Design of a Three-Phase Grid Connector System Using Power Transfer from Park’s Transformation

Instabilities in grid-connected inverters can arise from a number of sources, including mismatched parameters, grid impedance, faults, and feedback delays. Park’s transformation provides accurate control over reactive and active (real) power. This enhances the overall efficiency of the system by enabling operators to control reactive power compensation and optimize energy flow. In dynamic settings, this guarantees greater system stability and faster response times. The current paper aims to improve the grid system by utilizing the dq0 controller. The current work focuses on the analysis based on simulations and theory, where the state space equation serves as the basis for dq-axis current decoupling. A MATLAB platform was used to simulate the complete system. TDH values of 2.45%, or less than 5%, in the given results are acceptable. The suggested controller was hence appropriate for grid system applications.

A New Predictive Direct Power Control Solution for Three-phase Grid-Connected Inverters

This paper proposes a new Predictive Direct Power Control(P-DPC) solution for three-phase grid-connected inverters, which combines direct power control strategy with the predictive control strategy and space vector pulse width modulation(SVPWM), obtaining both high transient performance and a constant switching frequency. This control solution can achieve decoupling control for active and reactive power and an adjustable power factor. Meanwhile, the grid-connected current can approximately be sinusoidal. The feasibility and advantages of the control strategy are verified by the simulation and experiment compared with another existing P-DPC.

Grid Harmonic and Control Delay Compensation for Three-phase Grid-connected VSIs in Small Wind Turbine Systems

Voltage space vector pulse-width modulation(SVPWM) has been widely applied to control current in three-phase voltage source inverters(VSI).However,as a voltage type modulator,SVPWM has certain drawbacks compared with current type modulators for grid-connected applications.For a grid-connected VSI,the performance of existing current controllers based on SVPWM is compromised by grid harmonics,control delay and system nonlinearities such as switching dead time.Moreover,unlike current type PWM,SVPWM does not inherently have over-current protection.A novel SVPWM-based current controller is proposed for three-phase grid-connected VSIs for small wind turbine appli-cations.To overcome the drawbacks of SVPWM,a grid harmonic compensation method is proposed along with compen-sation for control delays.Both simulation and experimental results have established excellent steady-state response and fast dynamic response of the current controller.In addition,the DSP-based control system has both improved real-time control performance and fast response for over-current protection.

Current optimization-based control of dual three-phase PMSM for low-frequency temperature swing reduction

In this paper,a control scheme based on current optimization is proposed for dual three-phase permanent-magnet synchronous motor(DTP-PMSM)drive to reduce the low-frequency temperature swing.The reduction of temperature swing can be equivalent to reducing maximum instantaneous phase copper loss in this paper.First,a two-level optimization aiming at minimizing maximum instantaneous phase copper loss at each electrical angle is proposed.Then,the optimization is transformed to a singlelevel optimization by introducing the auxiliary variable for easy solving.Considering that singleobjective optimization trades a great total copper loss for a small reduction of maximum phase copper loss,the optimization considering both instantaneous total copper loss and maximum phase copper loss is proposed,which has the same performance of temperature swing reduction but with lower total loss.In this way,the proposed control scheme can reduce maximum junction temperature by 11%.Both simulation and experimental results are presented to prove the effectiveness and superiority of the proposed control scheme for low-frequency temperature swing reduction.

Deciphering engineering principle of three-phase interface for advanced gas-involved electrochemical reactions

As an alternative to conventional energy conversion and storage reactions,gas-involved electrochemical reactions,including the carbon dioxide reduction reaction(CO_(2)RR),nitrogen reduction reaction(NRR)and hydrogen evolution reaction(HER),have become an emerging research direction and have gained increasing attention due to their advantages of environmental friendliness and sustainability.Various studies have been designed to accelerate sluggish kinetics but with limited results.Most of them promote the reaction by modulating the intrinsic properties of the catalyst,ignoring the synergistic effect of the reaction as a whole.Due to the introduction of gas,traditional liquid-solid two-phase reactions are no longer applicable to future research.Since gas-involved electrochemical reactions mostly occur at the junctions of gaseous reactants,liquid electrolytes and solid catalysts,the focus of future research on reaction kinetics should gradually shift to three-phase reaction interfaces.In this review,we briefly introduce the formation and constraints of the three-phase interface and propose three criteria to judge its merit,namely,the active site,mass diffusion and electron mass transfer.Subsequently,a series of modulation methods and relevant works are discussed in detail from the three improvement directions of‘exposing more active sites,promoting mass diffusion and accelerating electron transfer’.Definitively,we provide farsighted insights into the understanding and research of three-phase interfaces in the future and point out the possible development direction of future regulatory methods,hoping that this review can broaden the future applications of the three-phase interface,including but not limited to gas-involved electrochemical reactions.

Electrical characteristics of new three-phase traction power supply system for rail transit

A novel three-phase traction power supply system is proposed to eliminate the adverse effects caused by electric phase separation in catenary and accomplish a unifying manner of traction power supply for rail transit.With the application of two-stage three-phase continuous power supply structure,the electrical characteristics exhibit new features differing from the existing traction system.In this work,the principle for voltage levels determining two-stage network is dissected in accordance with the requirements of traction network and electric locomotive.The equivalent model of three-phase traction system is built for deducing the formula of current distribution and voltage losses.Based on the chain network model of the traction network,a simulation model is established to analyze the electrical characteristics such as traction current distribution,voltage losses,system equivalent impedance,voltage distribution,voltage unbalance and regenerative energy utilization.In a few words,quite a lot traction current of about 99%is undertaken by long-section cable network.The proportion of system voltage losses is small attributed to the two-stage three-phase power supply structure,and the voltage unbal-ance caused by impedance asymmetry of traction network is less than 1‰.In addition,the utilization rate of regenerative energy for locomotive achieves a significant promotion of over 97%.

Highly efficient three-phase grid-connected parallel inverter system

In this paper, a new three-phase grid-connected inverter system is proposed. The proposed system includes two inverters. The main inverter, which operates at a low switching frequency, transfers active power to the grid. The auxiliary inverter processes a very low power to compensate for the grid current ripple. Thus, no active power is processed by the auxiliary inverter. The goal is to produce a grid current with a low total harmonic distortion(THD) and to obtain the highest efficiency from the inverter system. The main inverter is controlled via a space-vector pulse-width modulation owing to its optimum switching pattern, and the auxiliary inverter is controlled via a hysteresis current-control technique owing to the technique's fast dynamic response. The proposed system is analyzed in terms of different DC-link voltage, switching frequency,and filter inductance values. The optimum system parameters are selected that provide a THD value of less than 5%.A prototype inverter system at a 10 kW output power has been implemented. The main inverter operates at a 3 kHz switching frequency, and the auxiliary inverter compensates for the grid-current ripple. In total, a THD of 4.33%and an efficiency of 97.86% are obtained using the proposed inverter system prototype.

Speed Regulation Method Using Genetic Algorithm for Dual Three-phase Permanent Magnet Synchronous Motors

Dual three-phase Permanent Magnet Synchronous Motor(DTP-PMSM)is a nonlinear,strongly coupled,high-order multivariable system.In today’s application scenarios,it is difficult for traditional PI controllers to meet the requirements of fast response,high accuracy and good robustness.In order to improve the performance of DTP-PMSM speed regulation system,a control strategy of PI controller based on genetic algorithm is proposed.Firstly,the basic mathematical model of DTP-PMSM is established,and the PI parameters of DTP-PMSM speed regulation system are optimized by genetic algorithm,and the modeling and simulation experiments of DTP-PMSM control system are carried out by MATLAB/SIMULINK.The simulation results show that,compared with the traditional PI control,the proposed algorithm significantly improves the performance of the control system,and the speed output overshoot of the GA-PI speed control system is smaller.The anti-interference ability is stronger,and the torque and double three-phase current output fluctuations are smaller.

Optimization of Control Loops and Operating Parameters for Three-Phase Separators Used in Oilfield Central Processing Facilities

In this study,the Stokes formula is used to analyze the separation effect of three-phase separators used in a Oilfield Central Processing Facility.The considered main influencing factors include(but are not limited to)the typical size of oil and water droplets,the residence time and temperature of fluid and the dosage of demulsifier.Using the“Specification for Oil and Gas Separators”as a basis,the control loops and operating parameters of each separator are optimized Considering the Halfaya Oilfield as a testbed,it is shown that the proposed approach can lead to good results in the production stage.

Purification of Moringa oleifera Leaves Protease by Three-Phase Partitioning and Investigation of Its Potential Antibacterial Activity

One of plant-based products for dental care is plant-based proteolytic enzymes which are principally proteases. In order not to damage the protein and bioactive content, an efficient method should be employed for their purifications. As such, three-phase partitioning (TPP) was used to purify protease from moringa (Moringa oleifera). TPP is an emerging, promising, non-chromatographic and economical technology which is simple, quick, efficient and often one-step process for the separation and purification of bioactive molecules from natural sources. It involves the addition of salt (ammonium sulphate) to the crude extract followed by the addition of an organic solvent (butanol). The protein appears as an interfacial precipitate between upper organic solvent and lower aqueous phases. The various conditions such as ammonium sulphate, ratio of crude extract to t-butanol and pH which are required for attaining efficient purification of the protease fractions were optimized. Under optimized conditions, it was seen that, 35% of ammonium sulphate saturation with 1:0.75 ratio of crude extract to t-butanol at pH 7 gave 4.94-fold purification with 96.20% activity yield of protease in the middle phase of the TPP system. The purified enzyme from Moringa oleifera has no antimicrobial effect on the pathogenic bacteria tested. However, this purified enzyme, can be considered as a promising agent, cheap, and safe source which is suitable for using in various industries.

Vibration characteristics of sandwich plates with an auxetic honeycomb core and laminated three-phase skin layers under blast load

In this article,vibration characteristics of sandwich plates with an auxetic honeycomb core and laminated three-phase skin layers subjected to blast load are studied.Higher-order ES-MITC3 element based on higher-order shear deformation theory(HSDT)to achieve the governing equations.The sandwich plates with the ultra-light feature of the auxetic honeycomb core layer(negative Poisson’s ratio)and reinforced by two laminated three-phase skin layers.The obtained results in our work are compared with other previously published to confirm accuracy and reliability.In addition,the effects of parameters such as geometrical and material parameters on the vibration characteristics of sandwich plates with an auxetic honeycomb core and laminated three-phase skin layers are fully investigated.

Enhancing ammonia production rates from electrochemical nitrogen reduction by engineering three-phase boundary with phosphorus-activated Cu catalysts

Electrochemical N_(2) reduction reaction(eNRR) over Cu-based catalysts suffers from an intrinsically low activity of Cu for activation of stable N_(2) molecules and the limited supply of N_(2) to the catalyst due to its low solubility in aqueous electrolytes.Herein,we propose phosphorus-activated Cu electrocatalysts to generate electron-deficient Cu sites on the catalyst surface to promote the adsorption of N_(2) molecules.The eNRR system is further modified using a gas diffusion electrode(GDE) coated with polytetrafluoroethylene(PTFE) to form an effective three-phase boundary of liquid water-gas N_(2)-solid catalyst to facilitate easy access of N_(2) to the catalytic sites.As a result,the new catalyst in the flow-type cell records a Faradaic efficiency of 13.15% and an NH_(3) production rate of 7.69 μg h^(-1) cm^(-2) at-0.2 V_(RHE),which represent 3.56 and 59.2 times increases from those obtained with a pristine Cu electrode in a typical electrolytic cell.This work represents a successful demonstration of dual modification strategies;catalyst modification and N_(2) supplying system engineering,and the results would provide a useful platform for further developments of electrocatalysts and reaction systems.

Automatic measurement of three-phase contact angles in pore throats based on digital images

With the help of digital image processing technology, an automatic measurement method for the three-phase contact angles in the pore throats of the microfluidic model was established using the microfluidic water flooding experiment videos as the data source. The results of the new method were verified through comparing with the manual measurement data.On this basis, the dynamic changes of the three-phase contact angles under flow conditions were clarified by the contact angles probability density curve and mean value change curve. The results show that, for water-wetting rocks, the mean value of the contact angles is acute angle during the early stage of the water flooding process, and it increases with the displacement time and becomes obtuse angle in the middle-late stage of displacement as the dominant force of oil phase gradually changes from viscous force to capillary force. The droplet flow in the remaining oil occurs in the central part of the pore throats, without three-phase contact angle. The contact angles for the porous flow and the columnar flow change slightly during the displacement and present as obtuse angles in view of mean values, which makes the remaining oil poorly movable and thus hard to be recovered. The mean value of the contact angle for the cluster flow tends to increase in the flooding process, which makes the remaining oil more difficult to be recovered. The contact angles for the membrane flow are mainly obtuse angles and reach the highest mean value in the late stage of displacement, which makes the remaining oil most difficult to be recovered. After displacement, the remaining oils under different flow regimes are just subjected to capillary force, with obtuse contact angles, and the wettability of the pore throat walls in the microfluidic model tends to be oil-wet under the action of crude oil.

Application of CD34 expression combined with three-phase dynamic contrast-enhanced computed tomography scanning in preoperative staging of gastric cancer

BACKGROUND Accurate preoperative staging of gastric cancer(GC),a common malignant tumor worldwide,is critical for appropriate treatment plans and prognosis.Dynamic three-phase enhanced computed tomography(CT)scanning for preoperative staging of GC has limitations in evaluating tumor angiogenesis.CD34,a marker on vascular endothelial cell surfaces,is promising in evaluating tumor angiogenesis.We explored the value of their combination for preoperative staging of GC to improve the efficacy and prognosis of patients with GC.Medical records of 106 patients with GC treated at the First People's Hospital of Lianyungang between February 2021 and January 2023 were retrospectively studied.All patients underwent three-phase dynamic contrast-enhanced CT scanning before surgery,and CD34 was detected in gastroscopic biopsy specimens.Using surgical and pathological results as the gold standard,the diagnostic results of three-phase dynamic contrast-enhanced CT scanning at different T and N stages were analyzed,and the expression of CD34-marked microvessel density(MVD)at different T and N stages was determined.The specificity and sensitivity of three-phase dynamic contrast-enhanced CT and CD34 in T and N staging were calculated;those of the combined diagnosis of the two were evaluated in parallel.Independent factors affecting lymph node metastasis were analyzed using multiple logistic regression.RESULTS The accuracy of three-phase dynamic contrast-enhanced CT scanning in diagnosing stages T1,T2,T3 and T4 were 68.00%,75.00%,79.41%,and 73.68%,respectively,and for diagnosing stages N0,N1,N2,and N3 were 75.68%,74.07%,85.00%,and 77.27%,respectively.CD34-marked MVD expression increased with increasing T and N stages.Specificity and sensitivity of three-phase dynamic contrast-enhanced CT in T staging were 86.79%and 88.68%;for N staging,89.06%and 92.86%;for CD34 in T staging,64.15%and 88.68%;and for CD34 in N staging,84.38%and 78.57%,respectively.Specificity and sensitivity of joint diagnosis in T staging were 55.68%and 98.72%,and N staging were 75.15%and 98.47%,respectively,with the area under the curve for diagnosis improving accordingly.According to multivariate analysis,a longer tumor diameter,higher pathological T stage,lower differ-entiation degree,and higher expression of CD34-marked MVD were independent risk factors for lymph node metastasis in patients with GC.CONCLUSION With high accuracy in preoperatively determining the invasion depth and lymph node metastasis of GC,CD34 expression and three-phase dynamic contrast-enhanced CT can provide a reliable basis for surgical resection.

Grid System Analysis of Urban Flora of Bukhara City (Uzbekistan)

This article presents information on the study of the flora of Uzbekistan based on grid system mapping. The urban flora of the city of Bukhara was researched in it. As a result of research, the territory of Bukhara city was divided into 85 indexes based on 1 × 1 km2 grid mapping system. The diversity and density of species in the indexes are determined. The influence of anthropogenic factors on the diversity of species in the indexes is determined.

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity users.It hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by consumers.The development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning techniques.Moreover,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive hardware.Computer-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor performance.In this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious activity.The key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft detection.Different advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for classification.The effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification results.The performance evaluation of the proposed model revealed exemplary results across variousmetrics.The accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

A Long-Time-Step-Permitting Tracer Transport Model on the Regular Latitude–Longitude Grid

If an explicit time scheme is used in a numerical model, the size of the integration time step is typically limited by the spatial resolution. This study develops a regular latitude–longitude grid-based global three-dimensional tracer transport model that is computationally stable at large time-step sizes. The tracer model employs a finite-volume flux-form semiLagrangian transport scheme in the horizontal and an adaptively implicit algorithm in the vertical. The horizontal and vertical solvers are coupled via a straightforward operator-splitting technique. Both the finite-volume scheme's onedimensional slope-limiter and the adaptively implicit vertical solver's first-order upwind scheme enforce monotonicity. The tracer model permits a large time-step size and is inherently conservative and monotonic. Idealized advection test cases demonstrate that the three-dimensional transport model performs very well in terms of accuracy, stability, and efficiency. It is possible to use this robust transport model in a global atmospheric dynamical core.

Physics-Constrained Robustness Enhancement for Tree Ensembles Applied in Smart Grid

With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and intelligence.However,tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks,making it urgent to enhance their robustness.To address this,we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree ensembles.Our algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws,ensuring training data accurately reflects possible attack scenarios while adhering to physical rules.In our experiments,the proposed method increased robustness against adversarial attacks by 100%when applied to real grid data under physical constraints.These results highlight the advantages of our method in maintaining efficient and secure operation of smart grids under adversarial conditions.

Assessment of Crop Yield in China Simulated by Thirteen Global Gridded Crop Models

Global gridded crop models(GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national-and provincial-scale evaluation of the simulations by13 GGCMs [12 from the GGCM Intercomparison(GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops(wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national-and provincial-scale crop yield prediction in China.

Novel cyber-physical collaborative detection and localization method against dynamic load altering attacks in smart energy grids

Owing to the integration of energy digitization and artificial intelligence technology,smart energy grids can realize the stable,efficient and clean operation of power systems.However,the emergence of cyber-physical attacks,such as dynamic load-altering attacks(DLAAs)has introduced great challenges to the security of smart energy grids.Thus,this study developed a novel cyber-physical collaborative security framework for DLAAs in smart energy grids.The proposed framework integrates attack prediction in the cyber layer with the detection and localization of attacks in the physical layer.First,a data-driven method was proposed to predict the DLAA sequence in the cyber layer.By designing a double radial basis function network,the influence of disturbances on attack prediction can be eliminated.Based on the prediction results,an unknown input observer-based detection and localization method was further developed for the physical layer.In addition,an adaptive threshold was designed to replace the traditional precomputed threshold and improve the detection performance of the DLAAs.Consequently,through the collaborative work of the cyber-physics layer,injected DLAAs were effectively detected and located.Compared with existing methodologies,the simulation results on IEEE 14-bus and 118-bus power systems verified the superiority of the proposed cyber-physical collaborative detection and localization against DLAAs.