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Service restoration is one of the critical functions to enable the future self-healing distribution system. To restore the distribution system in a timely and reliable manner, the realistic system operating conditions need to be accurately characterized. In this paper, two main factors that have great impacts on distribution system restoration (DSR) in practice are investigated. First, cold load pickup (CLPU), generally caused by thermostatically controlled loads (TCLs), is a common phenomenon after an outage and shaped by the outage duration. However, the time-dependent behaviors of CLPU are rarely considered in literature. In this paper, the operating state evolution of TCLs after an outage is analyzed to characterize time-dependent CLPU. And the time-dependent CLPU is analytically embedded in DSR to accurately represent the actual behaviors of the restored loads. Second, it is difficult to predict loads that fluctuate during DSR due to the lack of real-time measurement data. Accordingly, a robust DSR based on the information gap decision theory (IGDT) is proposed to address this challenge, fully considering the uncertainty of CLPU. The proposed models are tested in IEEE 13-node and 123-node test feeders. Simulation results demonstrate that the time-dependent CLPU model and the uncertainty modeling of CLPU can accurately capture the actual behaviors of loads with TCLs after an outage, which greatly improves DSR decisions in practice. [ABSTRACT FROM AUTHOR]

This paper presents a new soft switching high voltage gain interleaved dc-dc converter with a three-windings coupled inductor for a fuel cell vehicle. Two interleaved and intercoupled boost cells are connected by the input parallel and output series (IPOS) configuration, realizing low input current ripple and high voltage gain simultaneously. All power switches can operate under soft switching conditions by only adding a simple auxiliary circuit composed of one auxiliary inductor and one power switch. Besides, the auxiliary inductor is coupled with the main inductors, which results in a rapid zero convergence of the auxiliary current and a small conduction loss of the auxiliary circuit. The operating principle, steady state characteristic, comparison with other converters, and parameter design are analyzed in this paper. Finally, the main characteristics of the proposed converter are verified by a 1-kW laboratory prototype. [ABSTRACT FROM AUTHOR]

Since the inherent nature of many applied high-technological systems and networks possesses switching behaviors, modeling, controlling, and stabilizing problems of the switching plants are becoming as the important research scenarios in the current literature. Moreover, consideration of the effects of mismatching uncertainties along with matching uncertain parts as well as unknown dynamics is a significant topic in the control engineering community. As a result, this paper is dedicated to the controlling problem of partially unknown nonlinear switched systems whose dynamics are perturbed by both matched and mismatched uncertainties. In addition, since the existence of gain deviations in real-world implementations of physical actuators can lessen the control act of the switching system, this paper handles the corresponding gain variations in the control inputs via some adaptation variables. In the design procedure, no limiting supposition is made for the switch signal of the switched plant. The proposed control algorithm is based on the variable structure control theory in which the selected sliding surface is able to deal with mismatching uncertainties and the deriving control law is robust against the lumped uncertain components. As a contribution, the Lyapunov functions are built such that not only to provide an asymptotic stable system but also to assure the global (practical) finite-time stability of the equilibrium state of the final closed-loop cascade switched plant. The robust performance of the developed control strategy is confirmed via two illustrative examples. [ABSTRACT FROM AUTHOR]

In conventional hybrid beamforming approaches, the number of radio-frequency (RF) chains is the bottleneck on the achievable spatial multiplexing gain. Recent studies have overcome this limitation by increasing the update-rate of the RF beamformer. This paper presents a framework to design and evaluate such approaches, which we refer to as agile RF beamforming, from theoretical and practical points of view. In this context, we consider the impact of the number of RF-chains, phase shifters’ speed, and resolution to design agile RF beamformers. Our analysis and simulations indicate that even an RF-chain-free transmitter, which its beamformer has no RF-chains, can provide a promising performance compared with fully-digital systems and significantly outperform the conventional hybrid beamformers. Then, we show that the phase shifter’s limited switching speed can result in signal aliasing, in-band distortion, and out-of-band emissions. We introduce performance metrics and approaches to measure such effects and compare the performance of the proposed agile beamformers using the Gram-Schmidt orthogonalization process. Although this paper aims to present a generic framework for deploying agile RF beamformers, it also presents extensive performance evaluations in communication systems in terms of adjacent channel leakage ratio, sum-rate, power efficiency, error vector magnitude, and bit-error rates. [ABSTRACT FROM AUTHOR]

This paper proposes a model predictive current control (MPCC) method of six-phase permanent magnet synchronous hub motor (PMSHM) using auxiliary voltage vectors. First of all, 26 voltage vectors can be obtained from the switching states of six inverters, and 24 auxiliary voltage vectors can be generated by combining them. Second, four virtual voltage vectors can be found through the required locations, and the two vectors with the lowest cost will be selected by cost function. Then, additional current error correction module can better track the current. Finally, the proposed method is compared with the conventional MPCC method and another method with virtual voltage vectors. The innovation of this paper is that the recombination of vectors can better track and predict the current. A current error compensation module is added to reduce the error between the actual current and the predicted current. And the experimental results show that the proposed method has better performance such as smaller torque ripple and current THD both in steady and dynamic states. Finally, the strategy proposed in this paper was applied to the vehicle model through HIL test platform. The possibility of applying the strategy proposed in this paper to pure electric vehicles was verified under New European Driving Cycle (NEDC). [ABSTRACT FROM AUTHOR]

This paper summarizes the work performed by the Task Force —within Performance Characteristic Subcommittee of IEEE PES Transformers Committee— to investigate potential revisions to IEEE Std C57.142-2010. Although the scope of this document does not implicitly exclude HV and EHV systems, the existing document primarily includes examples and information on distribution voltage systems. A Task Force was formed to investigate the need to include information about power system transient events on HV systems more explicitly in this existing document. The Task Force was charged with the following tasks:-Establish system voltages encompassed by C57-142-2010 Guide. -Gather field data, reports, and literature on HV and EHV failures related to substation transients and transformer interaction. -Solicit input from the other technical committees on this subject. -Review IEC and CIGRE work in this area. -Recommend course of action on revision of the present Guide. -Recommend high level changes to the Guide. -Prepare final paper for the Subcommittee. In the course of this work several failure scenarios were identified. These are categorized and the failures are described in this paper. The final recommendations to the Subcommittee are summarized and recommendations are presented for the course of action on the revision/addition of HV and EHV material to the current C57.142 Guide. [ABSTRACT FROM AUTHOR]

A variable-switching constant-sampling frequency critical soft switching model predictive control (VSCS-MPC) method is proposed in this paper to improve the dynamic behavior, efficiency and power density of the DC/DC power converters. Firstly, this paper analyzes the boundary constraints of critical soft switching that are derived with the key parameters of the interlock time and threshold current for typical SiC and GaN devices. Then, the VSCS-MPC method is proposed for synchronous DC/DC converter. Both the current source load and resistive load converters are validated with the proposed MPC method. VSCS-MPC includes two controlling parts. First is the frequency controller to maintain the critical soft switching operation by adjusting the switching frequency based on the pre-defined boundary conditions with a constant sampling frequency. A discretized frequency controller is developed to improve the stability of the system by maintaining a fixed sampling frequency. Second part is the model predictive controller to track the output voltage/current and maintain critical soft switching during dynamic periods. The explicit optimization and oversampling methods are applied in the MPC controller to meet the high frequency demand. A large current ripple ($\triangle i_L$ $\ge$ 200 %) is introduced to achieve the critical soft switching and reduce the inductance. The switching losses are decreased by the frequency controller and the critical soft switching is maintained especially in dynamic periods due to the fast response of MPC. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of finite-time H∞ synchronization for a class of discrete-time switched neural networks with quantized feedback controllers. First, we take advantage of mode-dependent average dwell time approach and semi-time-dependent (STD) Lyapunov function method to establish new criteria for the finite-time synchronization. Based on the newly developed criteria, a finite-time bounded real lemma is presented and further, the quantized state feedback controller is designed to ensure the finite-time H∞ synchronization of the underlying neural networks. The conservatism is further reduced by the proposed mode-dependent and STD controller. Finally, we use two illustrative examples to show the effectiveness and superiority of the results obtained in this paper. [ABSTRACT FROM AUTHOR]

The modular multilevel converter (MMC), owing to the presence of a large number of submodules (SMs) and energy storing elements, requires a large footprint and initial investment. To address these issues, this paper proposes the switched modular multilevel converter (SMMC). It consists of two major elements; the chain-links (CLs), consisting of cascade connection of SMs as in MMC, and the single-pole-triple-throw (SPTT) switches, which can be realized using either the T-type or NPC-type switch strings. The SMMC works on the principle of connecting all the phase-legs in series and their respective positions are mutually interchanged. It offers a compact structure as the SMs count is reduced to 33% of MMC, which results in a much lower energy storage requirement. Furthermore, it does not have inter-phase circulating current problem and hence the CL inductors can also be avoided. The SMMC structure, operating principles, control, and modulation schemes are explained in detail. A detailed comparison of SMMC with the other major existing converters is carried out to highlight the important features of SMMC. The efficacy of SMMC is validated using PSCAD simulation studies with a 19-level grid-connected SMMC model. A 3-phase 19-level SMMC laboratory prototype is developed to further validate its feasibility. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMCs) in high- voltage applications contain large numbers of power switches, which increases the fault probability inside MMCs. This paper proposes a detection method for the faulty arm containing switch open-circuit failures in high-voltage MMCs to improve the reliable operations of MMCs. The proposed method uses the periodicity of the deviation between the maximum and minimum capacitor voltages to provide the detection reference. To yield a reliable reference, the repetitive signal generator is employed. Then, the fault is identified by the difference between the referenced and measured capacitor voltage deviations. An auxiliary criterion is also designated to avoid the false detection caused by the mutations in MMCs. The proposed method can reduce the difficulty in the selection of thresholds. Moreover, the proposed method is robust in high-voltage MMCs with inferior capacitor voltage balancing performance, which ensures detection rapidity and accuracy. Finally, the feasibility of the method is verified by simulation results in Matlab/Simulink. [ABSTRACT FROM AUTHOR]

Piezoelectrically actuated fast mechanical switches provide a low-loss conduction path in hybrid circuit breakers for protecting medium-voltage direct-current systems. As the desired actuation speed approaches the driving limit of a piezoelectric actuator, excessive vibration starts to dominate its underdamped travel curves, resulting in insulation failures and delayed switching in the fast mechanical switch. To improve the underdamped travel curves into critically damped travel curves, several switching motion control schemes with active damping filters are proposed in this paper. The switching motion controllers are based on an electromechanical model of a fast mechanical switch with experimentally identified parameters. According to hardware implementation tests, the proposed closed-loop control schemes optimized the switch travel curves with a 56% reduction in the undershoot and a 75% reduction in the settling time. Equipped with the critically damped travel curves, the piezoelectrically actuated fast mechanical switch is better suited for sequential submodule operations to reduce the interruption time, the peak current and the fault energy to be absorbed in hybrid circuit breakers. [ABSTRACT FROM AUTHOR]

This paper presents frequency domain (FD) Norton-type equivalents of single- and three-phase photovoltaic (PV) generators, aimed at transient calculations. The proposed equivalents can be interfaced with a general frequency-dependent network and/or nonlinear loads and include voltage/current sources representing initial conditions aimed at partitioned-time transient simulation. The transient solution is performed via the numerical Laplace transform (NLT) in a sequential scheme by using time sub-windows with corresponding initial conditions and using reduced number of samples. The proposed approach overcomes the issue of computationally heavy simulations as in classical implementations of NLT. Two case studies involving PV generator and nonlinear load are presented to illustrate the performance of the proposed FD PV models. [ABSTRACT FROM AUTHOR]

Uncertainties in power system studies are typically managed by Monte Carlo methods or by applying some worst case assumptions. As the number ofuncertainties increases, there is a need for methods that can estimate statistical parameters from a limited number of calculations. This paper utilizes a method called the Unscented Transform together with Cornish-Fisher expansion to estimate the 2%-value of switching overvoltages using only about one tenth the number of calculations as a Monte Carlo method, with similar accuracy. The uncertainties considered are the energizing instants of the three phases. The method is illustrated through EMT simulations in PSCAD and it is shown to provide a good approximation of the 2%-value in most of the studied cases. [ABSTRACT FROM AUTHOR]

To calibrate non-contact sensors with fast response and high scale factor, it is critical to develop step pulse generators capable of generating standard high voltage step pulses and accurately measuring the generated waveform. In this paper, two types of step pulse generators are designed with output voltages of 2 kV and 100 kV. The 2 kV step pulse generator can generate a step pulse with a rise time of ∼300 ps and an adjustable pulse width. A step pulse with a rise time less than 5 ns and a pulse width over 1 μs can be generated with the 100 kV step pulse generator. The uncertainty of 2 kV step pulse generator is then analyzed by simulations and experiments. Finally, a performance comparison with step pulse generators in previous studies is carried out. Bandwidth, linearity and repeatability of the sensors can be verified with the designed two step pulse generators. [ABSTRACT FROM AUTHOR]

The safety of converters is key to the stable operation of AC/DC hybrid power grids after AC faults. Thyristor valve current is a direct manifestation of the converter observability, but there are no measuring elements inside the converter, so the thyristor valve current can be reflected only indirectly through external electrical quantities. This paper proposes a virtual measurement scheme based on the temporal features of the converter terminal current. First, under the action of the trigger pulse, the polarity characteristics of the AC current and temporal features between the valves are utilized to predictive estimate the valve state. Then, when commutation failures occur and the bypass paths form, the conduction state of valve is constructed based on the relationship between AC and DC current. Last, when the valve is to be shut-off in the bypass path, the blocking state of the valve is corrected based on the unidirectional conductance characteristics of the valve. According to the above analysis, combined with the topological current equation of the converter, the valve current can be calculated in the whole process. Through the simulation of the different valve states and bypass paths and analysis of the field record data, the results show that the valve current can still be accurately calculated based on the virtual measurement scheme. [ABSTRACT FROM AUTHOR]

In this paper, we address the finite-time and fixed-time synchronization of a general class of switched neural networks (SNNs) with time delays subject to stochastic disturbances. Considering two types of switching in this class of SNNs: 1) intra-SNN state-dependent switching and 2) inter-SNN Markovian switching, we develop three control laws and derive three sets of sufficient conditions for both finite-time and fixed-time synchronization of SNNs subject to stochastic disturbances. We make two remarks on the effects of control-law parameters on synchronization settling time. Moreover, we derive several upper bounds of synchronization settling time and evaluate their pros and cons. Finally, we elaborate on two numerical examples to illustrate the viability of the theoretical results. [ABSTRACT FROM AUTHOR]

IPC (Inter-Process Communication) is a widely used operating system (OS) technique that allows one process to invoke the services of other processes. The IPC participants may share the same OS (internal IPC) or use a separate OS (external IPC). Even though a long line of researches has optimized the performance of IPC, it is still a major factor of the run-time overhead of IPC-intensive applications. Furthermore, there is no one-size-fits-all solution for both internal and external IPC. This paper presents SkyBridge, a general communication technique designed and optimized for both types of IPC. SkyBridge requires no involvement of the privileged software (the kernel or the hypervisor) and enables a process to directly switch to the virtual address space of the target process, regardless of whether they are running on the same OS or not. We have implemented SkyBridge on two microkernels (seL4 and Google Zircon) as well as an open-source serverless hypervisor (Firecracker). The evaluation results show that SkyBridge improves the latency of internal IPC and external IPC by up to 19.6x and 1265.7x, respectively. [ABSTRACT FROM AUTHOR]

The demand for real-time data processing has become increasingly attractive in Cyber-Physical Systems(CPSs), especially for data-intensive embedded real-time applications. In order to timely perceive and respond to environmental changes, the basic design requirement in such systems is to provide data service with high freshness. As modern CPSs become more complex, there are a broad set of system mode switch behaviors, some unforeseen, in a dynamic computational environment. However, conventional control algorithms can hardly handle such new scenarios, since most of them assume that the operational behavior is fixed. In this paper, we study the problem of how to maximize the freshness of data in multi-modal systems. We first use a recently proposed new conception, namely Age of Information (AoI) to quantify the freshness of data by combining the AoI metric with real-time constraints. Then, we propose, to our knowledge, the first freshness-aware scheduling solution to settle the problem via deep reinforcement learning(RL). To be specific, we develop an RL framework that can continuously update its scheduling strategies and maximize the freshness of data in the long term. Extensive simulation experiments are conducted and the results demonstrate that the proposed FAS-DQN outperforms other traditional state-of-the-art methods in terms of data freshness. [ABSTRACT FROM AUTHOR]

This paper focuses on the issue of network connectedness (NC) in security-constrained optimal transmission switching problems, which is complicated by branch contingencies and corrective line switching. Two criteria are firstly proposed with the principle of preserving NC as much as possible within reasonable limits. By extending the electrical flow based NC constraints, a proposition is derived to associate different cases of NC with the optimum of a linear program, yielding the mathematical formulation of the NC criteria. By Karush-Kuhn-Tucker conditions, this formulation is further transformed into a tractable version which can be incorporated with existing SCOTS models without affecting the applicability of original solution approaches. Finally, case studies on various networks and SCOTS models demonstrate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Magnetic random-access memory (MRAM) is a promising memory technology due to its high density, non-volatility, and high endurance. However, achieving high memory fidelity incurs high write-energy costs, which should be reduced for large-scale deployment of MRAMs. In this paper, we formulate a biconvex optimization problem to optimize write fidelity given energy and latency constraints. The basic idea is to allocate non-uniform write pulses depending on the importance of each bit position. The fidelity measure we consider is mean squared error (MSE), for which we optimize write pulses via alternating convex search (ACS). We derive analytic solutions and propose an alternating water-filling algorithm by casting the MRAM’s write operation as communication over parallel channels. Hence, the proposed alternating water-filling algorithm is computationally more efficient than the original ACS while their solutions are identical. Since the formulated biconvex problem is non-convex, both the original ACS and the proposed algorithm do not guarantee global optimality. However, the MSEs obtained by the proposed algorithm are comparable to the MSEs by complicated global nonlinear programming solvers. Furthermore, we prove that our algorithm can reduce the MSE exponentially with the number of bits per word. For an 8-bit accessed word, the proposed algorithm reduces the MSE by a factor of 21. We also evaluate MNIST dataset classification supposing that the model parameters of deep neural networks are stored in MRAMs. The numerical results show that the optimized write pulses can achieve 40% write-energy reduction for the same classification accuracy. [ABSTRACT FROM AUTHOR]

The digital implementation of all the control loops of a versatile buck-boost (VBB) dc–dc converter used in a stand-alone photovoltaic application is proposed in this paper to improve existing digital-analog sliding-mode-based implementations. All three control loops: maximum power point tracking (MPPT), fast input voltage regulation, and inner high-bandwidth current control, have been programmed in the same digital signal controller (DSC). A Model Predictive Control (MPC) based algorithm has satisfactorily solved the challenge of implementing the nominal 100 kHz switching frequency current loop. The MPC cost function is distributed throughout the algorithm to achieve three specific goals: the tracking of the reference current (G1), a quasi-constant steady-state switching frequency (G2), and the assurance that the duration of an interval is larger than the time required to calculate it (G3). The third goal requires the current control to toggle between peak- and valley-modes depending on the operating point. The correct fulfillment of these control objectives on the proposed MPC-based algorithm has been validated through simulations and experimental tests performed on a purpose built-prototype. [ABSTRACT FROM AUTHOR]

In this paper, a fault-tolerant control of a symmetrical six-phase induction generator based on a variable structure strategy is experimentally tested and compared with a classical proportional-integral controller. For this, we use a linear feedback sliding mode controller with switched feedback gains in such a way to control the inner current loops of this machine. One main drawback of the classical three-phase induction generator is that it is no longer possible to generate electrical power if only one phase is lost on the stator side. To overcome this issue, we will use a squirrel cage six-phase induction machine that can still operate when at least three phases remain on the stator side. This article proposes to use a variable structure control in order to cope with unbalanced currents and also maintain the generation of power when a loss of the stator's phases occurs. The proposed controller shows its robustness and good regulation performance in healthy and faulty modes. The simulation and experimental tests were carried out with a 24 kW induction machine that represents 1/100 of the electrical power of a real wind turbine. [ABSTRACT FROM AUTHOR]

In this paper a control method for a matrix converter (MC) based on the heterodyne concept from the communication field is presented. The method is used to convert the high frequency of a microturbine generator’s (MTG) output voltage to the utility grid’s frequency. In this control method a frequency modulation (FM) of the MC’s switching frequency is achieved using a DQ0 analysis of the converter’s filtered output voltage with the utility grid’s frequency as a reference. After filtration, the MC achieves a conversion to the reference frequency with a minimal total harmonic distortion (THD) of the output voltage while using a low switching frequency. In addition, the proposed method decouples the output frequency, phase angle and voltage amplitude, which allows them to be controlled separately. This significantly simplifies the required control, and enables a robust and low-cost design. The theoretical analysis, simulation and experimental results of the method are reported. [ABSTRACT FROM AUTHOR]

Multiphase drives with fault-tolerant capability are favored in high-reliability applications. In most fault-tolerant multiphase drives, the fault types and locations must be known prior to the fault-tolerant control. Therefore, fault diagnosis is an indispensable procedure. This paper proposes a generalized method to detect and identify the open-circuit faults (including open-switch and open-phase faults) in star-connected symmetrical multiphase drives with different phase numbers. The selected fault diagnosis signals are calculated solely from simple arithmetical operations of measured phase currents, resulting in easy real-time implementation. As fault detection signals are derived from the physical constraint imposed by the neutral point, the proposed method is naturally robust and not sensitive to operating points, machine transients and harmonics in stator currents. Therefore, a relatively small fault detection threshold can be used and fast detection can also be achieved. After the fault has been detected, the fault type is further identified according to the polarity of the integration of phase currents. Experimental results on nine-phase and five-phase induction machine drives verify the generality, fast diagnosis speed and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Differential power processing (DPP) converters have been developed for photovoltaic (PV) panels to preclude energy yield reduction due to partial shading. In large-scale PV systems comprising numerous series-connected panels, DPP converters with good modularity are preferable because the number of series-connected panels varies depending on applications. This paper proposes a switched capacitor converter (SCC)-based modular DPP architecture for large-scale PV systems. Four panels are grouped as a module, each having a panel-level DPP converter, and modules are connected in series to form a string. The design of the panel-level DPP converter is fixed while the system can be arbitrarily extended by stacking modules, achieving good modularity. Adjacent panel-level DPP converters are dc-coupled, by which modules can be connected using long cables, mitigating installation limitations. The experimental results of the laboratory and field testing demonstrated the energy yield enhancement by 10%–20%, depending on shading conditions. [ABSTRACT FROM AUTHOR]

This paper presents a sigma-modified adaptive control algorithm to enhance the charging profile in a multi-objective electric vehicle (EV) charging installation. The present algorithm takes care of multiple parametric uncertainties and grid non-idealities to provide an instantaneous control updation in order to achieve well-regulated charging dynamics. With the support of renewable energy and battery energy storage (BES), the present algorithm also ensures an uninterrupted charging profile with controller robustness and stability for bi-directional EV charging. The sigma-mod adaptive controller provides an iterative error convergence at each clock interval of supply voltage dynamics to guarantee improved power quality operation in presence of grid distortions. To further improve the reliability of EV charging opportunities, a solar photovoltaic (PV) array in conjunction with the battery energy storage supports the ancillary services through maximum power point operation. Multivariable sliding mode control and rule-based phase-shift adaptation at different stages of power transformation assure faster convergence, parameter uncertainty and controller stability for the bi-directional EV charging operation. A 3.3 kW PV-integrated off-board charging facility is designed and developed as a laboratory prototype to validate the multi-mode charging architecture with minimal grid dependency. [ABSTRACT FROM AUTHOR]

The paper develops two computationally efficient models, namely a detailed equivalent model and an average-value model, with provisions for representation of the critical state of converter blocking, for modular multilevel converters with embedded storage. These models are indispensable in the simulation of dc faults. The developed detailed equivalent model provides accuracy that matches electromagnetic transient (EMT) simulations, with much reduced computational burden; the developed average-value model represents the averaged behavior of the converter by neglecting switching transients. Both models are extensively evaluated in the context of an HVDC system against benchmark results form a detailed switching model developed in PSCAD/EMTDC. The results confirm the validity and accuracy of the models for steady state, transient, and faulted operating conditions including when the converter is blocked in response to a dc fault. [ABSTRACT FROM AUTHOR]

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]