Adaptive Robust Control of Multi-Machine Power Systems with Control Time Delay

The adaptive H_∞ control problem of multi-machine power system in the case of disturbances and uncertain parameters is discussed,based on a Hamiltonian model.Considered the effect of time delay during control and transmission,a Hamilton model with control time delay is established.Lyapunov-Krasovskii function is selected,and a controller which makes the system asymptotically stable is got.The controller not only achieves the stability control for nonlinear systems with time delay,but also has the ability to suppress the external disturbances and adaptive ability to system parameter perturbation.The simulation results show the effect of the controller.

Wide-area nonlinear robust voltage control strategy for multi-machine power systems

This paper presented a novel wide-area nonlinear excitation control strategy for multi-machine power systems. A simple and effective model transformation method was proposed for the system's mathematical model in the COI (center of inertia) coordinate system. The system was transformed to an uncertain linear one where deviation of generator terminal voltage became one of the new state variables. Then a wide-area nonlinear robust voltage controller was designed utilizing a LMI (linear matrix inequality) based robust control theory. The proposed controller does not rely on any preselected system operating point, adapts to variations of network parameters and system operation conditions, and assures regulation accuracy of generator terminal voltages. Neither rotor angle nor any variable's differentiation needs to be measured for the proposed controller, and only terminal voltages, rotor speeds, active and reactive power outputs of generators are required. In addition, the proposed controller not only takes into account time delays of remote signals, but also eliminates the effect of wide-area information's incompleteness when not all generators are equipped with PMU (phase measurement unit). Detailed tests were conducted by PSCAD/EMTDC for a three-machine and four-machine power systems respectively, and simulation results illustrate high performance of the proposed controller.

Switching Excitation Controller for Enhancement of Transient Stability of Multi-machine Power Systems

This paper proposes a switching structure excitation controller(SSEC)to enhance the transient stability of multimachine power systems.The SSEC switches between a bangbang funnel excitation controller(BFEC)and a conventional excitation controller(CEC),based on an appropriately designed state-dependent switching strategy.Only the tracking error of rotor angle is required to realize the BFEC in a bang-bang manner with two control values.If the feasibility assumptions of the BFEC are satisfied,the tracking error of rotor angle can be regulated within the predefined error funnels.The power system having the SSEC installed can achieve faster convergence performance compared to that having the CEC implemented only.Simulation studies are carried out in the New England 10-generator 39-bus power system.The control performance of the SSEC is evaluated in the cases that three-phase-to-ground fault and transmission line outage occur in the power system,respectively.

Coordinated nonlinear robust control of TCSC and excitation for multi-machine systems

An advanced nonlinear robust control scheme is proposed for multi-machine power systems equipped with thyristor-controlled series compensation (TCSC). First, a decentralized nonlinear robust control approach based on the feedback linearization and H∞ theory is introduced to eliminate the nonlinearities and interconnections of the studied system, and to attenuate the exogenous disturbances that enter die system. Then, a system model is built up, which has considered all the generators’ and TCSC’s dynamics, and the effects of uncertainties such as disturbances. Next, a decentralized nonlinear robust coordinated control law is developed based on this model. Simulation results on a six-machine power system show that the transient stability of the power system is obviously improved and die power transfer capacity of long distance transmission lines is enhanced regardless of fault locations and system operation points. In addition, the control law has engineering practicality since all the variables in the expression of he control strategy can be measured locally.

Adaptive Excitation Control with L_2 Disturbance Attenuation for Multi-Machine Power Systems

Generator excitation control plays an important role in improving the dynamic performance and stability of power systems. This paper is concerned with nonlinear decentralized adaptive excitation control for multi-machine power systems. Based on a recursive design method, an adaptive excitation control law with L2 disturbance attenuation is constructed. Furthermore, it is verified that the proposed control scheme possesses the property of decentralization and the robustness in the sense of L2-gain. As a consequence, transient stability of a multi-machine power system is guaranteed, regardless of system parameters variation and faults.

Capacity planning of hydro-wind-solar hybrid power systems considering hydropower forbidden zones

In the capacity planning of hydro-wind-solar power systems(CPHPS),it is crucial to use flexible hydropower to complement the variable wind-solar power.Hydropower units must be operated such that they avoid specific restricted operation zones,that is,forbidden zones(FZs),to avoid the risks associated with hydropower unit vibration.FZs cause limitations in terms of both the hydropower generation and flexible regulation in the hydro-wind-solar power systems.Therefore,it is essential to consider FZs when determining the optimal wind-solar power capacity that can be compensated by the hydropower.This study presents a mathematical model that incorporates the FZ constraints into the CPHPS problem.Firstly,the FZs of the hydropower units are converted into those of the hydropower plants based on set theory.Secondly,a mathematical model was formulated for the CPHPS,which couples the FZ constraints of hydropower plants with other operational constraints(e.g.,power balance constraints,new energy consumption limits,and hydropower generation functions).Thirdly,dynamic programming with successive approximations is employed to solve the proposed model.Lastly,case studies were conducted on the hydro-wind-solar system of the Qingshui River to demonstrate the effectiveness of the proposed model.

Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.

Research on Disaster Prevention and Mitigation Technologies in Power Systems

Power systems are critical to modern society,providing the backbone for all economic,industrial,and residential activities.However,these systems face significant threats from both natural and man-made disasters,such as earthquakes,floods,hurricanes,cyber-attacks,and equipment failures.The vulnerability of power systems to these disasters can result in prolonged outages,economic losses,safety risks,and social consequences.This paper explores various disaster prevention and mitigation technologies employed in power systems to enhance resilience and ensure reliable electricity supply during and after disasters.It discusses early warning systems for natural hazards,resilient infrastructure designs,and cybersecurity measures to defend against man-made threats.Additionally,it examines fault detection,power system restoration,and disaster-resilient control strategies that aid in quick recovery from disruptions.The integration of smart grids,renewable energy sources,and advanced control technologies is emphasized as crucial for improving disaster preparedness and minimizing recovery time.Through the application of these technologies,power systems can better withstand and recover from the growing risks posed by both natural and human-induced disasters.

Fault Detection and Prevention Strategies in Power Systems

Power systems are critical to modern society,but their complexity has increased with the integration of renewable energy and advanced technologies.This paper explores fault detection and prevention strategies essential for ensuring system reliability.We examine traditional methods such as overcurrent and differential protection,as well as advanced techniques including machine learning(ML)and artificial intelligence(AI).Additionally,we discuss fault prevention strategies like predictive maintenance,redundancy,and self-healing grids.Despite advancements,challenges such as the complexity of modern grids,cybersecurity threats,and economic constraints remain.The paper concludes with future prospects,emphasizing emerging technologies and global research initiatives aimed at enhancing grid resilience and security.

Adaptive Protection Mechanisms in Power Systems

With the increasing complexity and dynamic nature of modern power grids,adaptive protection mechanisms have emerged as a promising solution to address the challenges faced by traditional protection systems.These systems dynamically adjust their settings based on real-time grid conditions,enabling faster fault detection,improved fault isolation,and enhanced system stability.The need for such adaptive protection systems has become more pronounced as power systems evolve with the integration of renewable energy sources,distributed generation,and microgrids.By leveraging advanced technologies such as machine learning,artificial intelligence,smart sensors,and wide-area measurement systems,adaptive protection mechanisms provide a more flexible and resilient approach to grid protection.This paper explores the definition,key features,enabling technologies,and applications of adaptive protection in power systems,with a focus on its role in distribution networks,transmission networks,and the integration of renewable energy sources.The integration of adaptive protection into modern power grids is essential for maintaining grid reliability,minimizing service interruptions,and optimizing the overall performance of power systems.

Applications of Localized Phase Compensation Method to Design a Stabilizer in a Multi-machine Power System

为了演示和验证稳定器设计的就地相位补偿法在多机电力系统中的应用,介绍在多机电力系统中,就地补偿设计稳定器的2个应用实例。第1个实例是在多机电力系统中就地补偿设计电力系统稳定器（power system stabilizer,PSS）,阻尼电力系统局部模振荡。第2个实例是就地补偿设计附加在静态同步补偿器（static synchronous compensator,STATCOM）上的稳定器,抑制多机电力系统中的区域模振荡,并给出在一个16机电力系统中的应用计算和仿真结果。

利用MATLAB中Sim Power Systems模库时变压器模型的参数计算及其仿真结果比较

从MATLAB-S im Power System s中变压器模型仿真的角度,介绍了变压器模型的参数计算方法与给定,并结合仿真结果,阐明该文中参数给定方法的合理性.

An Augmented Jacobian Method for Power Flow Analysis of Weakly Looped Distribution Systems with PV Buses

A power flow analysis method for weakly looped distribution systems with PV buses is proposed in this paper. The proposed method is computationally more efficient and more robust compared with the conventional compensation methods. The robustness is achieved by embedding the boundary conditions of loops and PV buses into the Jacobian matrix. The computational efficiency is achieved by the carefully designed factorization of Jacobian matrix. Test results on a 33 bus system are presented.

基于SimPowerSystems的电力系统仿真与潮流分析

叙述了用MATLAB软件中的SIMULINK以及SimPowerSystems工具箱进行简单电力系统仿真的基本过程,并利用Powergui对相应系统进行动态仿真和系统潮流分析.对位于不同节点类型处的负荷模型仿真系统进行了讨论,并给出了模型的实现方法.

基于Power Systems Blockset的电路与电机仿真分析

介绍了基于PowerSystemsBlockset电路与电机的仿真分析法 ,建立了电路模型并进行了正弦稳态仿真分析 ,又建立了电机仿真模型并获得了电机的工作特性 ,另外对绕线式异步电机转子回路串电阻的启动过程进行了仿真。仿真结果与理论分析一致 ,且建模与仿真过程非常简洁 ,说明该方法非常适于电路的正弦稳态分析和异步电机及其拖动系统的动态仿真。

访IBM系统与科技事业部工商企业部大中华区总经理叶明 IBM Power Systems瞄准成长型企业

5月28日，IBM在京举办新一代Power Systems面向成长型企业发布论坛，为了更好地理解IBM的Power Systems策略以及Power Systems针对成长型企业的特殊设计，记者采访了IBM系统与科技事业部工商企业部大中华区总经理叶明。

基于SimPowerSystems的电力系统仿真实践教学研究

对电力系统仿真实践教学进行了研究,重点对基于SimPowerSystems工具的电力系统仿真过程进行了详细论述,首先介绍了电力系统仿真各部件模型,接着详细论述了基于SimPowerSystems的电力系统仿真模型建立过程,包括具体步骤和相关指标,最后通过某地区实际电力系统仿真模型的建立和运行分析,说明通过SimPowerSystems进行电力系统仿真实践教学和研究是十分有效的途径.

IBM：Power Systems成为成长型企业前进引擎

IBM帮助企业在信息化领域取得了巨大的成绩,为解决企业信息化这一棘手的问题提供了答案。