An Adaptive Control Strategy for Energy Storage Interface Converter Based on Analogous Virtual Synchronous Generator

In the DC microgrid,the lack of inertia and damping in power electronic converters results in poor stability of DC bus voltage and low inertia of the DC microgrid during fluctuations in load and photovoltaic power.To address this issue,the application of a virtual synchronous generator(VSG)in grid-connected inverters control is referenced and proposes a control strategy called the analogous virtual synchronous generator(AVSG)control strategy for the interface DC/DC converter of the battery in the microgrid.Besides,a flexible parameter adaptive control method is introduced to further enhance the inertial behavior of the AVSG control.Firstly,a theoretical analysis is conducted on the various components of the DC microgrid,the structure of analogous virtual synchronous generator,and the control structure’s main parameters related to the DC microgrid’s inertial behavior.Secondly,the voltage change rate tracking coefficient is introduced to adjust the change of the virtual capacitance and damping coefficient flexibility,which further strengthens the inertia trend of the DC microgrid.Additionally,a small-signal modeling approach is used to analyze the approximate range of the AVSG’s main parameters ensuring system stability.Finally,conduct a simulation analysis by building the model of the DC microgrid system with photovoltaic(PV)and battery energy storage(BES)in MATLAB/Simulink.Simulation results from different scenarios have verified that the AVSG control introduces fixed inertia and damping into the droop control of the battery,resulting in a certain level of inertia enhancement.Furthermore,the additional adaptive control strategy built upon the AVSG control provides better and flexible inertial support for the DC microgrid,further enhances the stability of the DC bus voltage,and has a more positive impact on the battery performance.

TEG参数HbA1c联合梗死体积对急性缺血性脑卒中患者治疗后颅内出血的预测价值

目的探讨血栓弹力图(TEG)参数、糖化血红蛋白(HbA1c)联合磁共振弥散加权成像(DWI)梗死体积对急性缺血性脑卒中(AIS)患者治疗后颅内出血的预测价值。方法对接受静脉溶栓治疗的184例AIS患者的临床资料进行回顾性分析。比较发生和未发生颅内出血患者临床资料、TEG参数、HbA1c及DWI梗死体积等差异,采用Logistic回归分析探讨AIS患者发生颅内出血影响因素,采用受试者工作特征(ROC)曲线分析TEG参数、HbA1c联合DWI梗死体积预测颅内出血的应用价值。结果184例患者中,发生颅内出血43例,颅内出血发生率为23.37%。发生颅内出血患者入院时美国国立卫生研究院卒中量表(NIHSS)评分、HbA1c、D-二聚体(D-D)和降钙素原(PCT)水平高于未发生颅内出血患者(P<0.01)。发生颅内出血患者R值(凝血反应时间)、K值(血细胞凝集块形成时间)、DWI梗死体积大于未发生颅内出血患者,而Angle值(血细胞凝集块形成速率)、MA值(最大血块强度)、CI值(凝血指数)小于未发生颅内出血患者(P<0.05或0.01)。Logistic回归分析结果显示,R值、DWI梗死体积、HbA1c是AIS患者发生颅内出血的影响因素(P<0.01)。R值、DWI梗死体积、HbA1c三项指标联合预测颅内出血的ROC曲线下面积为0.828,灵敏性和特异性分别为83.70%和65.20%。结论TEG参数、HbA1c联合DWI梗死体积在预测AIS患者治疗后颅内出血方面有较好的应用价值,值得临床使用。

Modeling and small-signal stability analysis of doubly-fed induction generator integrated system

Owing to their stability,doubly-fed induction generator(DFIG)integrated systems have gained considerable interest and are the most widely implemented type of wind turbines and due to the increasing escalation of the wind generation penetration rate in power systems.In this study,we investigate a DFIG integrated system comprising four modules:(1)a wind turbine that considers the maximum power point tracking and pitch-angle control,(2)induction generator,(3)rotor/grid-side converter with the corresponding control strategy,and(4)AC power grid.The detailed small-signal modeling of the entire system is performed by linearizing the dynamic characteristic equation at the steady-state value.Furthermore,a dichotomy method is proposed based on the maximum eigenvalue real part function to obtain the critical value of the parameters.Root-locus analysis is employed to analyze the impact of changes in the phase-locked loop,short-circuit ratio,and blade inertia on the system stability.Lastly,the accuracy of the small-signal model and the real and imaginary parts of the calculated dominant poles in the theoretical analysis are verified using PSCAD/EMTDC.

基于System Generator的卷积加速结构设计与实现

为解决卷积神经网络中卷积运算耗时长、运算复杂的问题,针对卷积运算的并行性特征,提出一种基于分块的流水线加速方法,并基于该方法在System Generator上进行了电路设计。通过在FPGA(Field-programmable Gate Array)上进行实验验证,该设计模型能正确输出卷积运算结果;在结构和输入数据相同的情况下,该设计模型在计算速度上相比于普通CPU最高可加速258倍,相比于服务器级CPU提高了近40倍,具有良好的加速效果。

基于NSGA-II算法的TEG脱水工艺能耗分析及参数优化

为满足天然气脱水工艺中干气露点达标和能耗优化要求,以某气田集气站为例,采用ASPEN Hysys软件搭建天然气脱水工艺流程,根据实际运行参数筛选影响脱水系统能耗的工艺参数,利用BBD实验设计建立多目标回归函数,并采用第二代自适应非支配遗传算法(NSGA-Ⅱ)对函数进行求解,最后与Hysys自带的优化器求解算法进行了对比。结果表明:TEG循环量、重沸器温度和汽提气量对能耗的敏感性较强;通过分析Pareto前沿,当优化前后水露点接近的条件下,等量功比优化前降低了4.18%;当优化前后等量功接近的条件下,干气露点比优化前降低了1.92℃;当采用Hysys软件自带的优化器求解时,TEG循环量和汽提气量均有所减小,但重沸器温度未得到优化。NSGA-Ⅱ算法在能耗降低及参数优化上具有优越性,可以得到全局最优解。

Research on Virtual DC Generator-Based Control Strategy of DCMicrogrid with Photovoltaic and Energy Storage

With the penetration of a large number of photovoltaic power generation units and power electronic converters,the DC microgrid shows low inertia characteristics,which might affect the stable operation of the microgrid in extreme cases.In order to enhance the“flexible features”of the interface converter connected to the DC bus,a control strategy of DCmicrogrid with photovoltaic and energy storage based on the virtual DC generator(VDCG)is proposed in this paper.The interface converters of the photovoltaic power generation system and the energy storage system simulates the inertia and damping characteristics of the DC generator to improve the stability of the DC bus voltage.The impedance ratio of DC microgrid was obtained by establishing the small-signal model of photovoltaic power generation system and energy storage system,and the Nyquist curves was applied to analyze the small-signal stability of the system.Finally,the simulation results were verified with MATLAB/Simulink.The results show that the proposed control strategy can slow down the fluctuation of bus voltage under the conditions of photovoltaic power fluctuation and load mutation,thus enhancing the system stability.

Numerical Study on the Effect of Vortex Generators on the Aerodynamic Drag of a High-Speed Train

A relatively high aerodynamic drag is an important factor that hinders the further acceleration of high-speed trains.Using the shear stress transport(SST)k-ωturbulence model,the effect of various vortex generator types on the aerodynamic characteristics of an ICE2(Inter-city Electricity)train has been investigated.The results indi-cate that the vortex generators with wider triangle,trapezoid,and micro-ramp arranged on the surface of the tail car can significantly change the distribution of surface pressure and affect the vorticity intensity in the wake.This alteration effectively reduces the resistance of the tail car.Meanwhile,the micro-ramp vortex generator with its convergent structure at the rear exhibits enhancedflow-guiding capabilities,resulting in a 15.4%reduction in the drag of the tail car.

Demonstration of a small‐scale power generator using supercritical CO_(2)

The supercritical CO_(2)(sCO_(2))power cycle could improve efficiencies for a wide range of thermal power plants.The sCO_(2)turbine generator plays an important role in the sCO_(2)power cycle by directly converting thermal energy into mechanical work and electric power.The operation of the generator encounters challenges,including high temperature,high pressure,high rotational speed,and other engineering problems,such as leakage.Experimental studies of sCO_(2)turbines are insufficient because of the significant difficulties in turbine manufacturing and system construction.Unlike most experimental investigations that primarily focus on 100 kW‐or MW‐scale power generation systems,we consider,for the first time,a small‐scale power generator using sCO_(2).A partial admission axial turbine was designed and manufactured with a rated rotational speed of 40,000 rpm,and a CO_(2)transcritical power cycle test loop was constructed to validate the performance of our manufactured generator.A resistant gas was proposed in the constructed turbine expander to solve the leakage issue.Both dynamic and steady performances were investigated.The results indicated that a peak electric power of 11.55 kW was achieved at 29,369 rpm.The maximum total efficiency of the turbo‐generator was 58.98%,which was affected by both the turbine rotational speed and pressure ratio,according to the proposed performance map.

Analysis of pseudo-random number generators in QMC-SSE method

In the quantum Monte Carlo(QMC)method,the pseudo-random number generator(PRNG)plays a crucial role in determining the computation time.However,the hidden structure of the PRNG may lead to serious issues such as the breakdown of the Markov process.Here,we systematically analyze the performance of different PRNGs on the widely used QMC method known as the stochastic series expansion(SSE)algorithm.To quantitatively compare them,we introduce a quantity called QMC efficiency that can effectively reflect the efficiency of the algorithms.After testing several representative observables of the Heisenberg model in one and two dimensions,we recommend the linear congruential generator as the best choice of PRNG.Our work not only helps improve the performance of the SSE method but also sheds light on the other Markov-chain-based numerical algorithms.

A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reconfiguration and Demand Response

To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.

Moisture‑Electric–Moisture‑Sensitive Heterostructure Triggered Proton Hopping for Quality‑Enhancing Moist‑Electric Generator

Moisture-enabled electricity(ME)is a method of converting the potential energy of water in the external environment into electrical energy through the interaction of functional materials with water molecules and can be directly applied to energy harvesting and signal expression.However,ME can be unreliable in numerous applications due to its sluggish response to moisture,thus sacrificing the value of fast energy harvesting and highly accurate information representation.Here,by constructing a moisture-electric-moisture-sensitive(ME-MS)heterostructure,we develop an efficient ME generator with ultra-fast electric response to moisture achieved by triggering Grotthuss protons hopping in the sensitized ZnO,which modulates the heterostructure built-in interfacial potential,enables quick response(0.435 s),an unprecedented ultra-fast response rate of 972.4 mV s^(−1),and a durable electrical signal output for 8 h without any attenuation.Our research provides an efficient way to generate electricity and important insight for a deeper understanding of the mechanisms of moisture-generated carrier migration in ME generator,which has a more comprehensive working scene and can serve as a typical model for human health monitoring and smart medical electronics design.

The tangential k-Cauchy-Fueter type operator and Penrose type integral formula on the generalized complex Heisenberg group

The tangential k-Cauchy-Fueter operator and k-CF functions are counterparts of the tangential Cauchy–Riemann operator and CR functions on the Heisenberg group in the theory of several complex variables,respectively.In this paper,we introduce a Lie group that the Heisenberg group can be imbedded into and call it generalized complex Heisenberg.We investigate quaternionic analysis on the generalized complex Heisenberg.We also give the Penrose integral formula for k-CF functions and construct the tangential k-Cauchy-Fueter complex.

Artificial Intelligence in the Oil and Gas Industry:Opportunities,Challenges,and Strategies

Introduction The current new wave of the digital revolution is sweeping the world with unprecedented breadth and depth.With the acceleration of digital transformation,artificial intelligence(AI),which is known as the engine of the“Fourth Industrial Revolution”,is playing a significant role in driving the digital transformation and intelligent development of related industries,and generating substantial social and economic benefits.In the oil and gas industry,it has become an inevitable trend to utilize AI technology to achieve automatic data collection,real-time monitoring,intelligent production optimization,and smart decision-making.

Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

Optimization of the Gas Generator in Composite Power System with Tip-Jet Rotor

The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of the tip-jet rotor composite power system, studying the effects of intake mode, inner cavity structure, propellant components, and injection amount on the characteristics of the composite power system. The results show that when a single high-temperature exhaust gas enters, the gas generator outlet fluid is uneven and asymmetric;when two-way high-temperature exhaust gas enters, the outlet temperature of the gas generator with a tilted inlet is more uniform than that with a vertical inlet;adding an inner cavity improves the temperature and velocity distribution of the gas generator's internal flow field;increasing the energy of the propellant is beneficial for improving the available moment.

What value does video generator Sora bring to the textile industry?

On 15 February,OpenAI released its first video generation model"Sora".This is another disruptive work of the company after ChatGPT.It is reported that this AI video model can generate HD videos up to 1 minute long based on the text given by the user.For the time being,its impact on the textile industry may be indirect,but it may also have some interesting and practical effects as it is developed and refined in the future.Here are some of the effects that Sora may have on the textile industry.

Exploring Pedagogical Ideologies and Strategies for College English Writing Instruction from a Generative Artificial Intelligence Perspective

This study,drawing on the commonalities between generative artificial intelligence and foreign language writing instruction,outlines the core ideology of digital humanities-based college English writing instruction,including auxiliary use of generative artificial intelligence tools,primary focus on humanistic education,and the re-production of knowledge,aiming to foster students’critical thinking,collaborative skills,and creativity.Building on this foundation,the study delves into generative artificial intelligence tools applicable to different stages of process-genre writing and their strategic applications.The use of generative artificial intelligence tools is beneficial for students to present,discuss,and share writing content,encouraging them to enhance their writing,collaboration,critical thinking,and creative abilities through deep interaction with model essays and creative discourses.

A generative adversarial network-based unified model integrating bias correction and downscaling for global SST

本文提出了一种基于生成对抗网络的全球海表面温度(sea surface temperature,SST)偏差订正及降尺度整合模型.该模型的生成器使用偏差订正模块将数值模式预测结果进行校正,再用可复用的共享降尺度模块将订正后的数据分辨率逐次提高.该模型的判别器可鉴别偏差订正及降尺度结果的质量,以此为标准进行对抗训练。同时,在对抗损失函数中含有物理引导的动力学惩罚项以提高模型的性能.本研究基于分辨率为1°的GFDL SPEAR模式的SST预测结果,选择遥感系统(Remote Sensing System)的观测资料作为真值,面向月尺度ENSO与IOD事件以及天尺度海洋热浪事件开展了验证试验:模型在将分辨率提高到0.0625°×0.0625°的同时将预测误差减少约90.3%,突破了观测数据分辨率的限制,且与观测结果的结构相似性高达96.46%.

Investigation of Oil Vapours in Hydro-Generator

The article discusses engineering approaches to solving the problem of oil vapours in generators. Due to the design characteristics of each power plant, it is difficult to find a typical solution. Nevertheless, the article suggests ways to reduce the amount of oil mist. For their implementation, a calculation methodology based on the substitution scheme of the hydraulic path of the bearing support unit is created which takes into account the design features of the bearing and the parameters of the environment around the oil bath. The methodology employed is presented. The numerical method of modelling the aerodynamic fields of the entire hydro generator is used to estimate the air flows and pressures in the oil bath zone of the thrust bearing. Additionally, the method made it possible to track suspected oil particles that could get from the thrust-bearing bath into the surrounding area of the generator. Measures are proposed to reduce the level of oil mist through the competent design of the oil vapour removal system from the bearing bath.

sdLDL、LDL及TEG在高脂血症患者颈动脉粥样硬化诊断中的应用

目的:研究小而密低密度脂蛋白(sdLDL)、低密度脂蛋白(LDL)、血栓弹力图(TEG)在高脂血症患者颈动脉粥样硬化(CAS)诊断中的应用价值。方法:回顾性选取2021年11月-2022年10月于丰城市中医院就诊的200例高脂血症患者作为研究对象,根据其是否伴发CAS进行分组,单纯高脂血症患者分为A组(n=94),伴发CAS的高脂血症患者分为B组(n=106),另外选取同时期于本院体检健康者(n=50)作为C组,收集三组相关临床资料。比较三组sdLDL、LDL及TEG,分析sdLDL、LDL及TEG参数诊断高脂血症CAS的价值。结果:B组sdLDL、LDL水平均显著高于A组、C组(P<0.05);A组、B组反应时间(R)、血凝块形成时间(K)均明显短于C组,B组R明显短于A组(P<0.05);A组、B组最大振幅(MA)、弹力图最大切角(Angle)均显著高于C组,B组MA明显高于A组(P<0.05)。ROC曲线分析结果显示,sdLDL、LDL、R、MA诊断CAS的曲线下面积(AUC)分别为0.728、0.667、0.764、0.693,而四者联合检测CAS的AUC为0.832,显著高于单独指标检测(Z=3.727、4.850、3.037、4.386,P=0.000、0.000、0.002、0.000),敏感度为84.91%,特异度为68.75%。结论:sdLDL、LDL及TEG与高脂血症患者CAS密切相关,均有一定的诊断价值,且联合检测可显著提高诊断效能。