An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.

Study on Effects of Short Circuit Between High and Common Ends of LVDT's Lead Wires on Sum Voltage

The Linear variable differential transformer(LVDT)is widely used in the aircraft field and crucial to the safety of the aircraft.Based on the short-circuit failure mode between the high and common ends of the LVDT′s lead wires,the theoretical formula of short-circuit sum voltage was deduced and verified via tests.Moreover,the effects of the core length and the winding resistance on the short-circuit sum voltage were analyzed and discussed through numerical methods.The present research put forward some references for LVDT′s design.

Data-driven short circuit resistance estimation in battery safety issues

Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networks(CNN)based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working conditions.Cycling tests of cells with an external short circuit(ESC)are produced to obtain the database and generate the training/testing samples.The samples are sequences of voltage,current,charging capacity,charging energy,total charging capacity,total charging energy with a length of 120 s and frequency of 1 Hz,and their corresponding short circuit resistances.A big database with~6×10^(5)samples are generated,covering various short circuit resistances(47~470Ω),current loading modes(Constant current-constant voltage(CC-CV)and drive cycle),and electrochemical states(cycle numbers from 1 to 300).Results show that the average relative absolute error of five random sample splits is 6.75%±2.8%.Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups:the optimized input sequence length(~120 s),feature selection(at least one total capacity-related variable),and rational model design,using multiple layers with different kernel sizes.This work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.

A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.

Low switching loss and increased short-circuit capability split-gate SiC trench MOSFET with p-type pillar

A split-gate SiC trench gate MOSFET with stepped thick oxide, source-connected split-gate(SG), and p-type pillar(ppillar) surrounded thick oxide shielding region(GSDP-TMOS) is investigated by Silvaco TCAD simulations. The sourceconnected SG region and p-pillar shielding region are introduced to form an effective two-level shielding, which reduces the specific gate–drain charge(Q_(gd,sp)) and the saturation current, thus reducing the switching loss and increasing the short-circuit capability. The thick oxide that surrounds a p-pillar shielding region efficiently protects gate oxide from being damaged by peaked electric field, thereby increasing the breakdown voltage(BV). Additionally, because of the high concentration in the n-type drift region, the electrons diffuse rapidly and the specific on-resistance(Ron,sp) becomes smaller.In the end, comparing with the bottom p~+ shielded trench MOSFET(GP-TMOS), the Baliga figure of merit(BFOM,BV~2/R_(on,sp)) is increased by 169.6%, and the high-frequency figure of merit(HF-FOM, R_(on,sp) × Q_(gd,sp)) is improved by310%, respectively.

Thermal runaway evolution of a 280 Ah lithium-ion battery with LiFePO_(4) as the cathode for different heat transfer modes constructed by mechanical abuse

Lithium iron phosphate batteries have been increasingly utilized in recent years because their higher safety performance can improve the increasing trend of recurring thermal runaway accidents.However,the safety performance and mechanism of high-capacity lithium iron phosphate batteries under internal short-circuit challenges remain to be explored.This work analyzes the thermal runaway evolution of high-capacity LiFePO_(4) batteries under different internal heat transfer modes,which are controlled by different penetration modes.Two penetration cases involving complete penetration and incomplete penetration were detected during the test,and two modes were performed incorporating nails that either remained or were removed after penetration to comprehensively reveal the thermal runaway mechanism.A theoretical model of microcircuits and internal heat conduction is also established.The results indicated three thermal runaway evolution processes for high-capacity batteries,which corresponded to the experimental results of thermal equilibrium,single thermal runaway,and two thermal runaway events.The difference in heat distribution in the three phenomena is determined based on the microstructure and material structure near the pinhole.By controlling the heat dissipation conditions,the time interval between two thermal runaway events can be delayed from 558 to 1417 s,accompanied by a decrease in the concentration of in-situ gas production during the second thermal runaway event.

Extreme Learning Machine-Based Thermal Model for Lithium-Ion Batteries of Electric Vehicles under External Short Circuit

External short circuit(ESC)of lithium-ion batteries is one of the common and severe electrical failures in electric vehicles.In this study,a novel thermal modelis developed to capture the temperature behavior of batteries under ESC conditions.Experiments were systematically performed under different battery initial state of charge and ambient temperatures.Based on the experimental results,we employed an extreme learming machine(ELM)-based thermal(ELMT)model to depict battery temperature behavior under ESC,where a lumped-state thermal model was used to replace the activation function of conventional ELMs.To demonstrate the effectiveness of the proposed model,wecompared the ELMT model with a multi-lumped-state thermal(MLT)model parameterized by thegenetic algorithm using the experimental data from various sets of battery cells.It is shown that the ELMT model can achieve higher computa-tional efficiency than the MLT model and better fitting and prediction accuracy,where the average root mean squared error(RMSE)of the fitting is 0.65℃ for the ELMT model and 3.95℃ for the MLT model,and the RMES of the prediction under new data set is 3.97℃ for the ELMT model and 6.11℃ for the MLT model.

Internal short circuit evaluation and corresponding failure mode analysis for lithium-ion batteries

Internal short circuit(ISC)is the major failure problem for the safe application of lithium-ion batteries,especially for the batteries with high energy density.However,how to quantify the hazard aroused by the ISC,and what kinds of ISC will lead to thermal runaway are still unclear.This paper investigates the thermal-electrical coupled behaviors of ISC,using batteries with Li(Ni_(1/3)CO_(1/3)Mn_(1/3))O_(2) cathode and composite separator.The electrochemical impedance spectroscopy of customized battery that has no LiPF6 salt is utilized to standardize the resistance of ISC.Furthermore,this paper compares the thermal-electrical coupled behaviors of the above four types of ISC at different states-of-charge.There is an area expansion phenomenon for the aluminum-anode type of ISC.The expansion effect of the failure area directly links to the melting and collapse of separator,and plays an important role in further evolution of thermal runaway.This work provides guidance to the development of the ISC models,detection algorithms,and correlated countermeasures.

A fault warning for inter-turn short circuit of excitation winding of synchronous generator based on GRU-CNN

Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation.To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding of a synchronous generator,a gate recurrent unit-convolutional neural network(GRU-CNN)model whose structural parameters were determined by improved particle swarm optimization(IPSO)is proposed.The outputs of the model are the excitation current and reactive power.The total offset distance,which is the fusion of the offset distance of the excitation current and offset distance of the reactive power,was selected as the fault judgment criterion.The fusion weights of the excitation current and reactive power were determined using the anti-entropy weighting method.The fault-warning threshold and fault-warning ratio were set according to the normal total offset distance,and the fault warning time was set according to the actual situation.The fault-warning time and fault-warning ratio were used to avoid misdiagnosis.The proposed method was verified experimentally.

Effects of current waveform parameters during droplet transfer on spatter in high speed waveform controlled Short-circuiting GMAW

Aim at improving the stability of the Short-circuiting Gas Metal Arc Welding （GMAW-S） process for the enhanced speed usage, effects of current waveform parameters during short-term on the welding stability have been investigated by experimental method. The welding power source used for the research is an inverter with a special current waveform control. It is shown that the spatter decreases at first then increases with each increase of the low current period, current increase rate and the maximum current limit. The test results are provided for welding of 1 mm and 3 mm mild steel at speed of 1.2 m/min. The stable GMA W-S process under high speed welding condition has been achieved by optimizing the parameters.

DETECTION AND ANALYSIS OF WELD POOL SHAPE FOR CO_2 SHORT CIRCUITING ARC WELDING

A general industrial CCD( ICCD) camera is redesigned to detect the weld pool without arc at the period of short circuiting, so that the interference of arc and spatter during CO2 short circuiting arc welding is eliminated. Through the analysis of weld pool image, both size parameters (such as weld pool area A, weld pool length L1, L2 and weld pool breadth b) and contour parameters (b, which describe the curves of weld pool boundany) ,which could indicate the shape features of weld pool, had been defined to express weld pool information quantitatively. The investigation of the relationships between weld pool shape parameters and welding process parameters may be beneficial to the quality control of CO2 welding.

Study on chaos in short circuit gas metal arc welding process

Based on the chaos theory, an idea is put forward to analyze the short circuit Gas Metal Arc Welding （ GMAW-S） process. The theory of phase space reconstruction and related algorithms such as mutual information and so on, are applied to analyze the chaos of the GMAW-S process. The largest Lyapunov exponents of some current time series are calculated, and the results indicate that chaos exists in the GMAW-S process. The research of the chaos in the GMAW-S process can be help to get new knowledge of the process.

Influence of optical interference and carrier lifetime on the short circuit current density of organic bulk heterojunction solar cells

Based on simple analytical equations, short circuit current density （Jsc） of the organic bulk heterojunction solar cells has been calculated. It is found that the optical interference effect plays a very important role in the determination of Jsc; and obvious oscillatory behaviour of Jsc was observed as a function of thickness. At the same time, the influence of the carrier lifetime on Jsc also cannot be neglected. When the carrier lifetime is relatively short, Jsc only increases at the initial stage and then decreases rapidly with the increase of active layer thickness. However, for a relatively long carrier lifetime, the exciton dissociation probability must be considered, and Jsc behaves wave-like with the increase of active layer thickness. The validity of this model is confirmed by the experimental results.

Investigation on microprocessor based waveform control of short circuit transfer CO_2 welding

A new kind of simple and flexible CO2 welding system was developed to carry out waveform control. The system consisted of IGBT inverter, PWM circuit and microprocessor unit （ MPU） , in which the output current of constant current （CC） power supply could be changed according to transient physical state, and the variable down slope rate control could be used to ensure a stable welding process. The welding experiment results proved the effectiveness of this control approach.

Determining the feature values of parameters indicating the critical states of molten metal bridge in short circuit transfer

Short circuit transfer involves bridging between the consumable electrode and the weld pool, associated with variations of electrical parameters which characterize the change of molten metal bridge state and are very important for the control of .spatter. In this paper, electrical process parameters and short circuit transfer images were simultaneously recorded with a LabView-based synchronous sensing and visualizing system. The arc^bridge resistance and derivatives of welding current, arc voltage and arc resistance at various instants were calculated by means of offline analysis of the welding current, arc voltage and droplet images. Parameters and their feature values indicating the onset of short circuit and the oncoming necking-down of molten metal bridge were determined. Using the calculated feature values, bridge-state-feedback control for .short circuit transfer was realized with a spatter rate less than 0. 25%.

A new simulation model and its application in CO_2 short-circuiting transfer welding

A new simulation model of CO 2 short circuiting transfer welding may be employed to develop a new pattern of welding machine and to predict welding process parameters to obtain the optimum welding technology properties. In this paper, a new simulating model is developed according to the AWP (adapting welding physics process) waveform control method. Good agreement is shown between the predicted and experimentally determined results. The model will make an important promotion in the development of CO 2 arc welding technique.

Appearance and characteristics of non explosive short circuit transfer using basic electrodes

By means of high-speed photograph and synchronous oscillograph, the appearance and technical features of non-explosive short circuiting transfer using basic electrodes are investigated, and the conditions to form this metal transfer mode are discussed. It is shown that the metal transfer mode has its high frequency of droplet, short period of arc extinguishing and long arc igniting period. This metal transfer mode is expected for basic electrodes for its less spatter and higher deposition efficiency.

The simulation research for transient current variation in short circuit fault of urban rail transportation

Urban rail transit is one of the most important way for urban residents. However, frequent power failure, especially the short fault hinders the safe and stable operation of rail transit. The research of the transient variation of line electrical parameters in short circuit fault is the basis of researches for technology of line protection and short circuit fault location. Based on Matlab/Simulink, a 24-pulse rectifier circuit model is established, the resistance and inductance value of the catenary and rail network are calculated. The short Circuit fault simulation model of DC traction power supply system is established. The short-circuit fault of the traction network at close and distant points are simulated, the transient variation values of fault current with the different fault distance are analyzed. The simulation results show that the transient current peak of the nearby short circuit is oscillatory and convergent due to the nonlinear devices, which proves the accuracy of the model and provides a reference for the precise configuration of the line protection equipment.

The Detection of Inter-Turn Short Circuits in the Stator Windings of Sensorless Operating Induction Motors

This work proposes an alternative strategy to the use of a speed sensor in the implementation of active and reactive power based model reference adaptive system (PQ-MRAS) estimator in order to calculate the rotor and stator resistances of an induction motor (IM) and the use of these parameters for the detection of inter-turn short circuits (ITSC) faults in the stator of this motor. The rotor and stator resistance estimation part of the IM is performed by the PQ-MRAS method in which the rotor angular velocity is reconstructed from the interconnected high gain observer (IHGO). The ITSC fault detection part is done by the derivation of stator resistance estimated by the PQ-MRAS estimator. In addition to the speed sensorless detection of ITSC faults of the IM, an approach to determine the number of shorted turns based on the difference between the phase current of the healthy and faulty machine is proposed. Simulation results obtained from the MATLAB/Simulink platform have shown that the PQ-MRAS estimator using an interconnected high-gain observer gives very similar results to those using the speed sensor. The estimation errors in the cases of speed variation and load torque are almost identical. Variations in stator and rotor resistances influence the performance of the observer and lead to poor estimation of the rotor resistance. The results of ITSC fault detection using IHGO are very similar to the results in the literature using the same diagnostic approach with a speed sensor.

Reducing the Short Circuit Levels in Kuwait Transmission Network

This paper describes the study analysis performed to evaluate the available and potential solutions to control the highly increasing short circuit （SC） levels in Kuwait power system. The real Kuwait High Voltage （HV） network was simulated to examine different measures at both 275 kV and 132 kV stations. The simulation results show that the short circuit currents exceed the permissible levels （40 kA in the 132 kV network and 63 kA in the 275 kV network） in some specific points. The examined measures include the a study on changing the neutral point policy, changing some lines from alternating current （AC） to direct current （DC）, dividing specific bus bars in some generating stations and applying current limiters. The paper also presents a new plan for the transmission network in order to manage the expected increase in short circuit levels in the future.