual leaders. Finally, the stability analysis and simulation example are given to verify the proposed control strategy. [ABSTRACT FROM AUTHOR]

High-performance multicast-enabled packet forwarding engines (PFEs), as an essential component of high-end switches, use a polynomial-time membership query algorithm to determine which port(s) the data packet should be forwarded. The currently widely used query algorithm is Bloom Filter (BF), which has been proven to have many fatal flaws. Another error-free membership query algorithm includes Scalar-pair Vectors Routing Forwarding (SVRF), Fractional-N Scalar-pair Vectors Routing Forwarding (Frac-N SVRF), and the Per-Port Prime Filter Array (P3FA) also have some shortcomings in space and time efficiencies. In this paper, we proposed a hybrid strategy: Divaricate Heterogeneous SVRF (DH-SVRF) scheme, which based on the P3FA and Frac-N SVRF, which randomly divides all member ships into N groups, and each group has the same structure and is independent of each other to obtain higher time efficiency and space utilization. Finally, we also discussed the selection of the optimal egress-diversity threshold. Through mathematical modeling and simulation, we validate that the proposed DH-SVRF scheme is superior to the SVRF/Frac-N SVRF and traditional BF in terms of scalability, space utilization, and time efficiency in specific conditions such as appropriate egress-diversity thresholds. [ABSTRACT FROM AUTHOR]

The ITER magnet system will operate in extremely severe conditions, which impose high requirements for mechanical and dielectric strength of the electrical insulation of the superconductive coils. Only monolithic structure obtained during the VPI procedure is capable to provide the required mechanical and dielectric strength for electrical insulation. To provide the qualitative insulation, a temperature non-uniformity of the electrical insulation should be kept within the range of [−5, +5 °C] and [−0, +20 °C] during filling with epoxy compound and its curing, respectively. The PF1 coil is about 150 t in weight and consists of materials with different thermal conductivity. Besides, a complicated geometry of the coil adds complexity to VPI. Since the VPI is usually a long-term and irreversible process (within pot life of compound), the whole process should be controllable. The paper describes the developed calculation model of the ITER PF1 coil and presents the results of numerical simulation of this model at VPI of electrical insulation. The completed VPI of the ITER PF1 coil has verified the proposed method for coil heating and proved an acceptable agreement between the calculated and measured temperature distributions throughout the VPI procedure. [ABSTRACT FROM AUTHOR]

In this paper, elliptically contoured (EC) distributions are used to model outlier-contaminated measurement noises. Exploiting a heuristic approach to introduce an unknown parameter, we present an analytical update form of the joint posterior probability density function of the state vector and auxiliary random variable, from which a novel robust EC distributions-based Kalman filtering framework is first derived. To illustrate the effectiveness of the proposed framework, the convergence, robustness, optimality and computational complexity analyses of the proposed method are then given. In addition, to cope with complex noise environments, the interaction multiple model is employed to achieve the adaptive selection of EC distributions such that well-behaved estimation performance can be obtained for different noise cases. Simulation results demonstrate the validity and superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes an optimization model for the joint planning of sectionalizing switches (SSs), including remote-controlled switches (RCSs) and manual switches (MSs), and tie lines among distribution feeders. Considering a flexible installation of SSs and tie lines (i.e., deployment of SSs on both sides of a line and construction of external and internal tie lines on of a feeder), this model is conducive to developing an economic investment scheme while preserving the expected energy not supplied (EENS) reliability criterion. First, the minimum total cost of investment, maintenance and penalty for EENS is chosen as the objective function. Next, a route analysis method is introduced to analyze particular performances of different deployment schemes for RCSs, MSs, external tie lines and internal tie lines. Considering the differences between overhead lines and underground cables, the lower bound of the restoration time of each load is estimated based on optimal restoration strategies in different fault scenarios. Then, the joint planning problem is formulated as a mixed-integer linear programming (MILP) model with the aid of algebraic operations to calculate the global optimal solution. The effectiveness of the proposed model is verified for several cases in a 54-node distribution system. Numerical results indicate that the proposed planning solution merits higher economy and lower EENS as compared to the schemes offered by other prevalent methods. [ABSTRACT FROM AUTHOR]

In this paper, the state estimation problem for singularly perturbed switched complex dynamic networks (CDNs) is addressed, in which the persistent dwell-time (DT) switching mechanism is employed to depict the switchings among parameters of each node. In the aforementioned switching mechanism, the concept of stage consisting of the persistent portion and the DT portion is introduced. Based on the singular perturbation theory, a two-time-scaling variables containing fast and slow states are taken into account on the CDNs simultaneously, which make the constructed networks more realistic. Furthermore, the main aim is to design a mode-dependent estimator to track the state information that cannot be directly obtained and further ensures the global uniform exponential stability of the investigated systems with a generalized dissipativity property. Some sufficient criteria on the existence of the desired mode-dependent state estimator are established by utilizing a modified matrix decoupling method. Finally, the availability of the estimator design procedures is verified by a simulation example. [ABSTRACT FROM AUTHOR]

Three-port converters with high voltage gain are desirable solutions for integrating renewable energy and energy storage devices into high voltage dc bus. A high gain three-port converter with soft switching is proposed in this paper, which can realize zero voltage switching for all switches and zero current switching for all diodes in various operating modes. Single coupled inductor is used to achieve high voltage gain and to reduce the voltage stress of switches so that switches with low on-resistance can be selected to reduce the conduction loss. In addition, the advantages of fewer components, higher voltage gain, and very low switch voltage stresses make the proposed converter more suitable for application in renewable energy systems than similar solutions. Various operating modes, performance analysis, design considerations, efficiency analysis, and control method of the proposed converter are discussed. A laboratory prototype with 30 V renewable energy source, 48 V energy storage device and 400 V output is designed to verify the performance of the proposed three-port converter. [ABSTRACT FROM AUTHOR]

This paper investigates the secrecy performance of a spectrum sharing network, where ${N}$ legitimate source-destination pairs orderly access the shared spectrum for communication, while an eavesdropper (E) attempts to tap the legitimate information transmission. To improve the physical layer security, we propose two jamming strategies that can intelligently switch between jamming and non-jamming, namely, suboptimal jammer selection (SJS) scheme and optimal jammer selection (OJS) scheme. Specifically, when a user pair is assigned to access the shared spectrum, another source is chosen as a friendly jammer in order to create intentional interference at E. For the purpose of comparison, we present the non-jammer selection (NJS) scheme as a benchmark. Analytical closed-form secrecy outage probability expressions of NJS, SJS and OJS schemes are derived over Nakagami- ${m}$ fading channels. We further present an asymptotic secrecy outage probability analysis to evaluate the secrecy diversity gain performance of NJS, SJS and OJS schemes. Numerical results show that the secrecy outage probability performance of OJS scheme is better than SJS and NJS schemes in the low average channel power gain ${\mathop \Omega \nolimits _{D} }$ region. Furthermore, the secrecy outage probabilities of NJS as well as SJS and OJS schemes converge to each other with the increase of ${\mathop \Omega \nolimits _{D} }$ , due to the fact that the OJS and SJS scheme will switch to NJS scheme when ${\mathop \Omega \nolimits _{D} }$ tends to infinity. [ABSTRACT FROM AUTHOR]

In subway systems, increasing attention has been paid to improve energy efficiency due to remarkable energy consumption for rail transportation operation. The optimization of single-train driving control and multi-train operation synergy are two critical and closely related aspects for energy saving, but they are rarely solved in an integrative manner. The comprehensive study on these two aspects is a complex, large-scale, multi-variable and constrained task, which involves nested, coupled and mutual-input optimization processes. This paper proposes an energy-efficient integrated model, which includes optimizing single-train operation control in an inner model and multi-train operation synergy, committing to the utilization of regenerative braking energy (RBE) in an outer model. A parallelized particle swarm optimization based on Map-Reduce (PPSO-MR) algorithm is proposed to solve the integrated model to reduce the execution time. Two concepts of temporal-spatial record and time shift are introduced to derive the movement of a train at inter-stations for the operation adjustment of multiple trains on a subway line. Experimental results show that the proposed control model solved by the holistic optimization approach can achieve lower energy consumption with fast execution time. This study provides the novel model and algorithm to obtain energy-saving schedules serving the multi-train operation coordination. [ABSTRACT FROM AUTHOR]

Two-stage AC-DC converters are considered as a prominent solution for DC-type electric vehicle (EV) chargers. However, this kind of architecture suffers from high switching losses with large heatsink and DC-link capacitor volume. To relieve this issue, this paper presents a new hybrid modulation for DC-type EV chargers, where a two-phase clamped discontinuous pulse-width-modulation (DPWM) in the front-end circuit is cooperated with the variable frequency triangular-current-mode (TCM) zero voltage switching (ZVS) or its simplified implementation, i.e., boundary-ZVS (B-ZVS) strategy, in the back-end circuit. The former can stop the switching actions in the front-end stage during two-thirds of the grid period, while the AC currents are at their highest values, which can yield to the best switching loss reduction and deliver high power factor operation. Besides, TCM-ZVS or B-ZVS modulations can achieve ZVS turn-on action for all semiconductors during all operating range in the DC-DC stage to further reduce the power losses on the semiconductors. With such characteristics, the proposed strategies can reduce the switching losses of the system to the best extent, and thus allow an enhancement of the system power density by improving the power conversion efficiency. The proposed strategy is described, analyzed, validated, and benchmarked in a 5 kW SMD SiC MOSFET-based two-stage AC-DC converter. A 99% power efficiency can be achieved with the solution implementing the TCM-ZVS strategy at an output voltage of 400 V and rated power. [ABSTRACT FROM AUTHOR]