Current Change Rate Research Articles

Control and Fault Protection Strategy in DC Distribution Network

This article provides a detailed analysis of the dynamic characteristics of DC pole-to-pole faults in modular multilevel converters and proposes a protection and control strategy based on the current rate of change. By detecting the current rate of change, a resistance current limiter is put into operation to achieve DC bipolar short circuit non-blocking fault crossing. The fault current is cut off by the DC circuit breaker. This method is an active current limiting control method that adds current limiting devices before fault current identification, leading to fault identification. Finally, a single-ended flexible DC distribution network model was built by using a real-time simulation system. The simulation results verified the effectiveness and accuracy of the protection and control strategy in the case of pole-to-pole faults.

State of health estimation based on inconsistent evolution for lithium-ion battery module

Estimating state of health for battery module is one of the most significant and challenging techniques to promote the commercialization of electric vehicles. Based on the relationship changes of branch current and its estimation error during aging, a state of health estimation general framework is presented for battery module. Firstly, the parallel battery module aging experiment is designed. In addition, the consistency changes of branches were analyzed. A neural network model utilizing dual back-propagation for estimating branch current errors was developed by employing the experimental data of battery module. Through estimation error of branch current under five working conditions, two aging characteristics are extracted, one is the slope of compensation value and current, the other is the slope of compensation value and current change rate. These features are fed into gaussian process regression training to obtain a state of health estimation model for the battery module. Furthermore, the model is validated with new european driving cycle working condition. Finally, a dual bidirectional long short-term memory neural network is utilized to illustrate the versatility of the presented universal framework, which can effectively estimate state of health of battery module with the maximum relative error of 2.1226 %.

VSC-HVDC traveling wave protection based on single-ended boundary fault information supplement strategies

Traveling wave protection for the voltage source converter-based high-voltage direct current (VSC-HVDC) system, relying on single-ended information, has a limited ability to distinguish boundary faults. Many novel protection schemes have been proposed to enrich the single-ended fault information, with the aim of improving this ability. Nevertheless, they still face issues such as reduced protection speed or demanding protection measuring devices. To enrich the fault information within existing measurement conditions while guaranteeing the protection speed, two single-ended boundary fault information supplement strategies are proposed. According to the bipolar symmetry of the fault traveling wave, the measurement of one pole is supplemented with that of the other pole. According to the reactor characteristics, i.e., the proportional relationship between the voltage and the current change rate of the DC reactor, the voltage measurement is further supplemented. The VSC-HVDC traveling wave protection based on the single-ended boundary fault information supplement strategies is proposed. This results in a significant improvement in distinguishing high-resistance boundary faults. The protection performance and applicability have been validated on a four-terminal VSC-HVDC simulation model based on PSCAD/EMTDC.© 2017 Elsevier Inc. All rights reserved.

Optimal Torque Sharing Function Control for Switched Reluctance Motors Based on Active Disturbance Rejection Controller

In this article, an optimal torque sharing function (TSF) control method incorporated with improved linear active disturbance rejection control (LADRC) and modified coyote optimization algorithm (MCOA) is introduced and applied in switched reluctance motors (SRMs). First, the piecewise TSF is employed to reduce the torque ripple, which exhibits little effects on the rate of current change and the current peak value. The improved linear extended state observer with the variable gain in speed controller using LADRC is designed to guarantee better antidisturbance ability and torque ripple reduction simultaneously. Then, the MCOA is introduced to automatically tune the parameters including the turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> angle, conduction angle, and coefficients for better comprehensive performances. Finally, comparisons among the conventional TSF with LADRC, the piecewise TSF with LADRC, and the proposed TSF with improved LADRC are conducted both in the simulations and experiments. The results indicate that the proposed method behaves best in aspects of torque ripple suppression and anti-interference ability among the three methods.

Transient analysis and safety-oriented process optimization during electrolysis–fuel cell transition of a novel reversible solid oxide cell system

The reversible solid oxide cell (rSOC) is an emerging solution for power-gas conversion in renewable energy networks owing to its high efficiency and bi-directional operation. However, there are still many unidentified safety issues endangering the stability and lifespan of rSOC that need to be addressed before its widespread commercialization. In this paper, a novel one-dimensional rSOC stack model incorporating peripheral auxiliary components is introduced to investigate the transient behavior of the co-flow rSOC stack during electrolysis–fuel cell transition and to develop a safety-oriented optimization strategy for the switching process. This is the first comprehensive study of thermal−material safety hazards for rSOC in the system environment and the first proposal of a dual-model predictive control strategy to avoid nonlinearities in global predictive control during cross-mode switching. It is found that localized extreme temperature gradients, fuel starvation and thermal oscillations are the main safety issues faced by rSOC in switching transients. The conclusion that the current stride and the rate of current change are key factors in guaranteeing the transient safety of rSOC is obtained by evaluating targeted dispatch currents. On this basis, the constraint of current-change rate of 7 A s−1 is incorporated into the controller design, further results indicated that the proposed cooperative control strategy effectively prevents the reactant crisis with smoother thermodynamic responses, which are all within the safety threshold.

Long‐term herbivore removal experiments reveal how geese and reindeer shape vegetation and ecosystem CO2‐fluxes in high‐Arctic tundra

Abstract Given the current rates of climate change, with associated shifts in herbivore population densities, understanding the role of different herbivores in ecosystem functioning is critical for predicting ecosystem responses. Here, we examined how migratory geese and resident, non‐migratory reindeer—two dominating yet functionally contrasting herbivores—control vegetation and ecosystem processes in rapidly warming Arctic tundra. We collected vegetation and ecosystem carbon (C) flux data at peak plant growing season in the two longest running, fully replicated herbivore removal experiments found in high‐Arctic Svalbard. Experiments had been set up independently in wet habitat utilised by barnacle geese Branta leucopsis in summer and in moist‐to‐dry habitat utilised by wild reindeer Rangifer tarandus platyrhynchus year‐round. Excluding geese induced vegetation state transitions from heavily grazed, moss‐dominated (only 4 g m−2 of live above‐ground vascular plant biomass) to ungrazed, graminoid‐dominated (60 g m−2 after 4‐year exclusion) and horsetail‐dominated (150 g m−2 after 15‐year exclusion) tundra. This caused large increases in vegetation C and nitrogen (N) pools, dead biomass and moss‐layer depth. Alterations in plant N concentration and CN ratio suggest overall slower plant community nutrient dynamics in the short‐term (4‐year) absence of geese. Long‐term (15‐year) goose removal quadrupled net ecosystem C sequestration (NEE) by increasing ecosystem photosynthesis more than ecosystem respiration (ER). Excluding reindeer for 21 years also produced detectable increases in live above‐ground vascular plant biomass (from 50 to 80 g m−2; without promoting vegetation state shifts), as well as in vegetation C and N pools, dead biomass, moss‐layer depth and ER. Yet, reindeer removal did not alter the chemistry of plants and soil or NEE. Synthesis. Although both herbivores were key drivers of ecosystem structure and function, the control exerted by geese in their main habitat (wet tundra) was much more pronounced than that exerted by reindeer in their main habitat (moist‐to‐dry tundra). Importantly, these herbivore effects are scale dependent, because geese are more spatially concentrated and thereby affect a smaller portion of the tundra landscape compared to reindeer. Our results highlight the substantial heterogeneity in how herbivores shape tundra vegetation and ecosystem processes, with implications for ongoing environmental change.

Fast detection of short circuits in low-voltage AC systems based on wavelet packet transform and current change rate

The safe and stable operation of a new low-voltage power system requires the research and application of fast detection technology of short-circuit faults. However, the existing methods are difficult to effectively realize the rapidity and reliability in case of short circuits with unclear features and various interference conditions. Therefore, the fault feature of short-circuit current in the full phase angle range is analyzed, and a new method of short-circuit detection based on wavelet packet transform and current change rate is proposed. Among them, the fast-action detection method of wavelet packet transform is used for faults with obvious features to achieve detection rapidity, and the double criteria backup detection method of wavelet packet transform and current change rate is used for faults with unclear features to ensure detection reliability. On this basis, the hardware technology realization of short-circuit fault fast detection algorithm is studied. For short circuit faults, load startup, load switching, and other situations, the real low-voltage AC system experiment is carried out to verify. Finally, the test shows that the detection method can effectively and rapidly detect short-circuit faults within 1ms in the full phase angle range, and has robustness under interference conditions.

Short-circuit Fault Detection in Low-voltage DC Microgrids Based on Improved Current Change Rate

Along with the explosion of new energy sources, DC microgrid has obvious advantages as well as better development paths, but reliable fault detection is still one of the key issues to be solved for DC microgrid. The fault current characteristics are analyzed by a fault RLC equivalent circuit, and the characteristics at different fault location points are further analyzed on the independent DC microgrid model composed of a PV generation unit, an energy storage unit, and a load unit. A fault detection method based on the improved current change rate is proposed by combining the current abrupt change direction. A DC microgrid model with a bus voltage of 400 V is built and simulated in Matlab/Simulink. The simulation results show that the proposed method can detect and isolate bus and unit short-circuit faults in less than 2 ms, ensuring the proper operation of the whole system, which has a certain reference significance for fault protection of low-voltage DC microgrids at independent operation sites.

Evaluation of two model predictive control schemes with different error compensation strategies for power management in fuel cell hybrid electric buses

Fuel cell hybrid electric buses (FCHEBs) employing hydrogen fuel cells as the main power source and supercapacitors as the energy buffer could be a feasible electrified transportation technology. This paper evaluates two model predictive control (MPC) schemes with different error compensation strategies for power management in FCHEBs: MPC scheme with Adaptive Compensation (denoted as AC-MPC) and MPC scheme with Gaussian Process Regression Compensation (denoted as GPRC-MPC). AC-MPC introduces adaptive weights based on the supercapacitor state of charge (SOC) and compensates for the errors associated with the linearization of the nonlinear fuel cell/supercapacitor hybrid energy storage system. GPRC-MPC utilizes Gaussian process regression to predict and compensate for the load disturbance error and the residual error. AC-MPC and GPRC-MPC are evaluated using the New York Bus (NYBus) drive cycle and a drive cycle collected along the GBG17 bus route in Sweden. Simulation results demonstrate the effectiveness of AC-MPC and GPRC-MPC in improving the hydrogen system performance by reducing the hydrogen consumption and the maximum fuel cell current change rate compared to the linear MPC scheme without any compensation while ensuring that the supercapacitor SOC is bounded.

Variable Amplitude Gate Voltage Synchronous Drive Technique for Improving Dynamic Current Balancing in Paralleled IGBTs

The problem of current sharing imbalance in the parallel connection of IGBT multi-modules affects the wide-scale application of parallel IGBT. The current imbalance problem in the dynamic process is mainly caused by the difference in control loop parameters. In parallel IGBT applications, current sharing is a critical concern. Objective differences in IGBT module and driver circuit parameters, as well as incomplete symmetry in the power circuit, lead to inconsistent parasitic parameters, resulting in both static and dynamic current-sharing issues. Static current sharing refers to the uneven distribution of load current under static operating conditions, while dynamic current sharing refers to the imbalance in current distribution among parallel IGBT modules during turn-on and turn-off processes. This is mainly influenced by the synchronization of turn-on and turn-off timings and the consistency of collector current change rates during these processes. The difference in characteristic parameters of IGBT modules is an important factor leading to the difference in control loop parameters, which has a profound impact on the dynamic current-sharing characteristics of IGBT parallel applications. In the case where the device parameters cannot be changed, some drive compensation controls can compensate for the influence of device differences on dynamic current sharing. Accurate identification of the characteristic parameters of the IGBT module is the key to this method. This paper mainly studies a synchronous variable-amplitude drive scheme and studies the influence of parameters such as synthetic gate resistance, gate-emitter capacitance, and on-off gate threshold voltage on the dynamic current-sharing characteristics. The correlation characteristics of the characteristic parameters of the IGBT device body are studied, and the characteristic model of each parameter and the influencing variable is constructed. The parallel working model of PSpice devices is established, and the influence of different characteristic parameters on the current-sharing characteristics is evaluated, and its sensitivity is summarized through simulation analysis. Through the 1700 V/300 A IGBT parallel switch characteristic experiment, the current sharing effectiveness of the synchronous variable amplitude driving method is verified. Finally, the effects of different gate control voltages and different action times on the dynamic current-sharing characteristics are summarized.

CLIMATE CHANGE MITIGATION AND ADAPTATION: WITH OR AGAINST INDIGENOUS PEOPLES?

Climate change and its negative consequences represent a common problem for all the people on Earth and are likely to become one of the most serious challenges that humankind faces. As such, mitigation measures and adaptation actions are of particular importance. Although often thought as the two sides of the same coin, the climate change mitigation and adaptation differ from each other, especially in the context of indigenous peoples. Therefore, the first part of the paper centres on the relation between climate change mitigation and adaptation and their consequences for indigenous communities. The newest international treaty on climate change, the Paris Agreement, establishes the global goal on adaptation, which should take into consideration vulnerable groups, communities and ecosystems, and more importantly, should be based on and guided by the best available science and knowledge of indigenous peoples, often referred to as ‘traditional knowledge’. As such, the second part of the paper focuses on the adaptation methods guided by the traditional knowledge. Although examples include indigenous peoples’ traditional knowledge from all over the globe, much attention is given to the Arctic Indigenous Peoples as, due to current speed of climate change, the Arctic is recognized as a global climate change hotspot. Although indigenous peoples have been living in their territories since the time immemorial, adapting their ways of life to the difficult weather and environmental conditions, with the current climate change happening so rapidly, their possibilities of adaptation are weakening and climate change renders them more vulnerable, altering their economic and cultural activities and threatening their very existence. However, the current rate of climate change is not the only factor impairing the indigenous peoples’ adaptive capacities. Therefore, the final part of the paper is aimed at presenting what the obstacles to the successful adaptation to climate change are and whether migration should be considered an adaptive action.

Piezotronic and Piezo-Phototronic Effects-Enhanced Core-Shell Structure-Based Nanowire Field-Effect Transistors.

Piezotronic and piezo-phototronic effects have been extensively applied to modulate the performance of advanced electronics and optoelectronics. In this study, to systematically investigate the piezotronic and piezo-phototronic effects in field-effect transistors (FETs), a core-shell structure-based Si/ZnO nanowire heterojunction FET (HJFET) model was established using the finite element method. We performed a sweep analysis of several parameters of the model. The results show that the channel current increases with the channel radial thickness and channel doping concentration, while it decreases with the channel length, gate doping concentration, and gate voltage. Under a tensile strain of 0.39‱, the saturation current change rate can reach 38%. Finally, another core-shell structure-based ZnO/Si nanowire HJFET model with the same parameters was established. The simulation results show that at a compressive strain of -0.39‱, the saturation current change rate is about 18%, which is smaller than that of the Si/ZnO case. Piezoelectric potential and photogenerated electromotive force jointly regulate the carrier distribution in the channel, change the width of the channel depletion layer and the channel conductivity, and thus regulate the channel current. The research results provide a certain degree of reference for the subsequent experimental design of Zn-based HJFETs and are applicable to other kinds of FETs.

Prediction of abnormal conditions for fused magnesium furnace based on improved LSTM model and rule-based reasoning

There are some abnormal conditions during the fused magnesia smelting process (FMSP), making it crucial for the operators to predict their occurrence to ensure proper guidance of the operation. In this paper, a prediction method is proposed for current and sound signals in the FMSP based on the Temporal convolutional network-Bidirectional-Long short-term memory-Attention (TCN-Bi-LSTM-Attention) model. Through analysis of abnormal conditions in the FMSP, according to the characteristics of abnormal conditions and the change of current change rate before and after prediction, an abnormal condition identification scheme based on rule-based reasoning (RBR) that utilizes current and sound signals is constructed. The results of the experiment showed that when considering the same prediction steps, the proposed model had higher prediction accuracy compared to the TCN-Attention model and the Bi-LSTM-Attention model. The proposed abnormal condition identification scheme can predict the type of abnormal condition that will occur in the next 60 s, with recall, precision, and F1 scores of over 90% for four different abnormal conditions.

International climate targets are achievable, but only in models, not in the real world

The article argues that the relationships and historical trends of global temperatures and of fossil-fuel production are now both clear and relatively stable. Hence archival data of past performance allow a ‘speedometer reading’ of current rates of change and enable a direct ‘reality check’ on claims about future climate change. Embedded in a new Hubbert-style resource model the historical rates forecast that surface temperatures remain on course to rise by 4.5°C (6°C over land) by the early 2100s. This unsettling prospect is in close accord with several middle-of-the-road projections in the recent sixth IPCC Assessment Report (2021). Instead, if hoped-for targets of carbon neutrality are to be met and global temperature rises held to well below 2°C, as stipulated in the Paris Agreement, then the current rate of deployment of clean power sources would need to accelerate by an unprecedented 100-fold, to around 50 EJ year−1, within the decade.

Climate or diet? The importance of biotic interactions in determining species range size

AbstractAimSpecies geographical range sizes play a crucial role in determining species vulnerability to extinction. Although several mechanisms affect range sizes, the number of biotic interactions and species climatic tolerance are often thought to play discernible roles, defining two dimensions of the Hutchinsonian niche. Yet, the relative importance of the trophic and the climatic niche for determining species range sizes is largely unknown.LocationCentral and northern Europe.Time periodPresent.Major taxa studiedGall‐inducing sawflies and their parasitoids.MethodsWe use data documenting the spatial distributions and biotic interactions of 96 herbivore species, and their 125 parasitoids, across Europe and analyse the relationship between species range size and the climatic and trophic dimensions of the niche. We then compare the observed relationships with null expectations based on species occupancy to understand whether the relationships observed are an inevitable consequence of species range size or if they contain information about the importance of each dimension of the niche on species range size.ResultsWe find that both niche dimensions are positively correlated with species range size, with larger ranges being associated with wider climatic tolerances and larger numbers of interactions. However, diet breadth appears to more strongly limit species range size. Species with larger ranges have more interactions locally and they are also able to interact with a larger diversity of species across sites (i.e. higher β‐diversity), resulting in a larger number of interactions at continental scales.Main conclusionsWe show for the first time how different aspects of species diet niches are related to their range size. Our study offers new insight into the importance of biotic interactions in determining species spatial distributions, which is critical for improving understanding and predictions of species vulnerability to extinction under the current rates of global environmental change.

Online Junction Temperature Estimation Method for SiC MOSFETs Based on the DC Bus Voltage Undershoot

Silicon carbide (SiC) power devices are promising in industrial applications. Junction temperature monitoring is greatly significant for improving the reliability of devices and systems. However, state-of-the-art SiC MOSFET junction temperature estimation methods generally have drawbacks of low resolution, difficult measurement, and complicated installation. In this article, a novel junction temperature estimation for SiC MOSFETs based on the dc bus voltage undershoot is proposed. The correlation between junction temperature and current change rate is analyzed and verified by experiments. The current change rate of each SiC MOSFET can be measured via the dc bus voltage undershoot because of the stray inductance of the bus commutation loop. The undershoot of the dc bus voltage during the turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> transient displays a linear dependence on the junction temperatures of the corresponding SiC MOSFET. Hence, the dc bus voltage undershoot can be utilized for monitoring the junction temperatures of two SiC MOSFETs in the half-bridge. Besides, practical implementation and estimation errors are presented. The method proposed has high accuracy and resolution for junction temperature monitoring. Besides, the method proposed can reduce the complexity, size, and cost of the monitoring circuit. Moreover, the method proposed is noninvasive and easy to install. It is promising for SiC MOSFET junction temperature monitoring in practical applications.

Adaptive Model Predictive Current Control for PMLSM Drive System

This article proposes an adaptive model predictive current control (AM-MPCC) for surface-mounted permanent magnet linear synchronous motor systems to simultaneously enhance the robustness against permanent magnet flux, inductance, and resistance mismatches. First, the conventional continuous control set model predictive control is analyzed, illustrating that parameter variations will inevitably deteriorate the current regulation performance. Then, an adaptive predictive model, which involves a disturbance term and an optimized current change rate coefficient, is proposed. The optimal coefficient is estimated using a steady-state incremental model and the steepest descent method at each control period. A discrete-time sliding mode disturbance observer is devised based on the adaptive model with updated coefficients to achieve the disturbance term. Finally, an exponential reaching law-based-reference trajectory is defined for the cost function of AM-MPCC to adjust the current approach trajectory. Experimental results verify the excellent robustness performances of the proposed method.

Research on the Switching Characteristics Based on the SiC MOSFET Model

With the continuous development of power electronics technology, the third-generation semiconductor materials represented by SiC and GaN have significant advantages in the band gap width, breakdown electric field, thermal conductivity, electron saturation rate and other key parameters, which meet the needs of modern industry for high power, high voltage and high frequency. When the SiC MOSFET plays its high frequency advantage, with the increase of switching frequency, the voltage change rate and current change rate of the device will be larger in the process of turning on and off. This paper mainly analyzes the characteristics of SiC MOSFET devices, and modifies the model based on the model provided by the manufacturer. By establishing static and dynamic test circuits, the static characteristic curves of the model were observed, and the drain voltage and current waveforms of the original model and the optimized model were compared during the switching process. The results show that the switching time of the optimized model is improved, and the oscillation waveform is greatly improved. Then, the accuracy of the optimized model is verified by the double-pulse circuit, and the drain source voltage and the drain source current are studied and observed under different temperature and drive resistance conditions. This paper provides data support for improving the switching characteristics of SiC MOSFET in practical applications.

Effect of cooling surface temperature difference on the performance of high-temperature PEMFCs

Internal temperature distribution of the high-temperature proton exchange membrane fuel cell (HT-PEMFC) is affected by the cooling temperature, heat generation and reactant gas flow. Reasonable temperature control is helpful to improve the fuel cell performance and durability. In this work, a three-dimensional model that couples the reactant flows, species transport, heat transfer, charge transfer, and electrochemical reaction, was developed to simulate the HT-PEMFC operation. A solid mechanics model was established to analyze the stress distribution of the fuel cell. The polarization curves, distributions of temperature, membrane proton conductivity, current density and stress are investigated for different cooling surface temperature. Furthermore, the effect of assembly temperature on the stress of phosphoric acid-doped polybenzimidazole (PBI) membrane is discussed. Results reveals that the peak power density and uniformity of current density decrease with the increase of cooling surface temperature difference. The peak power density decreases by 9.14% when the temperature difference increases from 0 K to 40 K. The cooling surface temperature difference of less than 10 K and the voltage range in 0.5–0.7 V can achieve better current density uniformity and smaller current density change rate. In addition, the membrane in fuel cell has the highest stress, and increasing the assembly temperature is helpful to reduce the membrane stress. When the assembly temperature increases from 293.15 K to 343.15 K, the max and min compressive stresses in membrane in-plane decrease from 39.436 MPa to 31.416 MPa–24.934 MPa and 17.369 MPa at the temperature difference of 30 K, which decreases by 36.77% and 44.7%, respectively.

A novel model predictive control strategy of D-PMSG wind turbine systems for LVRT based on two-state unloading resistance and super capacitor

For low voltage ride through (LVRT) of the wind power generation system, rotor energy storage and super capacitor are promising options. When the rotor energy storage cooperates with the super capacitor for LVRT, the DC voltage will undulate violently due to the speed fluctuation. To solve this problem, a crowbar circuit topology and its control strategy including unloading resistance and super capacitor are proposed in this paper. During the process of LVRT, the super capacitor and resistor absorb energies together. In doing so, the DC bus voltage fluctuation will be suppressed by changing the value of the unloading resistance. The proposed method can effectively reduce the power of the unloading resistor and the capacity of super capacitor, and further decrease the hardware cost. By adding the penalty term of the current change rate to the cost function using the model predictive control method (MPC), the DC bus voltage fluctuation is reduced with the realization of rotor energy storage. The control performances of the proposed LVRT strategy are validated through simulation results.