Current Fluctuations Research Articles

A proactive energy management strategy for battery-powered autonomous systems

Battery energy management systems have been studied in control communities for many years. This paper proposes a new perspective by integrating control and scheduling for battery-powered autonomous systems. This is motivated by the observations that battery closed-loop control can significantly improve the DC-bus stability but reduce the battery durability, while load scheduling can considerably improve the battery durability by smoothing the load power. In view of the above findings, we propose a proactive energy management strategy for the battery energy management system to improve both the DC-bus stability and battery durability. We first analyze the schedulability of load tasks to check if they are schedulable. Then, the power of schedulable loads is scheduled with an active load scheduling algorithm to smooth the fluctuation of battery current and extend the battery lifetime. Thereafter, the scheduled load power is integrated with a feedforward control to restrain DC-bus voltage fluctuation. In addition to the classical sporadic/periodic load tasks model, we propose a new aperiodic load task model to characterize the load power triggered by events in practical applications. An experimental platform is built to verify the effectiveness of the proposed proactive energy management method. Experimental results show that the proposed proactive energy management method can suppress the 15.71% DC-bus voltage fluctuation and reduce the 8.93% battery current fluctuation, extending the battery lifetime by 7.57% compared to existing energy management strategies.

Low-temperature stable ferroelectric–antiferroelectric transition for cryogenic energy storage application

The capacitors are in rising demand for cryogenic applications. As for now, it still remains an ongoing challenge for simultaneously achieving high energy storage density and cryogenic temperature stability. Herein, the strategy of stable backward phase transition was demonstrated in the antiferroelectric composition of (Pb0.9175La0.055)(Zr0.975Ti0.025)O3. As a result, we achieved high recoverable energy density about 10 J/cm3 with exceptional low-temperature stability from −160 to 25 °C. Multi-layer ceramic capacitors designed for pulse discharge applications also demonstrated high performance in cryogenic conditions, with the peak current fluctuations of less than 4%. Through in situ characterizations using x-ray diffraction, Raman spectra, and transmission electron microscopy, we discovered that the anisotropic structural evolution is responsible for a stable backward phase transition, providing the material with robust stability at cryogenic temperatures. These results offer a good paradigm for improving the temperature stability of antiferroelectric multi-layer capacitors to meet the rigorous demands of energy storage applications.

Hyperchaotic power with wide current variation for efficient manganese electrodeposition

A practical hyperchaotic circuit has been designed, which has further been successfully applied to the manganese metal electrolysis system, replacing the traditional direct current power to alter the dynamic system of electrolysis process. The results illustrate that the hyperchaotic current can significantly suppress the electrochemical oscillation. Therefore, the growth of manganese (Mn) dendrites in the cathode can be significantly suppressed by the ultra − wide chaotic current fluctuation because of the regulation of electronic dynamic system. In addition, the distribution of manganese dendrites is quantified for the first time through image analysis, processing, and calculation. Besides, the hyperchaotic current can also considerably improve the current efficiency with 2 % increasing and reduce the energy consumption about 0.3 kW·h/kg simultaneously. It also demonstrates some advantages of chaotic current electrodeposition technology by conducting a larger-scale chaotic current electrolysis experiment.

A 1.25-GS/s 10-bit single-channel ring amplifier-based pipelined ADC in 28-nm CMOS

This paper proposed a pipelined analog-to-digital converter (ADC) that utilizes a high-linearity input buffer and a two-step input-split fully differential ring amplifier (ringamp). The implemented input buffer based on a gain-boost cascode current source, is optimized for linearity over a wider frequency range by suppressing fluctuations in tail current. To save power consumption without compromising common-mode and power-supply rejection, a fully differential ring amplifier is employed as the residue amplifier. Additionally, a correlation-based calibration is implemented, which involves injecting pseudo-random dither signals into each multiplying digital-to-analog converter (MDAC) stage to enhance linearity. Fabricated in a 28-nm CMOS process, the 1.25-GS/s 10-bit ADC achieves a spurious-free dynamic range (SFDR) of 70.7 dB and a signal-to-noise-and-distortion ratio (SNDR) of 50.3 dB at Nyquist input. The core conversion circuits of the ADC consume only 30.2 mW from a single 1-V supply. This translates to a Walden figure of merit (FoM) of 90 fJ/conversion-step and a Schreier FoM of 153.5 dB, respectively.

Performance improvement of a standalone PV system using supercapacitors: modeling and energy management

Standalone photovoltaic (PV) systems are the most common and practical application in remote areas and communities far from the power grid. However, in the case of supplying a pulsating load with only a battery as a storage unit, their performance degraded. Therefore, hybrid electrical energy storage (HEES) systems represent a viable solution. This paper investigates the impact of utilizing a supercapacitor (SC) to work cooperatively with a battery storage unit to enhance the overall system behavior. Two scenarios of battery storage systems with/without SC are considered. A comprehensive modeling and sizing approach is established and presented in detail. Then, an energy management system (EMS) is proposed to enhance the HEES system’s performance. A proportional-integral (PI)-based controller is designed and examined to control the power electronic converters and hence improve energy management. The HEES system operation is simulated and evaluated using MATLAB/Simulink to feed a pulsating load, where the drawn pulsated load current is composed of two components: one component is supplied by battery, and the other component is fed from SC. Finally, the performance of the two hybrid configurations is evaluated in terms of battery voltage and current fluctuations, transient response, and load voltage and current ripples. The obtained results demonstrate the effectiveness of introducing SCs into HEES system.

Simulation characterization of measurement errors of the wide-range environmentally friendly current transformers

To accurately measure the hundreds of millions of dollars of electricity consumed, the accuracy, safety, environmental friendliness, and reliability of current transformers become crucial. In response to these problems, there is an urgent need to develop an environmentally friendly current transformer that can adapt to the needs of power systems with wide-range current fluctuations. Therefore, in this paper, the simulation model of a three-phase current transformer with a combined transformer is developed. Simulation and verification work for the relationship between the error characteristics of environmentally friendly current transformers and the influence of magnetic field changes in each phase and the magnitude of the load on the secondary side. We compared the measurement errors before and after active compensation, demonstrating that environmentally friendly current transformers can increase the range and measurement flat frequency range while ensuring their 0.2S class measurement accuracy. This in turn proves the feasibility of wide-range environmentally friendly current transformers.

Assessing the role of tidal cycle, waves, and wind as drivers of surf zone zooplankton on a temperate sandy beach

The surf zone is strongly affected by tides, waves, and winds. However, there are still a lack of knowledge about the response of the zooplankton community to these physical factors in the surf area, with a particular emphasis on tidal effects. The aim of this study was to conduct a preliminary assessment of two distinct tidal cycles, encompassing fluctuations in on-offshore currents, waves, and wind and their influence on the surf zooplankton community of Pehuen Co (PC) sandy beach, Argentina. The study involved field sampling at a single station in the surf zone on September 4th, 2018, and May 20th, 2019. The sampling covered four tidal phases at 3-hour intervals, when water and zooplankton samples were collected for analysis. Environmental variables, such as current velocities, water level, and wind data, among others, were also registered. The results indicated that the abundance of surf zooplankton was significantly influenced by physical forces, resulting in distinct impacts. During the Sept 2018 tidal cycle (calm conditions), an on-offshore current emerged as the primary driving force, resulting in the highest abundance of zooplankton being observed at low tide. In contrast, during the May 2019 tidal cycle (southern winds), strong winds intensified the offshore current velocities and wave height, affecting the zooplankton abundance. High velocities of on-offshore currents corresponded to lower abundance of zooplankton at low tide. This situation introduced an extra physical force -the wind- playing a significant role in restructuring the dynamic of the zooplankton community. The preliminary analysis suggests that the relationship between environmental and biological data is complex and varies depending on the physical factors involved. Notably, in rough conditions, south winds can restructure zooplankton dynamics, influenced by strong winds. This work emphasizes the importance of the surf zone waters of sandy beaches and are useful for future research or monitoring programmes of similar high-energy ecosystems.

Current fluctuations in a partially asymmetric simple exclusion process with a defect particle.

We study an exclusion process on a ring comprising a free defect particle in a bath of normal particles. The model is one of the few integrable cases in which the bath particles are partially asymmetric. The presence of the free defect creates localized or shock phases according to parameter values. We use a functional approach to Bethe equationsresulting from a nested Bethe ansatz to calculate exactly the mean currents and diffusion constants. The results agree very well with Monte Carlo simulations and reveal the main modes of fluctuation in the different phases of the steady state.

The Thousand-Pulsar-Array programme on MeerKAT – XII. Discovery of long-term pulse profile evolution in seven young pulsars

ABSTRACT A number of pulsars are known to have profile evolution on time-scales of months, often correlated with spin-down rate changes. Here, we present the first result from 3 yr of monitoring observations from MeerKAT as part of the Thousand Pulsar Array programme. This programme obtains high-fidelity pulse profiles for ∼ 500 pulsars, which enabled the detection of subtle changes in seven sources not previously known to exhibit long-term profile evolution. A 2D Gaussian convolution is used to highlight correlated emission variability in both the pulse phase and observing epoch direction. Simulations show that for one additional source the observed profile variability is likely to originate from stochastic single-pulse shape variability (jitter). We find that it is common for long-term profile variability to be associated with changes in polarization fractions, but not with polarization position angle (PA) changes. PA changes are expected if emission height changes or precession is responsible for the profile variability. PSR J1741−3927 is the only pulsar in our sample that shows correlated PA variability, and this is associated with orthogonal polarization mode activity. For the six other pulsars limits on possible emission height changes and impact angle changes are derived. These limits are consistent with the small changes in the total intensity profile shape. None of the sources show detectable spin-down variability correlated with the emission changes, which are thought to be driven by magnetospheric current fluctuations. Therefore, the absence of correlated spin-down rate variability allows upper limits to be placed on changes in the magnetospheric charge density.

Exogenous application of nano-silicon, potassium sulfate, or proline enhances physiological parameters, antioxidant enzyme activities, and agronomic traits of diverse rice genotypes under water deficit conditions

Water deficit is a critical obstacle that devastatingly impacts rice production, particularly in arid regions under current climatic fluctuations. Accordingly, it is decisive to reinforce the drought tolerance of rice by employing sustainable approaches to enhance global food security. The present study aimed at exploring the effect of exogenous application using different biostimulants on physiological, morphological, and yield attributes of diverse rice genotypes under water deficit and well-watered conditions in 2-year field trial. Three diverse rice genotypes (IRAT-112, Giza-178, and IR-64) were evaluated under well-watered (14400 m3/ha in total for the entire season) and water deficit (9170 m3/ha) conditions and were exogenously sprayed by nano-silicon, potassium sulfate, or proline. The results showed that drought stress substantially decreased all studied photosynthetic pigments, growth traits, and yield attributes compared to well-watered conditions. In contrast, antioxidant enzyme activities and osmoprotectants were considerably increased compared with those under well-watered conditions. However, the foliar application of nano-silicon, potassium sulfate, and proline substantially mitigated the deleterious effects of drought stress and markedly enhanced photosynthetic pigments, antioxidant enzyme activities, growth parameters, and yield contributing traits compared to untreated stressed control. Among the assessed treatments, foliar spray with nano-silicon or proline was more effective in promoting drought tolerance. The exogenous application of proline improved chlorophyll a, chlorophyll b, and carotenoids by 21.4, 19.6 and 21.0% followed by nano-silicon treatment, which enhanced chlorophyll a, chlorophyll b, and carotenoids by 21.1, 17.6 and 9.5% compared to untreated control. Besides, the application of proline demonstrated a superior improvement in the content of proline by 52.5% compared with the untreated control. Moreover, nano-silicon exhibited the maximum enhancement of catalase and peroxidase activity compared to the other treatments. The positive impacts of applied exogenously nano-silicon or proline significantly increased panicle length, number of panicles/plant, number of grains/panicle, fertility percentage, 1000-grain weight, panicle weight, and grain yield, compared to untreated plants under water deficit conditions. In addition, the physiological and agronomic performance of evaluated rice genotypes significantly contrasted under drought conditions. The genotype Giza-178 displayed the best performance under water deficit conditions compared with the other genotypes. Consequently, the integration of applied exogenously nano-silicon or proline with tolerant rice genotype as Giza-178 is an efficient approach to ameliorating drought tolerance and achieving agricultural sustainability under water-scarce conditions in arid environments.

Determining Transmission Characteristics from Shot-Noise-Driven Electroluminescence in Single-Molecule Junctions.

Biased metal-molecule-metal junctions emit light through electroluminescence, a phenomenon at the intersection of molecular electronics and nanoplasmonics. This can occur when the junction plasmon mode is excited by inelastic electron current fluctuations. Here, we simultaneously measure the conductance and electroluminescence intensity from single-molecule junctions with time resolution in a solution environment at room temperature. We use current versus bias data to determine the molecular junction transport parameters and then relate these to the expected current shot noise. We find that the electroluminescence signal accurately matches the theoretical prediction of shot-noise-driven emission in a large fraction of the molecular junctions studied. This introduces a novel experimental method for qualitatively estimating finite-frequency shot noise in single-molecule junctions under ambient conditions. We further demonstrate that electroluminescence can be used to obtain the level alignment of the frontier orbital dominating transport in the molecular junction.

Recent hummock establishment in the margin of a subarctic fen, Finnish Lapland

Northern fens, that host unique biota and form a remarkable carbon stock, are sensitive to changes in the moisture balance and, therefore, may be strongly affected by climatic fluctuations. However, long‐term monitoring and palaeoecological studies of fens are relatively rare and, as a result, their responses to past and current climatic fluctuations are poorly known. In this study, we examined the recent vegetation change as well as changes in testate amoeba communities in the mire margin of a subarctic fen in Finnish Lapland with four peat profiles. Testate amoebae were used as indicators of past fluctuations in water table depth. The vegetation showed a drastic shift from sedge‐dominated fen to Sphagnum‐dominated communities during the late 20th and the early 21st centuries. This shift was accompanied by a turnover in the testate amoeba community. Testate amoeba‐based water table reconstructions indicated recent drying. This may be due to the lowering of the water table either from accelerated Sphagnum increment or enhanced evaporation. The observed hummock establishment concurs with the documented hemisphere‐wide expansion trend of hummock communities in fens. This change may strengthen the carbon sink and storage capacity of these peatlands, which could be viewed as a welcome negative feedback process to the ongoing climate warming. However, the change also poses a threat to biodiversity since fens are not only species‐rich habitats but are also endangered ecosystems.

Enhancing the sensitivity of nanopipette biosensors for protein analysis

AbstractBackgroundThis paper compares experimental findings and simulation outcomes of single and multiple protein models moving through a nanopipette biosensor. It provides insights into the factors influencing the process and explores their relevance to proteomics.MethodsNanopipette biosensors were produced by pulling borosilicate glass tubes and treating them with an electron beam. A scanning electron microscope was used to characterize the nanopipettes. The study measured and modeled ionic currents for the elastase‐specific inhibitor protein. Simulation models were developed using the finite element method and Poisson–Boltzmann formalism, considering different protein configurations and translocation scenarios.ResultsThe results showed that the pore current of a nanopipette decreases as the protein approaches the nanopipette. The minimum pore current occurs at the widest part of the protein, and the current increases as the protein progresses through the nanopipette. For multiple protein translocations, the pore current decreases between the widest parts of the first and second proteins, and the lowest current is observed at the broadest part of the second protein. After the third protein, the pore current remains constant. It is also found that the fractional blockade difference, translocation speed, fluctuation in pore current, and dwell time are all affected by the number of proteins translocating through the nanopipette. The fractional blockade difference, the decrease in pore current caused by the protein, increases with the number of proteins while the translocation speed decreases. The fluctuation in pore current and dwell time is also longer for three‐protein translocations than for single‐protein translocations.ConclusionThis study offers valuable insights into biomolecule transport through nanopipettes, enhances our understanding of protein dynamics in restricted environments, and significantly contributes to single‐protein sequencing studies, drug screening, and proteomics.

Cluster-Enhanced Nanopore Sensing of Ovarian Cancer Marker Peptides in Urine.

The development of novel methodologies that can detect biomarkers from cancer or other diseases is both a challenge and a need for clinical applications. This partly motivates efforts related to nanopore-based peptide sensing. Recent work has focused on the use of gold nanoparticles for selective detection of cysteine-containing peptides. Specifically, tiopronin-capped gold nanoparticles, trapped in the cis-side of a wild-type α-hemolysin nanopore, provide a suitable anchor for the attachment of cysteine-containing peptides. It was recently shown that the attachment of these peptides onto a nanoparticle yields unique current signatures that can be used to identify the peptide. In this article, we apply this technique to the detection of ovarian cancer marker peptides ranging in length from 8 to 23 amino acid residues. It is found that sequence variability complicates the detection of low-molecular-weight peptides (<10 amino acid residues), but higher-molecular-weight peptides yield complex, high-frequency current fluctuations. These fluctuations are characterized with chi-squared and autocorrelation analyses that yield significantly improved selectivity when compared to traditional open-pore analysis. We demonstrate that the technique is capable of detecting the only two cysteine-containing peptides from LRG-1, an emerging protein biomarker, that are uniquely present in the urine of ovarian cancer patients. We further demonstrate the detection of one of these LRG-1 peptides spiked into a sample of human female urine.

Parallel Operation Strategy of Inverters Based on an Improved Adaptive Droop Control and Equivalent Input Disturbance Approach

The operation of parallel inverters in microgrids is an important way to expand system capacity, but there are problems of circulating current fluctuations and power sharing errors in parallel inverters’ operation. In this paper, a parallel operation strategy for inverters based on improved adaptive droop control and Equivalent Input Disturbance (EID) is proposed. Firstly, the model and control topology of parallel inverters are presented. Secondly, in order to solve the power sharing error caused by impedance difference and the voltage drop caused by virtual impedance, a reference voltage generator based on improved adaptive droop control is proposed. Then, considering the circulating current fluctuation as a disturbance, a voltage controller based on an equivalent input disturbance approach is proposed to reduce the disturbance. Finally, simulation in MATLAB/Simulink is carried out to verify the effectiveness of the parallel operation strategy.

Experimental investigation and validation on an air-source heat pump frosting state recognition method based on fan current fluctuation signal and machine learning

Thick frost on the evaporators of air-source heat pumps and refrigeration systems can degrade system performance. Defrosting in time based on precise frosting state recognition method is of great importance. Indirect measuring recognition method with low accuracy is widely used in commercial systems, for cheapness and simpleness, needing improvement urgently. While accurate direct measuring methods are usually expensive and complicated. Therefore, a novel frosting state recognition method with high accuracy is proposed, which can be realized with a simple current sensor. The method is based on the micro fluctuation in the evaporator fan current (rather than current amplitude) caused by the perturbed air due to frost. An experimental setup is built to obtain fan current samples. Combining three feature extraction approaches and three classifiers, four frost state recognition methods using fan current fluctuation are merged. They are compared and studied based on the experimental samples. Results show original signal + 1D-CNN method has the best identification performance, reaching 95.74 ± 1.73 % accuracy at −10 °C evaporator air temperature. It reveals 94.53 ± 1.06 % accuracy in a temperature range of −5∼-20 °C, and 94.73 ± 1.00 % accuracy for another fan with the same model. The method has significant improvement in performance and good potential for further study and application.

A real‐time energy management control strategy of hybrid energy system for a pure electric loader

SummaryTo enhance the efficiency and prolong the battery life of hybrid energy systems equipped with battery and supercapacitor for a pure electric loader, this paper proposes a real‐time energy management strategy based on model predictive control (MPC). First, the working characteristics of the loader and the topology structure of the hybrid energy are analyzed. Second, considering the repetitive operation model of electric loaders, a neural network algorithm based on long short‐term memory is used to predict power and a dynamic programming algorithm is used as the rolling optimization solution for MPC strategy. Finally, the MPC is verified using the simulation in MATLAB/Simulink. The results indicate that compared with other strategies, the MPC strategy can improve hybrid energy efficiency and reduce the maximum battery current fluctuations. The proposed method demonstrates the feasibility and effectiveness of the hybrid energy system.

Operation and Coordinated Energy Management in Multi-Microgrids for Improved and Resilient Distributed Energy Resource Integration in Power Systems

Multi-microgrids (MMGs) revolutionize integrating and managing diverse distributed energy resources (DERs), significantly enhancing the overall efficiency of energy systems. Unlike traditional power systems, MMGs comprise interconnected microgrids that operate independently or collaboratively. This innovative concept adeptly addresses challenges posed by pulsed load effects, capitalizing on the cooperative nature of interconnected microgrids. A coordinated MMG system effectively redistributes and shares the impact of pulsed loads, mitigating voltage fluctuations and ensuring sustained system stability. The proposed cooperative MMG scheme optimizes power distribution and load prioritization, facilitating the seamless allocation of surplus energy from neighboring microgrids to meet sudden surges in demand. This study focuses on DC standalone multi-microgrid systems, showcasing their inherent adaptability, resilience, and operational efficiency in managing pulse, variable, and unpredictable generation deficits. Several experiments on a laboratory-scale DC multi-microgrid validate the system’s robust performance. Notably, transient current fluctuations during pulse loads are promptly stabilized through the effective collaboration of microgrids. Variable load experiments reveal distinct behaviors, shedding light on the profound influence of control strategies. This research reveals the transformative potential of MMGs in addressing energy challenges, with a particular focus on DC standalone multi-microgrid systems. The findings underscore the adaptability and resilience of the proposed cooperative scheme, marking a significant stride in the evolution of modern power systems.

On sizing of battery energy storage systems for PV plants power smoothing

The high variability of solar irradiance causes fluctuations in the generation of photovoltaic (PV) power plants. This characteristic affects power system operation, thus, strategies are necessary to mitigate the intermittent characteristics of PV power plants. Several countries adopt grid codes incorporating ramp rate (RR) limitations for PV power injection into the grid, also known as power smoothing control. In this sense, battery energy storage systems (BESS) with coordinated RR control algorithms are commonly applied to mitigate current fluctuations from the PV system to the grid. Therefore, studies on the effect of local solar irradiance on BESS requirements for PV power smoothing applications are very important. It is also worth highlighting that in the literature there is a gap in the evaluation of aspects of battery lifetime, BESS volume, price and BESS oversizing for selecting an ideal battery model, among a catalog of batteries, constituting an industrial concern. Therefore, this work presents a detailed BESS sizing methodology, evaluating aspects of the energy requirements, power, and discharging rate (C-rate), based on the mission profile (featuring a customized solution for each project). In addition, the effect of the battery temperature control on the BESS sizing is evaluated. The case study is based on a 1 MW PV system, assessed using a one-year mission profile of solar irradiance and ambient temperature from Goiânia-Brazil. The PV plant is connected to a 440 V grid associated with a BESS that mitigates oscillations of 10%/min. The BESS sizing is evaluated in terms of BESS volume, lifetime, and oversizing factor for power and energy. The proposed methodology reduces the BESS volume by 57.14% in relation to the traditional BESS design of literature.

Physics-based modeling of surface potential and leakage current for vertical Ga2O3 FinFET

Gallium oxide (Ga2O3) is a promising ultra-wide bandgap material offering a large bandgap (&amp;gt;4.7 eV) and high critical electric fields. The increasing demand for electronic devices for high-power applications in electric automobiles, high-performance computing, green energy technologies, etc., requires higher voltages and currents with enhanced efficiency. Vertical transistors, such as fin-shaped field-effect transistors (FinFETs) have emerged to meet the growing need with improved current handling capabilities, reduced resistance, and enhanced thermal performance. However, to fully exploit the Ga2O3 power transistors, precise and reliable physics-driven models are crucial. Therefore, a comprehensive surface potential model has been developed in this work for a vertical Ga2O3 FinFET. The electric potential across the channel is explained by analyzing the two-dimensional (2D) Poisson equation employing parabolic approximation. Such a surface potential model is instrumental in determining the performance of the Ga2O3 FinFET as it affects the threshold voltage, the drain current, and fringing capacitance. Exploiting the surface potentials, a fringing capacitance model is derived which is crucial in analyzing the speed of the device in compact integrated circuits. In addition, statistical analysis of the Ga2O3 FinFET using the Monte Carlo simulation technique is performed to determine the leakage current fluctuation due to doping variations. The validation of the analytical model with experimental results confirms the effectiveness and prospects of the developed models in the rapid development and characterization of next-generation high-performance vertical Ga2O3 power transistors.