多通道次同步附加阻尼控制器协调优化策略研究

为提高电力系统的小干扰稳定性,抑制系统中的次同步谐振,研究了多通道次同步附加阻尼控制器之间的协调优化策略。基于模态分离和相位补偿设计了多通道SEDC、TCSC-SSDC和HVDC-SSDC,在充分研究了所有次同步附加阻尼控制器的特点及其适应性的基础上,建立了修改后的IEEE SSR第一标准测试系统,以待改善谐振模式阻尼比最大化为优化目标建立优化模型。利用遗传算法对阻尼控制器参数进行协调优化,以得到能最大程度提高谐振模式阻尼的控制器参数。特征值计算和时域仿真结果表明,经过参数协调优化的多通道附加阻尼控制器能有效地抑制次同步谐振,改善了系统的小干扰稳定性。     

基于量测及智能优化算法的阻尼控制器协调设计

针对PSS与FACTS阻尼控制器的参数协调问题,提出了基于量测及智能优化算法的阻尼控制器协调设计方法。采用基于量测的Prony算法可以准确得到各机电振荡模式的特征值,采用微粒群优化算法可以有效协调优化阻尼控制器参数。仿真分析表明：PSS对提高本地模式及区间模式的阻尼比均有效,FACTS阻尼控制器则对提高区间模式阻尼比则更为有效,采用PSS与FACTS阻尼控制器的协调可以更好地抑制电力系统低频振荡。     

基于子空间辨识和遗传算法的多回直流协调阻尼控制器设计

提出了一种多回直流协调阻尼控制器的设计方法,用子空间辨识法对系统降阶建模,用遗传算法进行参数寻优,并对时滞系统稳定性进行了评估。首先利用基于Prony分析的主模比指标计算法选择直流控制器的广域输入信号,通过仿真得到扰动下系统输入输出数据,基于数据对系统进行子空间辨识,得到系统开环状态空间方程。其次将控制器加入开环系统得到闭环系统状态空间方程,以多种运行方式下的系统最小阻尼比最大化为优化目标,针对闭环系统状态空间方程,用遗传算法对控制器参数进行协调优化。采用基于自由权矩阵的时滞稳定性判据,分析含有多回直流协调控制器的广域电力系统的时滞稳定性。最后以南方电网为例,对多回直流协调阻尼控制器进行仿真,仿真结果表明,通过该方法所得到的多回直流协调阻尼控制器能够较好地提高电网阻尼水平,并满足时滞系统稳定性的要求。     

基于控制敏感因子的PSS和直流附加控制的协调阻尼控制

面对低频振荡阻尼控制器和输入信号多样化的复杂局面,如何优化协调阻尼控制器的输入信号和安装地点值得研究。为此,通过理论推导得出控制敏感因子指标用以指示阻尼控制器最优安装位置和输入信号;进一步提出了基于控制敏感点的电力系统稳定器(PSS)与直流附加阻尼控制的协调优化策略,给出了不依赖系统精确数学模型的实用化计算步骤。通过川渝电网多种运行方式验证,理论计算结果与仿真结果一致,结果表明控制敏感因子能够正确指示阻尼控制器的最优安装位置和输入信号,PSS与直流附加阻尼控制通过相互协调可以全面抑制低频振荡,提高系统运行稳定性。     

PSS与SVC多目标协调设计

随着电力系统的发展,元器件／装置相互间协调运行问题引起人们更多的关注,为此提出一种基于多目标进化算法（MOEA）的控制器设计方法,并在一多机电力系统中,给出了采用该方法进行多台电力系统稳定器（PSS）及静止无功补偿器（SVC）的协调控制设计的实例。仿真结果表明,所提出的协调控制器设计方法是有效的。PSS与SVC的协调运行可以有效地阻尼电力系统中的模态振荡和稳定节点电压。     

双馈风机附加阻尼控制环节与PSS的参数协调优化

对于含双馈风电场的多机电力系统,在双馈风机内部引入附加阻尼控制环节可以抑制系统低频振荡,但双馈风机附加阻尼控制环节可能会影响电力系统稳定器(PSS)抑制低频振荡的效果。提出了一种双馈风机附加阻尼控制环节与PSS的参数协调优化方法,设计了兼顾机电振荡模式和非机电振荡模式的阻尼特性的优化目标函数,并给出了基于粒子群算法的求解方法。以三机系统作为算例,优化设计了双馈风机附加阻尼控制环节与PSS的参数。时域仿真结果表明,所提出的参数协调优化方法可以更好地提升系统的阻尼,有利于低频振荡的快速平抑。     

电力系统稳定器影响频率振荡的机理及阻尼分析方法

频率振荡是有功频率控制过程的小扰动稳定问题。已有研究集中于发电机调速器和原动机环节的分析。电力系统稳定器也可用于抑制频率振荡。分析了发电机励磁系统影响频率振荡的机理,当负荷具有电压调节效应时,则发电机励磁系统通过影响负荷电压进而影响负荷功率,从而对频率振荡产生影响。给出了频率偏差通过电力系统稳定器、励磁、网络、负荷等环节影响电磁功率的过程,利用阻尼转矩法计算电磁功率阻尼系数并分析了电力系统稳定器的影响。提出了多机系统中不同发电机电力系统稳定器对频率振荡阻尼影响大小的评估方法,选择影响大的发电机进行参数优化可更加有效地提高频率振荡阻尼。利用IEEE的4机2区系统对分析结论进行了仿真验证。     

电力系统低频振荡定位与抑制研究

随着电力系统的不断发展,低频振荡问题对电力系统稳定性的影响日益凸显,因此,提出利用TLS-ESPRIT算法首先对低频振荡的振荡模态进行识别,并计算出各发电机组的阻尼转矩系数,进行振荡源识别与定位,然后针对振荡源设计静止无功补偿器(SVC)与电力系统稳定器(PSS)相结合的附加阻尼控制器的方法进行低频振荡抑制,其中阻尼控制器的参数设计经过混沌粒子群算法协调优化处理,起到较好的响应效果。最后通过Matlab搭建了一个四机两区域系统进行仿真分析,其结果表明了此方法能够有效地进行低频的识别与定位,投入阻尼控制器后振荡能够较快平息,验证了此方法的可靠性,提高了电力系统的稳定性。     

基于混沌变异粒子群算法的PSS与SVC阻尼控制器协调优化设计

同步发电机的电力系统稳定器(PSS)与静止无功补偿器(SVC)中附加阻尼控制器相结合可以有效抑制系统低频振荡,从而提高电网的动态稳定性。为使阻尼控制器参数相互匹配,本文提出一种基于混沌变异粒子群优化(CMPSO)算法的PSS与SVC阻尼控制器的参数协调计算方法。该方法以传统粒子群优化(PSO)算法为基础,为避免种群陷入局部最优,算法迭代后期对粒子进行混沌变异操作,从而提高算法的全局搜索能力。综合考虑系统的超调量和响应速率,以阻尼比最大和特征根实部最小为目标函数,将多机电力系统中阻尼控制器参数设计问题转换为带有不等式约束的目标优化问题。在四机两区域系统上的仿真算例表明,CMPSO算法与传统PSO相比具有更好的全局寻优能力。PSS与SVC阻尼控制器的协调优化设计能够在不同的干扰下有效抑制低频振荡,增强电力系统的暂态稳定性,减少故障后的电压波动。     

基于遗传算法的UPFC模糊阻尼控制器参数优化及与梯度下降法的比较

设计了一种统一潮流控制器（UPFC）模糊辅助控制器,能够阻尼互联系统之间功率低频振荡．分别使用遗传算法和梯度下降法实现了模糊阻尼控制器（FDC）的参数优化。建立了UPFC的频域模型,给出了主控制和辅助控制的框图。推导了模糊阻尼控制器参数优化的公式。互联多机系统算例显示了2种优化方法都具有很好的收敛性。且结果吻合,同时由这2种方法优化的阻尼控制器能够很好地阻尼系统的功率振荡。且比传统的基于线性系统设计的辅助控制器在不同的系统运行方式和振荡模式下具有更好的鲁棒性。     

多馈入交直流输电系统的模糊控制器协调优化算法

设计了一套阻尼区域间功率振荡的模糊控制器。在多馈入交直流输电系统的直流功率控制系统和发电机励磁系统中同时采用了该模糊控制器,并对影响其性能的关键参数进行了协调优化。为了解决优化结果容易限于局部最优的问题,采用了遗传算法进行全局并行寻优,同时引入序优化理论在概率意义上保证优化解的质量。仿真结果表明:与常规阻尼控制器相比,模糊控制器能更好地提高交直流互联系统的动态稳定性且具有鲁棒性。序优化遗传算法比传统遗传算法具有更稳定的性能,可作为多馈入交直流输电系统的模糊控制器参数协调优化的一种有效方法。     

Simultaneous tuning of power system damping controllers usinggenetic algorithms

This paper presents a method that simultaneously tune multiple power system damping controllers using genetic algorithms (GAs). Damping controller structures are assumed to be fixed consisting basically of lead-lag filters. The tuning method takes robustness into consideration as it guarantees system stabilization over a prespecified set of operating conditions. Modified GA operators are used in the simultaneous optimization of both phase compensations and gain settings for the stabilizers. The method is applied for global PSS tuning to the well-known New England system and to the coordinated tuning of 22 PSSs in a 1762-bus modified equivalent South-Southeastern Brazilian system     

Intelligent particle swarm optimized fuzzy PID controller for AVR system

In process plants like thermal power plants, biomedical instrumentation the popular use of proportional-integral-derivative (PID) controllers can be noted. Proper tuning of such controllers is obviously a prime priority as any other alternative situation will require a high degree of industrial expertise. So in order to get the best results of PID controllers the optimal tuning of PID gains is required. This paper, thus, deals with the determination of off-line, nominal, optimal PID gains of a PID controller of an automatic voltage regulator (AVR) for nominal system parameters and step reference voltage input. Craziness based particle swarm optimization (CRPSO) and binary coded genetic algorithm (GA) are the two props used to get the optimal PID gains. CRPSO proves to be more robust than GA in performing optimal transient performance even under various nominal operating conditions. Computational time required by CRPSO is lesser than that of GA. Factors that have influenced the enhancement of global searching ability of PSO are the incorporation of systematic and intelligent velocity, position updating procedure and introduction of craziness. This modified from of PSO is termed as CRPSO. For on-line off-nominal system parameters Sugeno fuzzy logic (SFL) is applied to get on-line terminal voltage response. The work of SFL is to extrapolate intelligently and linearly, the nominal optimal gains in order to determine off-nominal optimal gains. The on-line computational burden of SFL is noticeably low. Consequently, on-line optimized transient response of incremental change in terminal voltage is obtained.     

Optimization and coordination of wide-area damping controls for enhancing the transfer capability of interconnected power systems

This paper proposes systematic procedures to design wide-area damping controls (WADCs) in large interconnected power systems. An efficient model reduction method is first introduced, based on the pseudo-random binary signal (PRBS) probing technique and the prediction error identification algorithm (PEM). Then, the comprehensive controllability concept, as well as its calculating method, is proposed for properly locating the supplementary damping controllers. Further, an improved modal performance index is adopted as the measure of the stabilizing effect. With various constraints taken into account to meet practical engineering requirements, finally, the optimized and coordinated tuning of WADC parameters under various operation scenarios is achieved by a constrained nonlinear programming algorithm. The proposed approach has been tested on a practical 437-machine, 2791-node interconnected power system and the simulation results have demonstrated its high effectiveness in damping inter-area oscillations and enhancing across-region transfer capabilities.     

Tuning of power system stabilizers using genetic algorithms

Several techniques exist for developing optimal controllers. This paper investigates the tuning of power system stabilizers (PSS) using genetic algorithms (GA). A digital simulation of a linearized model of a single-machine infinite bus power system at some operating point is used in conjunction with the genetic algorithm optimization process. The integral of the square of the error and the time-multiplied absolute value of the error performance indices are considered in the search for the optimal PSS parameters. In order to have good damping characteristics over a wide range of operating conditions, the PSS parameters are optimized off-line for a selected set of grid points in the real power (P)-reactive power (Q) domain. The optimal settings thus obtained can then be stored and retrieved on-line to update the PSS parameters based on measurements of the generator real and reactive power. Time domain simulations of the system with GA-tuned PSS show the improved dynamic performance under widely varying load conditions.     

基于GATS混合算法的PSS与SVC控制器参数设计

随着电力网络规模的扩大,电力系统优化问题日益复杂,故提出了一种采用遗传禁忌GATS混合优化策略对电力系统稳定器PSS和静止无功补偿器SVC附加线性稳定控制器进行参数协调优化的设计方法。该方法结合遗传算法GA和禁忌搜索算法TS各自的优点,将禁忌搜索引入到遗传算法的变异操作,改进了遗传算法的变异算子,具有比常规遗传算法更强的局部搜索能力。在10机新英格兰电力系统上对该优化方法进行了测试。特征值分析表明,该设计方法能有效地将多种不同运行方式下系统的特征根移到复平面目标函数限定的区域内,保证了小扰动稳定性控制的鲁棒。同时还对不同优化方法的收敛性及计算时间进行了比对,结果表明遗传禁忌混合策略的性能优于常规遗传算法以及遗传模拟退火混合优化策略。     

Bat inspired algorithm based optimal design of model predictive load frequency control

Bat inspired algorithm (BIA) has recently been explored to develop a novel algorithm for distributed optimization and control. In this paper, BIA-based design of model predictive controllers (MPCs) is proposed for load frequency control (LFC) to enhance the damping of oscillations in power systems. The proposed model predictive load frequency controllers are termed as MPLFCs. Two-area hydro-thermal system, equipped with MPLFCs, is considered to accomplish this study. The suggested power system model considers generation rate constraint (GRC) and governor dead band (GDB). Time delays imposed to the power system by governor-turbine, thermodynamic process, and communication channels are accounted for as well. BIA is utilized to search for optimal controller parameters by minimizing a candidate time-domain based objective function. The performance of the proposed controller has been compared to those of the conventional PI controller based on integral square error (ISE) technique and the PI controller optimized by genetic algorithms (GA), in order to demonstrate the superior efficiency of the BIA-based MPLFCs. Simulation results emphasis on the better performance of the proposed MPLFCs compared to conventional and GA-based PI controllers over a wide range of operating conditions and system parameters uncertainties.     

Enhancement of Output Power Smoothing and Transient Stability of DFIG-Based Wind Energy Conversion System Using Optimized Controllers Parameters

In this paper, an attempt is made to tune the controllers of a doubly fed induction generator (DFIG)–based wind energy conversion system (WECS). The procedure is optimized to improve the performance of the WECS under both normal and transient operating conditions. It is shown that under normal operating conditions, the outer control loop of the rotor side converter, i.e., speed controller, affects the quality and quantity of output power. Therefore, to extract the maximum available power and smooth the power injected to the grid, this controller is tuned. On the other hand, other controllers affect the response of the DFIG during transient conditions. Thus, to improve the transient stability of the DFIG, the parameters of these controllers are tuned based on the eigenvalue analysis. To verify the performance of the proposed tuning method, comparisons between the proposed and conventional pole placement methods, under normal and fault operating conditions, are presented.     

多馈入直流输电系统小信号调制器的协调优化整定

分析了多馈入交直流并联输电系统中各直流系统之间可能存在的不良相互作用。提出了对各直流小信号调制器参数进行协调整定的必要性，并将参数的协调整定问题归结为控制器结构已知但有若干未定参数可供优化的数学规划问题，所选的目标函数是与各交流联络线的有功功率和各发电机的功角相关的。基于NETOMAC软件平台，采用程序自带的非线性优化模块，可同时对这些参数进行优化，这种参数整定方法本身已考虑了交直流电力系统固有的非线性特性而不必显式导出整个系统的数学模型，因而不需要进行网络简化或线性化近似，这种方法对大规模交直流电力系统的控制器参数整定具有独到的优势。构造了一个含有两个区域间低频振荡模式的双馈入交直流输电系统，并对该系统的各直流小信号调制器参数进行了协调优化整定，仿真结果表明，经过协调优化后得到的直流小信号调制器能提高整个交直流系统的阻尼性能，并具有良好的鲁棒性。     

不确定互联电力系统的分散鲁棒控制

针对不确定互联电力系统,提出了一种分散鲁棒输出反馈控制器的设计方法.为了使参数不确定性符合工程实际和简化控制器的求解,引入数值界的形式对不确定性进行描述.该方法将控制器的设计归结为一组矩阵不等式的求解问题,采用同伦迭代算法,通过固定不同的变量,将非线性矩阵不等式转化为两组线性矩阵不等式并交替求解.仿真结果表明所获得的控制器使得互联电力系统鲁棒稳定,阻尼转矩充足,满足给定的性能指标,并且具有良好的抑制大扰动的能力.