Influence of Yb_2O_3 doping on microstructural and electrical properties of ZnO-Bi_2O_3-based varistor ceramics

ZnO-Bi2O3-based varistor ceramics doped with Yb2O3 in the range from 0 to 0.4% （molar fraction） were obtained by a solid reaction route. The X-ray diffractometry （XRD） and scanning electron microscopy （SEM） were applied to characterize the phases and microstructure of the varistor ceramics, and a DC parameter instrument for varistor ceramics was applied to investigate their electrical properties and V-I characteristics. The XRD analysis of the samples shows that the ZnO phase, Bi2O3 phase, ZnTSbaOl2-type spinel phase and Zn2Bi3Sb3O14-type pyrochlore are present, and the Yb2O3 phases and Sb2O4 phases are found in varistor ceramics with increasing amounts of Yb2O3. The average size of ZnO grain firstly increases and then decreases with the increase of Yb2O3 content. The result also shows that the threshold voltage is between 656 V/nun and 1 232 V/mm, the nonlinear coefficient is in the range of 14.1-22.3, and the leakage current is between 0.60 μA and 19.6 μA. The 0.20% Yb2O3-added ZnO-Bi2O3-based varistor ceramics sintered at 900 ℃ have the best electrical characteristics.

NETLAB-An Internet based laboratory for electrical engineering education

This article describes an Internet based laboratory (NETLAB) developed at Zhejiang University for electrical engi- neering education. A key feature of the project is the use of real experimental systems rather than simulation or virtual reality. NELTAB provides remote access to a wide variety of experiments, including not only basic electrical and electronic experiments but also many innovative control experiments. Students can effectively use the laboratory at any time and from anywhere. NETLAB has been in operation since July 2003.

Prediction of Equivalent Electrical Parameters of Dielectric Barrier Discharge Load Using a Neural Network

A reliable, efficient and economical power supply for dielectric barrier discharge （DBD） is essential for its industrial applications. However, the equivalent load parameters complicare the design of power supply as they are variable and varied nonlinearly in response to varied voltage and power. In this paper the equivalent electrical parameters of DBD are predicted using a neural network, which is beneficial for the design of power supply and helps to investigate how the electrical parameters influence the equivalent load parameters. The electrical parameters includ- ing voltage and power are determined to be the inputs of the neural network model, as these two parameters greatly influence the discharge type and the equivalent DBD load parameters which are the outputs of the model. The voltage and power are decoupled with pulse density modula- tion （PDM） and hence the impact of the two electrical parameters is discussed individually. The neural network model is trained with the back-propagation （BP） algorithm. The obtained neural network model is evaluated by the relative error, and the prediction has a good agreement with the practical values obtained in experiments.

Economic Dispatch of Electrical Power System Based on the Multi-objective Co-evolutionary Algorithm

It is important to distribute the load efficiently to minimize the cost of the economic dispatch of electrical power system. The uncertainty and volatility of wind energy make the economic dispatch much more complex when the general power systems are combined with wind farms. The short term wind power prediction method was discussed in this paper. The method was based on the empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD). Furthermore,the effect of wind farms on the traditional economic dispatch of electrical power system was analyzed. The mathematical model of the economic dispatch was established considering the environmental factors and extra spinning reserve cost. The multi-objective co-evolutionary algorithm was used to figure out the model. And the results were compared with the NSGA-Ⅱ(non-dominated sorting genetic algorithm-Ⅱ) to verify its feasibility.

Controllable heterogeneous interfaces and dielectric modulation of biomass-derived nanosheet metal-sulfide complexes for high-performance electromagnetic wave absorption

Constructing new environmentally friendly dielectric coupling models is an effective strategy for design-ing high-performance wave absorbers.However,biomass carbon materials with high potential energy and a lack of magnetic response mechanism do not fulfill the requirements.In this work,the effects of different pyrolysis temperatures and the introduction of different metal sulfides on the microscopic morphology and dielectric-magnetic properties of the composites were investigated.Among them,K el-ement detected in the biomass effectively modulates the conduction loss.The minimum reflection loss(RL_(min))of-62.42 dB at 1.8 mm and the maximum effective absorption bandwidth(EAB_(max))of-62.42 dB at 1.9 mm were obtained due to the non-uniform interfacial-induced polarization of the metal-sulfide nanosheets and the scattering of the electromagnetic waves(EW)by the“island”microstructures.This study provides a powerful reference for the modification and application of biomass materials.

A Blockchain-Based Access Control Scheme for Reputation Value Attributes of the Internet of Things

The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.

Electrical modeling of dielectric barrier discharge considering surface charge on the plasma modified material

We present the variations of electrical parameters of dielectric barrier discharge(DBD)when the DBD generator is used for the material modification,whereas the relevant physical mechanism is also elaborated.An equivalent circuit model is applied for a DBD generator working in a filament discharging mode,considering the addition of epoxy resin(EP)as the plasma modified material.The electrical parameters are calculated through the circuit model.The surface conductivity,surface potential decay,trap distributions and surface charge distributions on the EP surface before and after plasma treatments were measured and calculated.It is found that the coverage area of micro-discharge channels on the EP surface is increased with the discharging time under the same applied AC voltage.The results indicate that the plasma modified material could influence the ignition of new filaments in return during the modification process.Moreover,the surface conductivity and density of shallow traps with low trap energy of the EP samples increase after the plasma treatment.The surface charge distributions indicate that the improved surface properties accelerate the movement and redistribution of charge carriers on the EP surface.The variable electrical parameters of discharge are attributed to the redistribution of deposited surface charge on the plasma modified EP sample surface.

Application of Electrical Automation Technology in Power System

With the continuous development and progress of science and technology in China, automation technology has occupied an important position in many fields while its application in power system is increasingly widespread. Therefore, the application of electrical automation technology in power system is of great significance for power supply stability and work efficiency. In this paper, the author analyzes the application of electric automation technology in power system and makes contributions to the sustainable and stable development of power enterprises.

Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Harmonic Impedance Modeling and Oscillation Analysis of Modular Multilevel Converter

To facilitate rapid analysis of the oscillation stability mechanism in modular multilevel converter-based high voltage direct current(MMC-HVDC)systems and streamline the simulation process for determining MMC impedance characteristics,a simplified mathematical simulation model for MMC closed-loop impedance is developed using the harmonic state space method.This model considers various control strategies and includes both AC-side and DC-side impedance models.By applying a Nyquist criterion-based impedance analysis method,the stability mechanisms on the AC and DC sides of the MMC are examined.In addition,a data-driven oscillation stability analysis method is also proposed,leveraging a global sensitivity algorithm based on fast model results to identify key parameters influencing MMC oscillation stability.Based on sensitivity analysis results,a parameter adjustment strategy for oscillation suppression is proposed.The simulation results from the MATLAB/Simulinkbased MMC model validate the effectiveness of the proposed method.

Utility and Application of a Versatile Analytical Method for MMF Calculation in AC Machines

A versatile analytical method(VAM) for calculating the harmonic components of the magnetomotive force(MMF) generated by diverse armature windings in AC machines has been proposed, and the versatility of this method has been established in early literature. However, its practical applications and significance in advancing the analysis of AC machines need further elaboration. This paper aims to complement VAM by augmenting its theory, offering additional insights into its conclusions, as well as demonstrating its utility in assessing armature windings and its application of calculating torque for permanent magnet synchronous machines(PMSM). This work contributes to advancing the analysis of AC machines and underscores the potential for improved design and performance optimization.

Enhanced degradation of tetracycline by gas-liquid discharge plasma coupled with g-C_(3)N_(4)/TiO_(2)

Plasma-catalysis is considered as one of the most promising technologies for antibiotic degradation in water.In the plasma-catalytic system,one of the factors affecting the degradation effect is the performance of the photocatalyst,which is usually restricted by the rapid recombination of electrons and holes as well as narrow light absorption range.In this research,a photocatalyst g-C_(3)N_(4)/TiO_(2) was prepared and coupled with gas-liquid discharge(GLD)to degrade tetracycline(TC).The performance was examined,and the degradation pathways and mechanisms were studied.Results show that a 90%degradation rate is achieved in the GLD with g-C_(3)N_(4)/TiO_(2) over a 10 min treatment.Increasing the pulse voltage is conducive to increasing the degradation rate,whereas the addition of excessive g-C_(3)N_(4)/TiO_(2) tends to precipitate agglomerates,resulting in a poor degradation efficiency.The redox properties of the g-C_(3)N_(4)/TiO_(2) surface promote the generation of oxidizing active species(H2O2,O3)in solution.Radical quenching experiments showed that·OH,hole(h^(+)),play important roles in the TC degradation by the discharge with g-C_(3)N_(4)/TiO_(2).Two potential degradation pathways were proposed based on the intermediates.The toxicity of tetracycline was reduced by treatment in the system.Furthermore,the g-C_(3)N_(4)/TiO_(2) composites exhibited excellent recoverability and stability.

Effect of dielectric material on the uniformity of nanosecond pulsed dielectric barrier discharge

Dielectric barrier discharge(DBD)is considered as a promising technique to produce large volume uniform plasma at atmospheric pressure,and the dielectric barrier layer between the electrodes plays a key role in the DBD processes and enhancing discharge uniformity.In this work,the uniformity and discharge characteristics of the nanosecond(ns)pulsed DBD with dielectric barrier layers made of alumina,quartz glass,polycarbonate(PC),and polypropylene(PP)are investigated via discharge image observation,voltage-current waveform measurement and optical emission spectral diagnosis.Through analyzing discharge image by gray value standard deviation method,the discharge uniformity is quantitatively calculated.The effects of the space electric field intensity,the electron density(Ne),and the space reactive species on the uniformity are studied with quantifying the gap voltage Ug and the discharge current Ig,analyzing the recorded optical emission spectra,and simulating the temporal distribution of Ne with a one-dimensional fluid model.It is found that as the relative permittivity of the dielectric materials increases,the space electric field intensity is enhanced,which results in a higher Ne and electron temperature(Te).Therefore,an appropriate value of space electric field intensity can promote electron avalanches,resulting in uniform and stable plasma by the merging of electron avalanches.However,an excessive value of space electric field intensity leads to the aggregation of space charges and the distortion of the space electric field,which reduce the discharge uniformity.The surface roughness and the surface charge decay are measured to explain the influences of the surface properties and the second electron emission on the discharge uniformity.The results in this work give a comprehensive understanding of the effect of the dielectric materials on the DBD uniformity,and contribute to the selection of dielectric materials for DBD reactor and the realization of atmospheric pressure uniform,stable,and reactive plasma sources.

Bifurcation analysis and control study of improved full-speed differential model in connected vehicle environment

In recent years, the traffic congestion problem has become more and more serious, and the research on traffic system control has become a new hot spot. Studying the bifurcation characteristics of traffic flow systems and designing control schemes for unstable pivots can alleviate the traffic congestion problem from a new perspective. In this work, the full-speed differential model considering the vehicle network environment is improved in order to adjust the traffic flow from the perspective of bifurcation control, the existence conditions of Hopf bifurcation and saddle-node bifurcation in the model are proved theoretically, and the stability mutation point for the stability of the transportation system is found. For the unstable bifurcation point, a nonlinear system feedback controller is designed by using Chebyshev polynomial approximation and stochastic feedback control method. The advancement, postponement, and elimination of Hopf bifurcation are achieved without changing the system equilibrium point, and the mutation behavior of the transportation system is controlled so as to alleviate the traffic congestion. The changes in the stability of complex traffic systems are explained through the bifurcation analysis, which can better capture the characteristics of the traffic flow. By adjusting the control parameters in the feedback controllers, the influence of the boundary conditions on the stability of the traffic system is adequately described, and the effects of the unstable focuses and saddle points on the system are suppressed to slow down the traffic flow. In addition, the unstable bifurcation points can be eliminated and the Hopf bifurcation can be controlled to advance, delay, and disappear,so as to realize the control of the stability behavior of the traffic system, which can help to alleviate the traffic congestion and describe the actual traffic phenomena as well.

Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

Improved combustion stability of biogas at different CO_(2) concentrations using inhomogeneous partially premixed stratified flames

Biogas is a renewable and clean energy source that plays an important role in the current environment of lowcarbon transition.If high-content CO_(2) in biogas can be separated,transformed,and utilized,it not only realizes high-value utilization of biogas but also promotes carbon reduction in the biogas field.To improve the combustion stability of biogas,an inhomogeneous,partially premixed stratified(IPPS)combustion model was adopted in this study.The thermal flame structure and stability were investigated for a wide range of mixture inhomogeneities,turbulence levels,CO_(2) concentrations,air-to-fuel velocity ratios,and combustion energies in a concentric flow slot burner(CFSB).A fine-wire thermocouple is used to resolve the thermal flame structure.The flame size was reduced by increasing the CO_(2) concentration and the flames became lighter blue.The flame temperature also decreased with increase in CO_(2) concentration.Flame stability was reduced by increasing the CO_(2) concentration.However,at a certain level of mixture inhomogeneity,the concentration of CO_(2) in the IPPS mode did not affect the stability.Accordingly,the IPPS mode of combustion should be suitable for the combustion and stabilization of biogas.This should support the design of highly stabilized biogas turbulent flames independent of CO_(2) concentration.The data show that the lower stability conditions are partially due to the change in fuel combustion energy,which is characterized by the Wobbe index(WI).In addition,at a certain level of mixture inhomogeneity,the effect of the WI on flame stability becomes dominant.

Machine learning-driven optimization of plasma-catalytic dry reforming of methane

This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data.To address the non-linear and complex nature of the plasma-catalytic DRM process,the hybrid ML model integrates three well-established algorithms:regression trees,support vector regression,and artificial neural networks.A genetic algorithm(GA)is then used to optimize the hyperparameters of each algorithm within the hybrid ML model.The ML model achieved excellent agreement with the experimental data,demonstrating its efficacy in accurately predicting and optimizing the DRM process.The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance.We found that the optimal discharge power(20 W),CO_(2)/CH_(4)molar ratio(1.5),and Ni loading(7.8 wt%)resulted in the maximum energy yield at a total flow rate of∼51 mL/min.Furthermore,we investigated the relative significance of each operating parameter on the performance of the plasma-catalytic DRM process.The results show that the total flow rate had the greatest influence on the conversion,with a significance exceeding 35%for each output,while the Ni loading had the least impact on the overall reaction performance.This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets,enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.

Decentralized Optimal Control and Stabilization of Interconnected Systems With Asymmetric Information

The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information.Compared with previous work,a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first time.The main challenge lies in three aspects:Firstly,the asymmetric information results in coupling between control and estimation and failure of the separation principle.Secondly,two extra unknown variables are generated by asymmetric information(different information filtration)when solving forward-backward stochastic difference equations.Thirdly,the existence of additive noise makes the study of mean-square boundedness an obstacle.The adopted technique is proving and assuming the linear form of controllers and establishing the equivalence between the two systems with and without additive noise.A dual-motor parallel drive system is presented to demonstrate the validity of the proposed algorithm.

A Design of Modular Interior Ferrite Magnet Fluxswitching Linear Motor for Track Transport

A novel topology of modular ferrite magnet fluxswitching linear motor(FMFSLM)use for track transport is presented in this paper,which enables more ferrite magnets to be inserted into the primary iron core.The motor has a significant low-cost advantage in long-distance linear drive.The proposed FMFSLM’s structure and working principle were introduced.Further,the thrust force expression of the motor was established.The thrust force components triggering thrust force ripple were investigated,and their expressions can be obtained according to the inductances’Fourier series expressions.Resultantly,the relationship between the harmonics of thrust force and that of self-and mutual inductances was revealed clearly.Based on the relationship,a skewed secondary should be practical to reduce the thrust force ripple.Thus,the effect of employing a skewed secondary to the proposed FMFSLM was investigated,and an optimized skewing span distance was determined.Finite element analysis(FEA)was conducted to validate the exactness of the theoretical analysis.The simulation results indicate that the strategy of suppressing thrust force ripple has a significant effect.Meanwhile,the motor maintains a good efficiency characteristic.The results of the prototype experiment are in good agreement with FEAs,which further verifies the proposed modular interior FMFSLM’s practicability.

Set-Membership Filtering Approach to Dynamic Event-Triggered Fault Estimation for a Class of Nonlinear Time-Varying Complex Networks

The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.