A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs

Battery energy storage systems(BESSs)are widely used in smart grids.However,power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe,which has resulted in an increase in operating costs.The general economic dispatch(ED)algorithm based on marginal cost(MC)consensus is usually a proportional(P)controller,which encounters the defects of slow convergence speed and low control accuracy.In order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance,we attempt to design a proportional integral(PI)controller with a reset mechanism(PI+R)to asymptotically promote MC consensus and total power mismatch towards 0 in this paper.To be frank,the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing,which accelerates convergence,improves control accuracy,and avoids overshoot.The eigenvalues of the system under a PI+R controller is well analyzed,ensuring the regularity of the system and enabling the reset mechanism.To ensure supply and demand balance within the isolated BESSs,a centralized reset mechanism is introduced,so that the controller is distributed in a flow set and centralized in a jump set.To cope with Zeno behavior and input delay,a dwell time that the system resides in a flow set is given.Based on this,the system with input delays can be reduced to a time-delay free system.Considering the capacity limitation of the battery,a modified MC scheme with PI+R controller is designed.The correctness of the designed scheme is verified through relevant simulations.

Observer-based dynamic event-triggered control for distributed parameter systems over mobile sensor-plus-actuator networks

We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.

Stability Analysis and Control of DC Distribution System with Electric Vehicles

The DC distribution network system equipped with a large number of power electronic equipment exhibits weak damping characteristics and is prone to low-frequency and high-frequency unstable oscillations.The current interpretation of the oscillation mechanism has not been unified.Firstly,this paper established the complete statespace model of the distribution system consisting of a large number of electric vehicles,characteristic equation of the distribution network system is derived by establishing a state-space model,and simplified reduced-order equations describing the low-frequency oscillation and the high-frequency oscillation are obtained.Secondly,based on eigenvalue analysis,the oscillation modes and the influence of the key system parameters on the oscillation mode are studied.Besides,impacts of key factors,such as distribution network connection topology and number of dynamic loads,have been discussed to suppress oscillatory instability caused by inappropriate design or dynamic interactions.Finally,using the DC distribution example system,through model calculation and time-domain simulation analysis,the correctness of the aforementioned analysis is verified.

基于DCS-惯性权重组合的柔性机械臂运动轨迹控制系统研究

为了有效调控机械臂运动幅度,避免柔性机械臂实际运动轨迹与目标轨迹发生较大的偏差,设计一种基于分散控制系统(DCS)-惯性权重组合的柔性机械臂运动轨迹控制系统,它是一个集合了计算机、通信、显示和控制的计算机系统,该系统由过程控制和过程监控。通过DCS算法控制监测对象行为幅度并计算柔性机械臂惯性权重,利用DCS-惯性权重组合求解素数控制指标的具体数值,实现了对柔性机械臂运动轨迹控制系统的软件设计。实验结果表明,DCS-惯性权重组合算法作用下的机械臂末端坐标在横轴、纵轴、空间轴方向上的运动幅值均可以被控制在10个单位长度之内,并且在0.52 s内进入机械臂运动轨迹最佳控制状态,运动轨迹差值最大仅为0.01 rad,验证了该系统具备可行性和有效性。

基于CNN的OCR技术在核电厂DCS系统测试中的应用和实现

核电厂分布式控制系统(DCS)的输入/输出模块在运行期间,随着电子器件性能下降以及时漂的影响,需要定期进行进度复测和校准。针对传统的DCS输入/输出通道测试覆盖率不足,测试效率低及人因问题,本文提出一种基于卷积神经网络(CNN)的光学字符识别(OCR)技术应用在DCS系统的在线测试方法。通过模拟设备和视频采集设备完成画面的自动切换,并读取画面信息,截取特定画面后对其图像预处理,再使用OCR识别模型识别画面内容,将得到的识别结果与期望值进行比较判断,从而实现自动化测试。测试结果表明,通过CNN训练后,显控设备画面字符识别率能达到100%,该方法可以突破设备厂家的专有通信协议的壁垒,可有效降低操作员的人因失误,提升测试效率和核电厂的经济性。

DCS控制器中电表接触传感器计量误差检测方法

由于DCS控制器中电表传感器在计量检测过程中,传统的B-MAC-DCS协议能耗和丢包率较高,无法缓解汇聚节点的漏斗效应,导致在远程抄表过程中传感器计量误差增大。提出一种机械电表接触传感器计量误差检测方法。采用小波基函数对DCS控制器中的接触传感器计量数据抗干扰处理,并通过动态选取阈值的方法,对经过小波变换后的数据去除噪声。使用低功耗自适应集簇分层型(low energy adaptive clustering hierarchy,LEACH)协议分簇代替传统的B-MAC协议;根据簇内监测值,引入阈值分析方法获取传感器计量指标,并将其作为判定依据进行误差检测,根据计量指标的变化情况判断是否存在计量误差。实验结果表明,所提方法可以准确且有效检测出机械电表接触传感器计量误差,解决DCS中机械电表的运行隐患问题。

基于SCADA-DCS通讯技术的油气开采数据自动化采集与控制系统

设计基于SCADA-DCS通讯技术的油气开采数据自动化采集与控制系统。系统以SCADA服务器为上层监控服务器,通过与井站现场仪器仪表实时通信,监控整个开采过程。当油气缓冲罐液位越限时,SCADA服务器自动下达指令至原油处理站DCS,启动基于智能PID的油泵控制器,调节油泵变频器,控制油气液位不溢出。系统使用SCADA-DCS通讯技术的MODBUS通信协议,并根据通信中断优先级分配方法,确保对中断处理时间要求高的通信请求能实时响应。实验结果表明,该系统能提升油气液位控制和紧急信息通讯效率。

Robust Consensus Tracking Control of Uncertain Multi-Agent Systems With Local Disturbance Rejection

In this paper,a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed graph.It is of two-degree-of-freedom nature.Specifically,a robust distributed controller is designed for consensus tracking,while a local disturbance estimator is designed for each agent without requiring the input channel information of disturbances.The condition for asymptotic disturbance rejection is derived.Moreover,even when the disturbance model is not exactly known,the developed method also provides good disturbance-rejection performance.Then,a robust stabilization condition with less conservativeness is derived for the whole multi-agent system.Further,a design algorithm is given.Finally,comparisons with the conventional one-degree-of-freedombased distributed disturbance-rejection method for mismatched disturbances and the distributed extended-state observer for matched disturbances validate the developed method.

Data-Driven Control of Distributed Event-Triggered Network Systems

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems(a.k.a.network systems).To this end,we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling,under which a model-based stability criterion for the closed-loop network system is derived,by leveraging a discrete-time looped-functional approach.Marrying the model-based criterion with a data-driven system representation recently developed in the literature,a purely data-driven stability criterion expressed in the form of linear matrix inequalities(LMIs)is established.Meanwhile,the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input data.Finally,numerical results corroborate the efficacy of the proposed distributed data-driven event-triggered network system(ETS)in cutting off data transmissions and the co-design procedure.

Operation Control Method of Relay Protection in Flexible DC Distribution Network Compatible with Distributed Power Supply

A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.

A Two-Layer Fuzzy Control Strategy for the Participation of Energy Storage Battery Systems in Grid Frequency Regulation

To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the loadwhen a large number of newenergy sources are connected to the grid,a two-layer fuzzy control strategy is proposed for the participation of the energy storage battery system in FM.Firstly,considering the coordination of FM units responding to automatic power generation control commands,a comprehensive allocation strategy of two signals under automatic power generation control commands is proposed to give full play to the advantages of two FM signals while enabling better coordination of two FM units responding to FM commands;secondly,based on the grid FM demand and battery FM capability,a double-layer fuzzy control strategy is proposed for FM units responding to automatic power generation control commands in a coordinated manner under dual-signal allocation mode to precisely allocate the power output depth of FM units,which can control the fluctuation of frequency deviation within a smaller range at a faster speed while maintaining the battery charge state;finally,the proposed Finally,the proposed control strategy is simulated and verified inMatlab/Simulink.The results show that the proposed control strategy can control the frequency deviation within a smaller range in a shorter time,better stabilize the fluctuation of the battery charge level,and improve the utilization of the FM unit.

EAST Cryogenic Supervisory and Control System Based on Delta-V DCS

The control system for the Experimental Advanced Superconductive Tokamak （EAST） cryogenic system is designed and constructed based on Delta-V DCS （Distribution Control System）, which consists of engineering workstations, operator workstations, application workstations, redundant controller units, input/output （I/O） cards and a redundant control network. Our task is to design a supervisory and control system to provide the operator interface for control and monitoring, sending alarms, archiving of selected signals, and other routines to analyze realtime and historic data. The hardware configuration, software structure and control algorithms are illustrated in detail in this paper. Hvpothetic oroblems and further research are also mentioned.

DCS devices based non-linear process control system design for plants with distributed time-delay using particle filter

Remote control process system with distributed time-delay has attracted much attention in different fields.In this paper,non-linear remote control of a single tank process system with wireless network is considered.To deal with the distributed time-delay in a large-scale plant,the time-delay compensation controller based on DCS devices is designed by using operator theory and particle filter.Distributed control system(DCS)device is developed to monitor and control from the central monitoring room to each process.The particle filter is a probabilistic method to estimate unobservable information from observable information.First,remote control system and experimental equipment are introduced.Second,control system based on an operator theory is designed.Then,process system with distributed time-delay using particle filter is carried out.Finally,the actual experiment is conducted by using the proposed time-delay compensation controller.When estimating with the proposed method,the result is close to the case in which the distributed time-delay does not exist.The effectiveness of the proposed control system is confirmed by experiment results.

Distributed generator-based distribution system service restoration strategy and model-free control methods

The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.

Modeling, Analysis and Simulation of a High-Efficiency Battery Control System

This paper explains step-by-step modeling and simulation of the full circuits of a battery control system and connected together starting from the AC input source to the battery control and storage system.The three-phase half-controlled rectifier has been designed to control and convert the AC power into DC power.In addition,two types of direct current converters have been used in this paper which are a buck and bidirectional DC/DC converters.These systems adjust the output voltage to be lower or higher than the input voltage.In the buck converters,the main switch operates in conduction or cut-off mode and is triggered by a Pulse-Width Modulated(PWM)signal.The output and input voltage levels ratio are used to calculate thePWMsignal’s duty cycle.Therefore,the duty cycle indicates the operation mode of the converter in steady-state operation.In this study,we analyze and control of a buck converter with the PWM signal.Besides,the bidirectional DC/DC converter has been achieved and optimized by PI control methods to control the battery charging and discharging modes.The simulation has been applied via the Matlab/Simulink environment.The results show the activity of each part of the designed circuits starting from the converters and the battery control system in charge and discharge modes.

A review of artificial intelligence applications in high-speed railway systems

In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.

An autobias control system for the electro optic modulator used in a quantum key distribution system

In a quantum key distribution system, it is crucial to keep the extinction ratio of the coherent pulses stable. This means that the direct current bias point of the electro-optic modulator （EOM） used for generating coherent pulses must be locked. In this paper, an autobias control system based on a lock-in-amplifier for the EOM is introduced. Its drift information extracting theory and control method are analyzed comprehensively. The long term drift of the extinction ratio of the coherent pulses is measured by a single photon detector, which indicates that the autobias control system is effective for stabilizing the bias point of the EOM.

Paleozoic Composite Petroleum System of North Africa:Hydrocarbon Distribution and Main Controlling Factors

North Africa, which is one of the main oil and gas producing regions in the world, is best known for its subsalt Paleozoic-Triassic reservoirs and Paleozoic source rocks. Hydrocarbon abundance varies greatly from one structural domain to another areally and from one stratigraphic interval to another vertically. Analyses of the essential elements and geological processes of the Paleozoic petroleum system indicate that the distribution of the Lower Silurian shale source rocks, the development of a thick Mesozoic overburden, the presence of the Upper Triassic-Lower Jurassic evaporite seal are the most important factors goveming the distribution of the Paleozoic-sourced hydrocarbons in North Africa. The Mesozoic sequence plays a critical role for hydrocarbons to accumulate by enabling the maturation of the Paleozoic source rocks during the Mesozoic-Paleogene times and preserving the accumulated hydrocarbons. Basins and surrounding uplifts, particularly the latter, with a thick Mesozoic sequence and a regional evaporite seal generally have abundant hydrocarbons. Basins where only a thin Mesozoic overburden was developed tend to have a very poor to moderate hydrocarbon prospectivity.

Research on Volt/Var Control of Distribution Networks Based on PPO Algorithm

In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.

A Note on the Controllability of Distribution Parameter Control System

This paper gives the relation between the precise controllabilities of two distrib-ution parameter systems.