Mathematical Modeling and Control Algorithm Development for Bidirectional Power Flow in CCS-CNT System

As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.

Research on passenger flow control at metro transfer stations based on real-time flow calculation of streamlines

Purpose – The volume of passenger traffic at metro transfer stations serves as a pivotal metric for theorchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations andthe recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processesand the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transferstation streamlines.Design/methodology/approach – The synthesis of stochastic process theory with streamline analysisengenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passengerflow data procured from monitoring systems within the transfer station, a gradient descent optimizationtechnique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorizedpassenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm isimplemented to allocate the intra-station categorized passenger flows across various streamlines, ascertainingthe traffic volume for each.Findings – Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation softwareis engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposedpassenger flow estimation model. The derived solutions are instrumental in formulating a crowd controlstrategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowdmanagement interventions that offer insights for the orchestration of passenger flow and operationalgovernance within metro stations.Originality/value – The construction of an estimation methodology for the real-time streamline traffic flowaugments the model’s dataset, supplanting estimated values derived from surveys or historical datasets withreal-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow managementwithin metro stations.

Autonomous Multi-Factor Energy Flows Controller (AmEFC): Enhancing Renewable Energy Management with Intelligent Control Systems Integration

The transition to sustainable energy systems is one of the defining challenges of our time, necessitating innovations in how we generate, distribute, and manage electrical power. Micro-grids, as localized energy hubs, have emerged as a promising solution to integrate renewable energy sources, ensure energy security, and improve system resilience. The Autonomous multi-factor Energy Flow Controller (AmEFC) introduced in this paper addresses this need by offering a scalable, adaptable, and resilient framework for energy management within an on-grid micro-grid context. The urgency for such a system is predicated on the increasing volatility and unpredictability in energy landscapes, including fluctuating renewable outputs and changing load demands. To tackle these challenges, the AmEFC prototype incorporates a novel hierarchical control structure that leverages Renewable Energy Sources (RES), such as photovoltaic systems, wind turbines, and hydro pumps, alongside a sophisticated Battery Management System (BMS). Its prime objective is to maintain an uninterrupted power supply to critical loads, efficiently balance energy surplus through hydraulic storage, and ensure robust interaction with the main grid. A comprehensive Simulink model is developed to validate the functionality of the AmEFC, simulating real-world conditions and dynamic interactions among the components. The model assesses the system’s reliability in consistently powering critical loads and its efficacy in managing surplus energy. The inclusion of advanced predictive algorithms enables the AmEFC to anticipate energy production and consumption trends, integrating weather forecasting and inter-controller communication to optimize energy flow within and across micro-grids. This study’s significance lies in its potential to facilitate the seamless incorporation of RES into existing power systems, thus propelling the energy sector towards a more sustainable, autonomous, and resilient future. The results underscore the potential of such a system to revolutionize energy management practices and highlight the importance of smart controller systems in the era of smart grids.

Reinforcement learning for wind-farm flow control:Current state and future actions

Wind-farm flow control stands at the forefront of grand challenges in wind-energy science.The central issue is that current algorithms are based on simplified models and,thus,fall short of capturing the complex physics of wind farms associated with the high-dimensional nature of turbulence and multiscale wind-farm-atmosphere interactions.Reinforcement learning(RL),as a subset of machine learning,has demonstrated its effectiveness in solving high-dimensional problems in various domains,and the studies performed in the last decade prove that it can be exploited in the development of the next generation of algorithms for wind-farm flow control.This review has two main objectives.Firstly,it aims to provide an up-to-date overview of works focusing on the development of wind-farm flow control schemes utilizing RL methods.By examining the latest research in this area,the review seeks to offer a comprehensive understanding of the advancements made in wind-farm flow control through the application of RL techniques.Secondly,it aims to shed light on the obstacles that researchers face when implementing wind-farm flow control based on RL.By highlighting these challenges,the review aims to identify areas requiring further exploration and potential opportunities for future research.

Experimental investigation of dynamic stall flow control using a microsecond-pulsed plasma actuator

To alleviate the performance deterioration caused by dynamic stall of a wind turbine airfoil,the flow control by a microsecond-pulsed dielectric barrier discharge(MP-DBD) actuator on the dynamic stall of a periodically pitching NACA0012 airfoil was investigated experimentally.Unsteady pressure measurements with high temporal accuracy were employed in this study,and the unsteady characteristics of the boundary layer were investigated by wavelet packet analysis and the moving root mean square method based on the acquired pressure.The experimental Mach number was 0.2,and the chord-based Reynolds number was 870 000.The dimensionless actuation frequencies F+ were chosen to be 0.5,1,2,and 3,respectively.For the light dynamic regime,the MP-DBD plasma actuator plays the role of suppressing flow separation from the trial edge and accelerating the flow reattachment due to the high-momentum freestream flow being entrained into the boundary layer.Meanwhile,actuation effects were promoted with the increasing dimensionless actuation frequency F+.The control effects of the deep dynamic stall were to delay the onset and reduce the strength of the dynamic stall vortex due to the accumulating vorticity near the leading edge being removed by the induced coherent vortex structures.The laminar fluctuation and Kelvin-Helmholtz(K-H) instabilities of transition and relaminarization were also mitigated by the MP-DBD actuation,and the alleviated K-H rolls led to the delay of the transition onset and earlier laminar reattachment,which improved the hysteresis effect of the dynamic stall.For the controlled cases of F+=2,and F+=3,the laminar fluctuation was replaced by relatively low frequency band disturbances corresponding to the harmonic responses of the MP-DBD actuation frequency.

Flow control performance evaluation of a tri-electrode sliding discharge plasma actuator

Tri-electrode sliding discharge(TED)plasma actuators are formed by adding a direct current(DC)exposed electrode to conventional dielectric barrier discharge(DBD)plasma actuators.There are three TED modes depending on the polarity and amplitude of the DC supply:DBD discharge,extended discharge and sliding discharge.This paper evaluates the electrical,aerodynamic and mechanical characteristics of a TED plasma actuator based on energy analysis,particle image velocimetry experiments and calculations using the Navier-Stokes equation.The flow control performances of different discharge modes are quantitatively analyzed based on characteristic parameters.The results show that flow control performance in both extended discharge and sliding discharge is more significant than that of DBD,mainly because of the significantly higher(up to 141%)body force of TED compared with DBD.However,conductivity loss is the primary power loss caused by the DC polarity for TED discharge.Therefore,power consumption can be reduced by optimizing the dielectric material and thickness,thus improving the flow control performance of plasma actuators.

Model Predictive Control Strategy of Multi-Port Interline DC Power Flow Controller

There are issues with flexible DC transmission system such as a lack of control freedom over power flow.In order to tackle these issues,a DC power flow controller(DCPFC)is incorporated into a multi-terminal,flexible DC power grid.In recent years,a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust scalability.This work proposes a model predictive control(MPC)strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic performance.Initially,the mathematical model of a multi-terminal DC power grid with a multi-port interline DC power flow controller is developed,and the relationship between each regulated variable and control variable is determined;The power flow controller is then discretized,and the cost function and weight factor are built with numerous control objectives.Sub module sorting method and nearest level approximation modulation regulate the power flow controller;Lastly,theMATLAB/Simulink simulation platformis used to verify the correctness of the establishedmathematicalmodel and the control performance of the suggestedMPC strategy.Finally,it is demonstrated that the control strategy possesses the benefits of robust dynamic performance,multiobjective control,and a simple structure.

Numerical Investigation of Flow Separation Control over an NACA0018 Airfoil Using Sweeping Jet Actuator

As an active flow control technology and with the advantages of no moving components, the Sweeping jet actuator has become a hotspot in the field of flow control. However, the linear relationship between oscillation frequency and momentum coefficient in a sweeping jet actuator makes it difficult to determine the dominant factors that affect control effectiveness. Decoupling the oscillation frequency and momentum coefficient, as well as determining the control mechanism, is the focus of studying the sweeping jet actuator. In this study, a novel sweeping jet actuator is designed using synthetic jets instead of feedback channels and applied to the flow separation control of NACA0018 airfoil. This article studies the control effect under three oscillation frequencies of F+ = f × c/U∞ = 1, 10, 100 and three momentum coefficients of Cμ = 0.45%, 0.625%, 0.9%. The numerical results indicate that all three oscillation frequencies have good control effects on flow separation, and the control effect is best when F+ = 1, with the maximum lift coefficient increasing by approximately 14% compared to the other two cases. And the sweeping jet actuator has a better ability to control flow separation as the momentum coefficient increases. By decoupling the characteristics of the sweeping jet actuator and conducting numerical analysis of the flow control effect, it will promote its better engineering application in the field of flow control. .

Dynamic Flow Control Strategies of Vehicle SCR Urea Dosing System

Selective Catalyst Reduction（SCR）Urea Dosing System（UDS）directly affects the system accuracy and the dynamic response performance of a vehicle.However,the UDS dynamic response is hard to keep up with the changes of the engine＇s operating conditions.That will lead to low NO_χconversion efficiency or NH_3 slip.In order to optimize the injection accuracy and the response speed of the UDS in dynamic conditions,an advanced control strategy based on an air-assisted volumetric UDS is presented.It covers the methods of flow compensation and switching working conditions.The strategy is authenticated on an UDS and tested in different dynamic conditions.The result shows that the control strategy discussed results in higher dynamic accuracy and faster dynamic response speed of UDS.The inject deviation range is improved from being between-8%and 10%to-4%and 2%and became more stable than before,and the dynamic response time was shortened from 200 ms to 150 ms.The ETC cycle result shows that after using the new strategy the NH_3 emission is reduced by 60%,and the NO_χemission remains almost unchanged.The trade-off between NO_χconversion efficiency and NH_3 slip is mitigated.The studied flow compensation and switching working conditions can improve the dynamic performance of the UDS significantly and make the UDS dynamic response keep up with the changes of the engine＇s operating conditions quickly.

A grouping strategy for reinforcement learning-based collective yawcontrol of wind farms

Reinforcement learning(RL)algorithms are expected to become the next generation of wind farm control methods.However,as wind farms continue to grow in size,the computational complexity of collective wind farm control will exponentially increase with the growth of action and state spaces,limiting its potential in practical applications.In this Letter,we employ a RL-based wind farm control approach with multi-agent deep deterministic policy gradient to optimize the yaw manoeuvre of grouped wind turbines in wind farms.To reduce the computational complexity,the turbines in the wind farm are grouped according to the strength of the wake interaction.Meanwhile,to improve the control efficiency,each subgroup is treated as a whole and controlled by a single agent.Optimized results show that the proposed method can not only increase the power production of the wind farm but also significantly improve the control efficiency.

Neuro-Fuzzy Based Interline Power Flow Controller for Real Time Power Flow Control in Multiline Power System

This article investigates the power quality enhancement in power system using one of the most famous series converter based FACTS controller like IPFC (Interline Power Flow Controller) in Power Injection Model (PIM). The parameters of PIM are derived with help of the Newton-Raphson power flow algorithm. In general, a sample test power system without FACTs devices has generated more reactive power, decreased real power, more harmonics, small power factor and poor dynamic performance under line and load variations. In order to improve the real power, compensating the reactive power, proficient power factor and excellent load voltage regulation in the sample test power system, an IPFC is designed. The D-Q technique is utilized here to derive the reference current of the converter and its D.C link capacitor voltage is regulated. Also, the reference voltage of the inverter is arrived by park transformation technique and its load voltage is controlled. Here, a sample 230 KV test power system is taken for study. Further as the conventional PI controllers are designed at one nominal operating point they are not competent to respond satisfactorily in dynamic operating conditions. This can be circumvented by a Fuzzy and Neural network based IPFC and its detailed Simulink model is developed using MATLAB and the overall performance analysis is carried out under different operating state of affairs.

Cloud control for IIoT in a cloud-edge environment

The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of 5G.For 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration.For a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule parameters.IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows.IIoT workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge environment.An adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost dramatically.Simulation and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.

Steel Quality Improvement Potentials in the Continuous Casting Process Using State of the Art Refractory Flow Control Systems

In the continuous casting process for high quality steel grades, activities are mainly focused on avoiding reoxidation and promoting non-metallic inclusion removal during steel transfer from the ladle through the tundish to the mould. In this paper, methods to effectively control flow from the tundish to the continuous casting mould are described and specific state of the art refractory solutions are also introduced.

A Fuzzy Flow Control Approach for ABR Service in ATM Networks

The explicit rate flow control mechanisms for ABR service are used to sharethe available bandwidth of a bottleneck link fairly and reasonably among many competitive users andto maintain the buffer queue length of a bottleneck switch connected to the link at a desired levelin order to avoid and control congestion in ATM networks. However, designing effective flow controlmechanisms for the service is known to be difficult because of the variety of dynamic parametersinvolved such as available link bandwidth, burst of the traffic, the distances between ABR sourcesand switches. In this paper, we present a fuzzy explicit rate flow control mechanism for ABRservice. The mechanism has a simple structure and is robust in the sense that the mechanism'sstability is not sensitive to the change in the number of active virtual connections (VCs). Manysimulations show that this mechanism can not only effectively avoid network congestion, but alsoensure fair share of the bandwidth for all active VCs regardless of the number of hops theytraverse. Additionally, it has the advantages of fast convergence, low oscillation, and high linkbandwidth utilization.

Theoretical Analysis and Numerical Simulation of the Static and Dynamic Characteristics of Hydrostatic Guides Based on Progressive Mengen Flow Controller

The oil film thickness of oil hydrostatic guide with constant pressure supply based on capillary restrictor is greatly affected by load, and this kind of hydrostatic guide is usually applied to the machine tools with moderate load. The static and dynamic characteristics of the guide have been studied by using some theoretical, numerical and experimental approaches, and some methods and measures have been proposed to improve its performances. The hydrostatic guide based on progressive mengen（PM） flow controller is especially suitable for the heavy numerical control（NC） machine tools. However, few literatures about the research on the static and dynamic characteristics of the hydrostatic guides based on PM flow controller are reported. In this paper, the formulae are derived for analyzing the static and dynamic characteristics of hydrostatic guides with rectangle pockets and PM flow controller according to the theory of hydrostatic bearing. On the basis of the analysis of hydrostatic bearing with circular pocket, some equations are derived for solving the static pressure, volume pressure and squeezing pressure which influence the dynamic characteristics of hydrostatic guides with rectangle pocket. The function and the influencing factors of three pressures are clarified. The formulae of amplitude-frequency characteristics and dynamic stiffness of the hydrostatic guide system are derived. With the help of software MATLAB, programs are coded with C＋＋ language to simulate numerically the static and dynamic characteristics of the hydrostatic guide based on PM flow controller. The simulation results indicate that the sensitive oil volume between the outlet of the PM flow controller and the guide pocket has the greatest influence on the characteristics of the guide, and it should be reduced as small as possible when the field working condition is met. Choosing the oil with a greater viscosity is also helpful in improving the dynamic performance of hydrostatic guides. The research work has instructing significance for analyzing and designing the guide with PM flow controller.

ASYMMETRIC VORTICES FLOW OVER SLENDER BODY AND ITS ACTIVE CONTROL AT HIGH ANGLE OF ATTACK

The studies of asymmetric vortices flow over slender body and its active control at high angles of attack have significant importance for both academic field and engineering area.This paper attempts to provide an update state of art to the investigations on the fields of forebody asymmetric vortices.This review emphasizes the correlation between micro-perturbation on the model nose and its response and evolution behaviors of the asymmetric vortices.The critical issues are discussed, which include the formation and evolution mechanism of asymmetric multi-vortices;main behaviors of asymmetric vortices flow including its deterministic feature and vortices flow structure;the evolution and development of asymmetric vortices under the perturbation on the model nose;forebody vortex active control especially discussed micro-perturbation active control concept and technique in more detail.However present understanding in this area is still very limited and this paper tries to identify the key unknown problems in the concluding remarks.

Optimization of flow control devices in a single-strand slab continuous casting tundish

The optimization of flow control devices in a single-slab continuous casting tundish was carried out by physical modeling, and the optimized scheme was presented. With the optimal tundish configuration, the minimum residence time of liquid steel was increased by 1.4 times, the peak concentration time was increased by 97%, and the dead volume fraction was decreased by 72%. A mathematical model for molten steel in the tundish was established by using the fluid dynamics package Fluent. The velocity field, concentration field, and the resi-dence time distribution （RTD） curves of molten steel flow before and after optimization were obtained. Experimental results showed that the reasonable configuration with flow control devices can improve the fluid flow characteristics in the tundish. The results of industrial applica-tion show that the nonmetallic inclusion area ratio in casting slabs is decreased by 32% with the optimal tundish configuration.

Metro passenger flow control with station-to-station cooperation based on stop-skipping and boarding limiting

Metro passenger flow control problem is studied under given total inbound demand in this work,which considers passenger demand control and train capacity supply.Relevant connotations are analyzed and a mathematical model is developed.The decision variables are boarding limiting and stop-skipping strategies and the objective is the maximal passenger profit.And a passenger original station choice model based on utility theory is built to modify the inbound passenger distribution among stations.Algorithm of metro passenger flow control scheme is designed,where two key technologies of stopping-station choice and headway adjustment are given and boarding limiting and train stopping-station scheme are optimized.Finally,a real case of Beijing metro is taken for example to verify validity.The results show that in the three scenarios with different ratios of normal trains to stop-skipping trains,the total limited passenger volume is the smallest and the systematic profit is the largest in scenario 3.

Orthogonal analysis of water model study on the optimization of flow control devices in a six-strand tundish

Improper flow control devices in a multi-strand tundish can cause some problems, for example, liquid steel cannot reach every nozzle at the same time and the liquid steel in nozzles far away from the entry zone has a lower temperature. The water model experiment of a six-strand tundish of Tianjin Iron ＆ Steel Co. Ltd. was performed, a new ＂U＂ type baffle was obtained, and its parameters were defined by perpendicular analysis. The ＂U＂ baffle can not only improve those imperfections, but also prolong the residence time of nonmetallic inclusions, which is good for their flotation and separation.

Improvement of tundish shape and optimization of flow control devices for sequence casting heavy steel ingots

The metallurgical effect of a round tundish used to cast heavy steel ingots in machine works at present was evaluated through water modeling experiments. The flow control devices of the improved oval tundish, which was used instead of the round tundish, had been optimized. The results show that the residence time of the round tundish is short, its inclusion removal efficiency is too low, and it has more dead zones and an unreasonable flow field. Compared with the round tundish, the improved oval tundish with the optimized weir and dam has a better effect： its minimum residence time is prolonged by 38.1 s, the average residence time is prolonged by 233.4 s, its dead volume fraction decreases from 26% to 15%, and the ratio of plug volume fraction to dead volume fraction increases from 0.54 to 1.27. The inclusion removal efficiency also increases by 17.5%.