Rate Of Voltage Change Research Articles

Stretchable Strain and Strain Rate Sensor Using Kirigami‐Cut PVDF Film

AbstractWearable sensor technology has recently received considerable interest because of the emergence of digital healthcare and its expanding markets. Wearable sensors require stretchability, biocompatibility, and high performance. In this study, stretchable strain sensors are designed and fabricated using a kirigami‐cut polyvinylidene fluoride (PVDF) film. Further, the biocompatibility of PVDF is examined. Kirigami cutting can improve stretchability by 400% using the structural distortion of the cut parts. Compared to previously reported sensors, the developed sensor can measure the strain and strain rate simultaneously. The effect of strain and strain rate on the piezoelectric performance is analyzed. The output voltage increases exponentially with the strain, and a high strain rate results in high piezoelectric efficiency. The strain and strain rate can be detected by analyzing the sensor property, which illustrates the relationship between the voltage and voltage change rate. The sensing performance is evaluated using various kirigami patterns. Theoretical analysis reveals the dependence of output voltage on strain and strain rate. Finally, the developed sensor is successfully used as a wearable sensor for athlete rehabilitation and posture monitoring.

A Virtual Inertia Method for Stability Control of DC Distribution Systems with Parallel Converters

DC distribution systems are a typical power electronic system with low inertia, low-rotational kinetic energy, and poor antidisturbance capability when loads fluctuate or parameters change. In this paper, a virtual inertia control with an additional first-order filtering link is proposed on the basis of P-Udc droop control. The results of the simulations and experiments verify that the additional inertia control reduces the voltage change rate and improves the system inertia by adjusting the virtual capacitance value on the DC side of the converter, which can achieve a smoother and more accurate voltage control and suppress the continuous voltage oscillation.

Predictive Commutation Failure Suppression Strategy for High Voltage Direct Current System Considering Harmonic Components of Commutation Voltage

The commutation failure of high voltage direct current (HVDC) systems could lead to unstable operation of the alternating current/direct current (AC/DC) hybrid power grid. The commutation voltage distortion caused by harmonics is a considerable but unclear factor of commutation failure. According to the control switching process of HVDC systems, the commutation voltage-time area method is employed to analyze and reveal the influence mechanism of harmonic components of commutation voltage on first and subsequent commutation failures. Considering the distortion characteristics of AC voltage, a predictive commutation failure suppression strategy considering multiple harmonics of commutation voltage is proposed. In this strategy, the new extinction angle and the zero-crossing offset angle after voltage distortion are calculated considering the harmonic components so as to obtain the compensation margin of the lag trigger angle by combining the correction margin with the voltage change rate. Moreover, the tuning method of parameters of extinction angle and voltage prediction variables are provided. Finally, a case study based on CIGRE standard HVDC system is performed and analyzed by using power systems computer-aided design (PSCAD) software. Compared with the International Council on Large Electric systems (CIGRE) standard test model and traditional commutation failure prevention (CFPREV) control model, the results verify that the proposed strategy can effectively reduce the risk of first and subsequent commutation failures and improve the sensitivity of CFPREV control.

An optimized parameter design method of SiC/Si hybrid switch considering turn-off current spike

In order to reduce the switching loss of SiC MOSFET/Si IGBT (SiC/Si) hybrid switch, the switching mode that turn off the Si IGBT prior to the SiC MOSFET is generally adopted to achieved the zero-voltage switching operation of IGBT. The minority carrier in N-base region of the IGBT are recombined in the form of exponential attenuation due to the conductivity modulation effect. When the SiC MOSFET is turned off, if the carrier recombination process of the IGBT is not finished, it needs to bear a large collector–emitter voltage change rate, resulting in apparent current spike. This current spike will increase the current stress of the device and produce additional turn-off loss. The equivalent model of double pulse test circuit of SiC/Si hybrid switch considering parasitic parameters is established, and the turn-off transient process is given analytically. The influence of turn-off delay time, circuit parameters and working conditions on current spike are analysed quantitatively. Combined with the consideration of device stress and comprehensive turn-off loss, an optimized circuit design method of SiC/Si hybrid switch considering turn-off current peak is proposed, which provides theoretical and design guidance for high reliability and high efficiency SiC/Si-based converters.

A hybrid DDAO-RBFNN strategy for fault tolerant operation in fifteen-level cascaded H-bridge (15L-CHB) inverter with solar photovoltaic (SPV) system

This paper proposes a hybrid approach for fault-tolerant operation in fifteen-level cascaded H-Bridge (15LCHB) inverter with solar photovoltaic system (SPV). Fault-tolerant operation performs two tasks: detection (classification of normal or abnormal) and identification (identification of faults). The proposed intelligent controller is the combination of Differential Annealing Dynamic Optimization (DDAO) and Radial Basis Function Neural Network (RBFNN) named DDAO-RBFNN approach. The major intention of the DDAO-RBFNN approach is separated into fault detection with lessening of complete photovoltaic solar energy conversion system. The proposed system takes into account the failure of the entire autonomous photovoltaic solar conversion process and manages the output voltage (OV) owing to the conditions of partial shading (PS). The collected data set (normal, abnormal) is stored at workstation. RBFNN is utilized to compute the CMI switching pattern that changes the PWM carrier signal. DDAO get the voltage values from RBFNN and evaluates them with the data set, if there is a rate of change of voltage. Any deviation find in the rate of voltage change, it makes a decision based on standard or fault conditions. The proposed system is activated on MATLAB/Simulink working platform, then the efficiency is compared with existing approaches.

Coordinated Control Strategy of Receiving-End Fault Ride-Through for DC Grid Connected Large-Scale Wind Power

This article proposes a comprehensive coordinated suppression strategy for DC overvoltage to achieve the receiving-end fault ride-through of DC grid connected large-scale wind power. For the monopolar DC overvoltage, by reasonably switching the control mode of bipolar modular multilevel converter (MMC), the power transfer capability of the healthy pole MMC can be improved while maintaining DC voltage stability, and the precise load-shedding control of wind farm and its coordination scheme with dissipative resistors are designed, which can effectively reduce the input capacity of dissipative resistors and the risk of wind turbines being cut off. For the bipolar DC overvoltage, the load-shedding control strategy and its parameter selection principles are proposed, which can make wind farm and capacitors in each MMC absorb excess power together, to reduce the change rate and amplitude of DC voltage. Then its cooperation scheme with the dissipative resistors is designed to achieve fault ride-through in the full power range of wind farm. Finally, based on the simulation model of four- terminal DC grid, the effectiveness of the proposed coordinated control methods is verified.

Enhancing Part-to-Part Repeatability of Force-Sensing Resistors Using a Lean Six Sigma Approach.

Polymer nanocomposites have found wide acceptance in research applications as pressure sensors under the designation of force-sensing resistors (FSRs). However, given the random dispersion of conductive nanoparticles in the polymer matrix, the sensitivity of FSRs notably differs from one specimen to another; this condition has precluded the use of FSRs in industrial applications that require large part-to-part repeatability. Six Sigma methodology provides a standard framework to reduce the process variability regarding a critical variable. The Six Sigma core is the DMAIC cycle (Define, Measure, Analyze, Improve, and Control). In this study, we have deployed the DMAIC cycle to reduce the process variability of sensor sensitivity, where sensitivity was defined by the rate of change in the output voltage in response to the applied force. It was found that sensor sensitivity could be trimmed by changing their input (driving) voltage. The whole process comprised: characterization of FSR sensitivity, followed by physical modeling that let us identify the underlying physics of FSR variability, and ultimately, a mechanism to reduce it; this process let us enhance the sensors’ part-to-part repeatability from an industrial standpoint. Two mechanisms were explored to reduce the variability in FSR sensitivity. (i) It was found that the output voltage at null force can be used to discard noncompliant sensors that exhibit either too high or too low sensitivity; this observation is a novel contribution from this research. (ii) An alternative method was also proposed and validated that let us trim the sensitivity of FSRs by means of changing the input voltage. This study was carried out from 64 specimens of Interlink FSR402 sensors.

Multi-Frequency bands based Pole-to-Ground fault detection method for MMC-Based radial DC distribution systems

In a small-current grounding system, the pole-to-ground fault may cause the voltage drop in the fault pole and the voltage rise in the other poles. In flexible DC distribution systems, Severe voltage variation may shorten the insulation lifetime of the equipment, which leads to great concerns on the safety issue. In addition, the existence of high transition resistance degrades the accuracy of fault detection methods, thus further affecting the reliability of the system. Therefore, it is essential to explore an advanced technology for faulty feeder detection. This study proposes a faulty feeder detection method based on the characteristics of transient zero-mode current (TZMC) in multi-frequency bands. The change rate of zero-mode voltage is applied as the protection activation criterion. Then, the characteristic matrix is constructed via computing the fuzzy entropy of TZMC in each frequency band. Finally, the faulty feeder can be identified by conducting fuzzy C-means on the characteristic matrix. This proposed method is tested through simulations on the PSCAD/EMTDC platform, which successfully demonstrates its outstanding adaptability, reliability, and accuracy.

Data-Driven ICA-Bi-LSTM-Combined Lithium Battery SOH Estimation

Lithium battery state of health (SOH) is a key parameter to characterize the actual battery life. SOH cannot be directly measured. In order to further improve the accuracy of SOH estimation of lithium batteries, a model combining incremental capacity analysis (ICA) and bidirectional long- and short-term memory (Bi-LSTM) neural networks based on health characteristic parameters is proposed to predict the SOH of lithium-ion batteries. First, the health characteristic parameters are initially selected from the lithium battery charging curve, and the health characteristics are extracted by the Pearson correlation coefficient, including the charging time of constant current, charging time of constant voltage, voltage change rate from 300 s to 1000 s, 200s of voltage per cycle at a time. Second, ICA was used to deeply mine the deep associations related to SOH and the peaks of IC curves and their corresponding voltages were extracted as additional inputs to the model. Then, Bi-LSTM is used to form a combined SOH estimation model through adaptive weighting factors. Finally, the verification is based on the 5th battery parameters of the NASA lithium battery data set. The experimental results show that the proposed combined model reduces the mean square error by 55.17%, 49.28%, and 41.47%, respectively, compared with single models such as BP neural network (BPNN), LSTM, and gated recurrent neural network (GRU).

A vibration reduction method based on smooth voltage PWM control of switched reluctance machines

At the beginning of the demagnetization instant of Switched Reluctance Machines (SRMs), the terminal voltage of the phase winding varies from the positive value of power supply to its negative with a sudden change. And this produces a high change rate of electromagnetic force giving rise to serious vibration, which known as the severe drawback of SRMs limiting its wide use. In this paper, a vibration reduction method for SRMs is proposed. A smooth voltage PWM control strategy is proposed and applied during the turn-off stage before the demagnetization instant, which aims to decrease the terminal voltage change rate of the phase winding. The duty cycle of the PWM is determined by the average voltage of phase winding during the time of turn-off, which is related to the period of stator natural frequency, electrical angular speed of rotor and parameters of the current controller of the machine. And it can update automatically under different working conditions. Some simulations are carried out, the results of which verify its effectiveness. Furthermore, the proposed control method is investigated from aspects both of torque ripple and system efficiency at different operating points.

The Effects of Pulse Shape on the Selectivity and Production Rate in Non-oxidative Coupling of Methane by a Micro-DBD Reactor

The conversion of methane to ethylene has been investigated in a micro-DBD reactor with electrodes containing charge injector parts and excited with a negatively nano-second pulse voltage superimposed on a positive dc voltage. The effect of changing the characteristics of pulsed voltage such as pulse rise time (5–7 ns), total pulse width (12–14 ns), and pulse fall time (5–7 ns) on generation rate and products selectivity of the methane plasma has been studied. The kinetic model includes twenty species (electron, ions, radicals, and neutrals). The results showed that change in input pulse shape changes the generation rate and selectivity of neutral products. The rate of voltage change during pulse on-time significantly changed the instant C2H4 selectivity. With increasing the pulse rise and fall times the ethylene selectivity decreases, while the hydrogen selectivity increases. Results also showed that the electron reactions are dominant conversion channels during pulse on-time, while they had lower contributions in conversion progress during pulse off-time and the conversion process during this period is mainly governed by the radical reactions.

Optimal Design of 9-Phase Permanent Magnet Synchronous Generator With Low Voltage Change Rate for Diesel Railway Vehicles

Due to the unchangeable air-gap flux density, the voltage output by permanent magnet synchronous generator (PMSG) will have a variation when the load changes. In order to reduce the voltage variation when PMSGs provide power for the rectifier load in diesel railway vehicles, an optimal method is presented to design a 9-phase PMSG. This optimal method not only ensures the open-circuit voltage of the generator equals the rated voltage of the load, but also it guarantees the PMSG has a low voltage change rate at the same time. In this paper, the saliency ratio range and the relationship between resistance of load and the induction of <i>d</i>-axis are derived according to the two-axis theory, when the PMSG has the negative or zero voltage change rate. Then based on the result of the derivation, by adding the I-shaped permanent magnet (PM) to the <i>d</i>-axis magnetic circuit of V-shaped interior PM rotor, a V-I-shaped PMSG is formed. After that, the Kriging method and the finite-element method (FEM) are used to establish a multi-objective function model. By calculating the minimum value of the multi-objective function, the construct dimension of the I-shaped PM is obtained. After the optimal design results are verified by the FEM, a 520 kVA 9-phase PMSG is manufactured to validate the effectiveness of the proposed methods.

Two‐stage voltage control strategy in distribution networks with coordinated multimode operation of PV inverters

To solve the problems of voltage violation and fast voltage fluctuation caused by photovoltaic (PV) grid connections in distribution networks, a two-stage coordinated voltage control strategy for PV inverters with multimode coordinated operation in distribution networks (DNs) is proposed. It is based on the characteristics of PV inverters that can be regulated rapidly and continuously. First, the voltage control process is divided into two control stages according to the voltage change rate, and the corresponding voltage control models are established. Then, the operating modes of PV inverters are classified into three modes: economic prevention, economic control, and efficient control. Different operating modes are used to adapt to the two-stage voltage control. Finally, a voltage fast control solution algorithm is proposed, which considers adaptive time delays and combines local measurement, prediction, and communication information to update control commands. The effectiveness and feasibility of the proposed voltage control strategy were demonstrated through simulation tests on a real 10-kV line with a high PV penetration rate in the Anhui province of China. The results show that the proposed strategy can prevent voltage violation and sudden changes and can smooth out voltage fluctuation.

Transient stability assessment application using post-disturbance voltage fluctuations in a multi-machine power system

Transient stability analysis programs are typically based on step-by-step numerical integrations of power-system models to simulate system dynamic behaviors. Unfortunately, these approaches are inadequate for dealing with the changing overall system conditions. For years, direct methods have held the promise of providing real-time stability assessments; however, they have presented several challenges with rotor angle-based theories. The angle-based common reference, such as the center of inertia, must be updated in each measurement instant, and this calculation requires the connectivity status of all generators. In addition, the field-angle difference data can suffer from errors, and an ex-post analysis needs many phasor measurement units. This study addresses these challenges with novel methods provided with voltage-based theoretical foundations because voltage is an easily available information. The proposed method monitors or simulates the post-disturbance voltages and calculates the product voltage deviation and rate of voltage change as an indicator of the post-disturbance transient instability. A relationship between the proposed index and the transient stability in a multi-machine power system is formulated, and the method effectiveness is tested through a simulation on a New England power system.

Experimental study of dynamic performance of defective cell within a PEMFC stack

Defective cell in a PEMFC stack may reduce durability and reliability of the stack and even damage the stack. However, the dynamic performance of defective cell within a PEMFC stack is not clear. In this paper, the dynamic characteristics of the defective cell under different load conditions are analyzed. The results reveal that the defective cell has slower dynamic response rate than other single fuel cells, and the defective cell causes a poor voltage uniformity of the stack. The increased frequency of load change makes the voltage change rate of defective cell higher. The increased amplitude of load change has a more negative impact than the increased frequency of load change, and makes the defective cell more prone to flooding. Furthermore, impedance spectrum shows that these load conditions have greater negative effect for the defective cell than other cells. Finally, according to the experimental results and practical application, recommends related to control strategy of PEMFC stack are proposed to extend lifetime.

변전소의 PMU 생성 빅 데이터의 통계적 분석을 통한 안정적 운용 탐색

In order to monitor, analyze, and control RESs operated in connection with the power system in real-time, the installation and distribution of PMUs are expanding. Accordingly, there is a need for a method that can effectively use the large-capacity big data generated by the PMU. In Gangwon-do, more than 3GW of RES is expected to be connected by 2025. In this paper, in order to cope with the volatility of RESs and to improve reliability of power system in Gangwon-do, the effect on the power system is effectively investigated through the PMU-generated big data of S/S connected with RESs. First, big data is collected using the PMU and F/R installed in the S/S. The instantaneous voltage change rate is calculated, and statistical techniques such as boxplot, kernel density, correlation index, and harmonic average are implemented using R programming, which is specialized for large data statistics and analysis. Finally, the power quality is analyzed through the implemented technique. So, it is thought to be helpful in research on the stable operation of RESs linked systems.

Frequency-Dependent Action of Neuromodulation.

In oscillatory circuits, some actions of neuromodulators depend on the oscillation frequency. However, the mechanisms are poorly understood. We explored this problem by characterizing neuromodulation of the lateral pyloric (LP) neuron of the crab stomatogastric ganglion (STG). Many peptide modulators, including proctolin, activate the same ionic current (IMI) in STG neurons. Because IMI is fast and non-inactivating, its peak level does not depend on the temporal properties of neuronal activity. We found, however, that the amplitude and peak time of the proctolin-activated current in LP is frequency dependent. Because frequency affects the rate of voltage change, we measured these currents with voltage ramps of different slopes and found that proctolin activated two kinetically distinct ionic currents: the known IMI, whose amplitude is independent of ramp slope or direction, and an inactivating current (IMI-T), which was only activated by positive ramps and whose amplitude increased with increasing ramp slope. Using a conductance-based model we found that IMI and IMI-T make distinct contributions to the bursting activity, with IMI increasing the excitability, and IMI-T regulating the burst onset by modifying the postinhibitory rebound in a frequency-dependent manner. The voltage dependence and partial calcium permeability of IMI-T is similar to other characterized neuromodulator-activated currents in this system, suggesting that these are isoforms of the same channel. Our computational model suggests that calcium permeability may allow this current to also activate the large calcium-dependent potassium current in LP, providing an additional mechanism to regulate burst termination. These results demonstrate a mechanism for frequency-dependent actions of neuromodulators.

Influence of power cycling ageing on the current and voltage transitions during hard switching of IGBT devices

In this paper, the influence of ageing by PCT (Power Cycling Test) on the hard switching behavior of IGBT (Insulated Gate Bipolar Transistor) devices, especially the current change rate di/dt and voltage change rate dv/dt during the switching process, is investigated with standard DC-PCT and a PCT with superimposed switching losses. 1200 V IGBTs with two different package forms are used for the PCTs to stimulate two common failure modes: discrete devices with the bond wire failures and modules without baseplate to trigger the solder layer degradation. To evaluate the hard switching behavior of the IGBTs, a DPT (double pulse test) is repetitively performed after a specific number of cycles at the same test conditions to determine the influence of power cycling ageing. The experimental results show that the current and voltage transient transitions of IGBT devices during hard switching are independent of the power cycling ageing.

Study on dynamic characteristic optimization of virtual inertia control for the grid-connected converters in DC micro grid

In order to reduce the transient time and voltage deviation due to voltage variation while increasing the system inertia of the DC microgrid, a new adaptive control method for the parameters of the grid-connected end is proposed. Firstly, a grid-connected converter control strategy mathematical model is established. Secondly, the influences of different control parameters on the dynamic characteristics of the system are studied. An adaptive equation based on the parameters of voltage deviation and voltage change rate of DC bus is proposed. Finally, through MATLAB/Simulink simulation, the simulation results of the traditional drooping control, the virtual inertial control with fixed parameters and the control strategy proposed in this paper are compared and analyzed. The result shows that the proposed control method has better dynamic characteristics.

Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids

This paper has introduced an algorithm for the identification of islanding events in the remotely located distribution grid with renewable energy (RE) sources using the voltage signals. Voltage signal is processed using Stockwell transform (ST) to compute the median-based islanding recognition factor (MIRF). The rate of change in the root mean square (RMS) voltage is computed by differentiating the RMS voltage with respect to time to compute the voltage rate of change in islanding recognition factor (VRCIRF). The proposed voltage-based islanding recognition factor (IRFV) is computed by multiplying the MIRF and VRCIRF element to element. The islanding event is discriminated from the faulty and operational events using the simple decision rules using the peak magnitude of IRFV by comparing peak magnitude of IRFV with pre-set threshold values. The proposed islanding detection method (IDM) effectively identified the islanding events in the presence of solar energy, wind energy and simultaneous presence of both wind and solar energy at a fast rate in a time period of less than 0.05 cycles compared to the voltage change rate (ROCOV) and frequency change rate (ROCOF) IDM that detects the islanding event in a time period of 0.25 to 0.5 cycles. This IDM provides a minimum non-detection zone (NDZ). This IDM efficiently discriminated the islanding events from the faulty and switching events. The proposed study is performed on an IEEE-13 bus test system interfaced with renewable energy (RE) generators in a MATLAB/Simulink environment. The performance of the proposed IDM is better compared to methods based on the use of ROCOV, ROCOF and discrete wavelet transform (DWT).