Three-dimensional power system stabilizer

Power system stabilizers (PSSs) are used to enhance damping of power system oscillations through excitation control of synchronous generator. The objective of the PSS is to generate a stabilizing signal, which produces a damping torque component on the generator shaft. Conventional PSSs are designed with the phase compensation technique in the frequency domain and include the lead-lag blocks whose parameters are determined according to a linearized power system model. The performance of conventional PSSs (CPSSs) depends upon the generator operating point and the system parameters, but a reasonable level of robustness can be achieved depending on the tuning method. This paper presents a new three-dimensional PSS (3D PSS), which uses rotor speed deviation, rotor acceleration and load angle deviation as input signals. The 3D PSS attempts to return the generator to the state-space origin, based on the generator’s trajectory in state-space and the achievement of torque equilibrium. The 3D PSS is robust to system parameters changes. The proposed algorithm was implemented in a digital control system, tested in a laboratory environment on a synchronous generator connected to the power system, and then compared with CPSS. Experimental results show that the proposed PSS achieves better performance than the CPSS in damping oscillations.     

Effects of various power system stabilizers on improving power system dynamic performance

To ensure the small-signal stability of a power system, power system stabilizers (PSSs) are extensively applied for damping low frequency power oscillations through modulating the excitation supplied to synchronous machines, and increasing interest has been focused on developing different PSS schemes to tackle the threat of damping oscillations to power system stability. This paper examines four different PSS models and investigates their performances on damping power system dynamics using both small-signal eigenvalue analysis and large-signal dynamic simulations. The four kinds of PSSs examined include the Conventional PSS (CPSS), Single Neuron based PSS (SNPSS), Adaptive PSS (APSS) and Multi-band PSS (MBPSS). A steep descent parameter optimization algorithm is employed to seek the optimal PSS design parameters. To evaluate the effects of these PSSs on improving power system dynamic behaviors, case studies are carried out on an 8-unit 24-bus power system through both small-signal eigenvalue analysis and large-signal time-domain simulations.     

Proposed mechanism for performance of power system stabilizers in the condition of strong resonance

This paper suggests a mechanism for the dynamic performance of damping controllers in the condition of strong resonance. The mechanism explains theoretically how the variation of a control parameter can move the resonance point in such a way to stabilize or destabilize the coupled modes. As an application, this mechanism is applied to justify the performance of power system stabilizers (PSSs) in a 2-area 4-machine test system, in which an exciter mode and an inter-area mode interact near a strong resonance. It makes the performance of the PSSs on the stability of the inter-area mode become severely dependent on the place of the PSS and the position of operating point with respect to the resonance point. In this circumstance, the PSSs of one of the system areas destabilize the inter-area mode. Considering the proposed mechanism, the appropriate location of the PSS and its proper gain value are identified to obtain the maximum damping of inter-area mode at each of the operating points. In addition, it is shown that due to the strong resonance, conventional methods make incorrect placement of the PSS; however, by using the real part of speed participation factors, suitable machines are chosen to place the PSS. This index provides important information regarding the impacts of strong resonance on the performance of PSSs.     

Optimal locations and tuning of robust power system stabilizer using genetic algorithms

Optimal locations and design of robust multimachine power system stabilizers (PSSs) using genetic algorithms (GA) is presented in this paper. The PSS parameters and locations are computed to assure maximum damping performance under different operating conditions. The efficacy of this technique in damping local and inter-area modes of oscillations in multimachine power systems is confirmed through nonlinear simulation results and eigenvalues analysis.     

A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems

A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper to improve power system dynamic stability. The proposed FBFN based PSS provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on machine loading conditions. The orthogonal least squares (OLS) learning algorithm is developed for designing an adequate and parsimonious FBFN model. Time domain simulations of a single machine infinite bus system and a multimachine power system subject to major disturbances are investigated. The performance of the proposed FBFN PSS is compared with that of conventional (CPSS). The results show the capability of the proposed FBFN PSS to enhance the system damping of local modes of oscillations over a wide range of operating conditions. The decentralized nature of the proposed FBFN PSS makes it easy to install and tune     

Pole placement approach for robust optimum design of PSS and TCSC-based stabilizers using reinforcement learning automata

Power system stability enhancement via robust optimum design of power system stabilizers (PSSs) and thyristor controlled series capacitor (TCSC)-based stabilizers is thoroughly investigated in this paper. The design problem of PSS and TCSC-based stabilizers is formulated as an optimization problem where a reinforcement learning automata-based optimization algorithm is applied to search for the optimal setting of the proposed PSS and CSC parameters. A pole placement based objective function is considered to shift the dominant system eigenvalues to the left in the s-plane. For evaluation of the effectiveness and robustness of the proposed stabilizers, their performances have been examined on a weakly connected power system subjected to different disturbances, loading conditions, and system parameter variations. The nonlinear simulation results and eigenvalues analysis demonstrate the high performance of the proposed stabilizers and their ability to provide efficient damping of low frequency oscillations. In addition, it is observed that the proposed CSC has greatly improved the voltage profile of system under severe disturbances.     

An efficient heuristic optimization technique for robust power system stabilizer design

Design of a power system stabilizer (PSS) using simulated annealing (SA) heuristic optimization technique is presented in this paper. Two different PSSs are proposed, namely, simulated annealing based PSS (SPSS) and robust SPSS (RSPSS). The proposed approach employs SA to search for optimal or near optimal settings of (RSPSS). The proposed approach employs SA to search for optimal or near optimal settings of PSS parameters. An objective function that shifts the system eigenvalues associated with the electromechanical modes to the left in the s-plane is proposed. The robustness of the proposed SPSS and RSPSS over a wide range of loading conditions and system parameter uncertainities is investigated. The nonlinear simulation results show the effectiveness of the proposed PSSs to damp out the low frequency oscillations and work effectively over a wide range of loading conditions and system parameter uncertainities.     

基于广域测量信息的互联电网模型预测阻尼控制

提出一种基于模型预测控制的新型阻尼控制器设计方法。为抑制区间低频振荡,该控制器由2级PSS构成,其输入信号由广域测量信号和本地测量信号组成。采用留数矩阵法选择广域控制回路,通过模式辨识进行2级PSS控制。将常规励磁系统中传统的自动电压调节器(automatic voltage regulator,AVR)用模型预测控制器(model predictive controller,MPC)替代,并与2级PSS协调作用,通过模型预测和优化求解,得到励磁控制器的最优控制输入,以实现电压调节和增强阻尼之间的动态协调。典型的四机两区系统仿真结果表明,基于模型预测控制的2级PSS设计的控制效果明显优于传统的阻尼控制,可以快速调节机端电压,显著改善互联电网阻尼。     

Optimal multiobjective design of robust power system stabilizers using genetic algorithms

Optimal multiobjective design of robust multimachine power system stabilizers (PSSs) using genetic algorithms is presented in this paper. A conventional speed-based lead-lag PSS is used in this work. The multimachine power system operating at various loading conditions and system configurations is treated as a finite set of plants. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electromechanical modes of all plants to a prescribed zone in the s-plane. A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The problem of robustly selecting the parameters of the power system stabilizers is converted to an optimization problem which is solved by a genetic algorithm with the eigenvalue-based multiobjective function. The effectiveness of the suggested technique in damping local and interarea modes of oscillations in multimachine power systems, over a wide range of loading conditions and system configurations, is confirmed through eigenvalue analysis and nonlinear simulation results.     

Optimization and coordination of damping controls for improvingsystem dynamic performance

This paper presents a global tuning procedure for FACTS device stabilizers (FDS) and power system stabilizers (PSS) in a multi-machine power system using a parameter-constrained nonlinear optimization algorithm implemented in a simulation program. This algorithm deals with such an optimization problem by solving a sequential quadratic programming using the dual algorithm. The main objective of this procedure is to simultaneously optimize pre-selected parameters of the FDSs and PSSs having fixed parameters in coping with the complex nonlinear nature of the power system. By minimizing a nonexplicit target function in which the oscillatory rotor modes of the generators involved and suing characteristics between areas are included, interactions among the FACTS controls under transient conditions in a multimachine power system are improved. A multimachine power system equipped with a TCSC and an SVC as well as three PSSs is applied to demonstrate the efficiency and robustness of the tuning procedure presented. The results obtained from simulations validate the improvement in damping of overall power oscillations in the system in an optimal and globally coordinated manner. The simulations also show that the stabilizers tuned are robust in providing adequate damping for a range of conditions in the system     

我国交流互联电网动态稳定性的研究及解决策略

在我国大区交流互联系统中存在着区域间弱阻尼或负阻尼低频振荡问题。为了解决该问题,工程人员通过现场试验、整定和调试,目前己为100多台机组配置了电力系统稳定器(PSS)。联网试验及联网后的运行经验证明,这些PSS的配置增强了联网系统的阻尼,保证了联网系统的动态稳定性,是解决我国大区交流互联系统动态稳定问题行之有效的方法。     

采用协同控制理论的同步发电机非线性励磁控制

提出了一种基于协同控制理论的非线性励磁控制器。首先依据同步发电机励磁控制的基本要求和特点,选择机端电压、有功功率和转子角速度三个变量的偏差的线性组合构成流形,以保证有效控制机端电压和抑制系统功率振荡。然后以同步发电机非线性模型为对象,推导出了非线性协同励磁控制器（Synergetic excitation controller,SEC）的控制律,并根据电力系统的运行特性,探讨了控制器参数的选取原则。最后,单机无穷大系统仿真结果表明,无论在大扰动还是在小扰动下,所提非线性协同励磁控制器比常规的AVR+PSS方式下的励磁控制器都能更快更精确地调节机端电压,还能够有效地抑制系统的功率振荡。     

Robust PSS design by probabilistic eigenvalue sensitivity analysis

When a wide range of system operation is taken into account for power system dynamic studies, probabilistic eigenvalue analysis efficiently provides the statistical distributions of concerned eigenvalues. Under the assumption of normal distribution, each eigenvalue can be described by its expectation and variance. To enhance system damping under multi-operating conditions by power system stabilizers (PSSs), effects of PSSs on both eigenvalue expectation and variance should be investigated. In this paper, the conventional eigenvalue sensitivity analysis has been extended to probabilistic environment. Eigenvalue sensitivities for both expectation and variance are determined to form two types of probabilistic sensitivity indices (PSIs). Robust PSS locations are selected by one type of PSI, PSS parameters are tuned by the probabilistic sensitivity analysis using another type of PSI.     

基于概率特征根分析的电力系统稳定器参数设计

多运行方式下的系统特征根将以一定的概率分布在某些区间内。正态假定下的均值、方差可用来描述这种分布特性。当使用电力系统稳定器（PSS）改善系统阻尼时,主要应考虑PSS对临界特征根的均值、方差的影响。文中将传统的特征根灵敏度分析方法扩展为对特征根均值的灵敏度和方差的灵敏度。由此进行的PSS选址和参数设计,将使PSS具有多运行方式下的整体合理性。     

适应复杂电力系统多种运行方式的PSS优化配置

低频振荡的抑制是电力系统规划阶段和运行过程中必须考虑的一个重要问题。抑制低频振荡一般的方法是在励磁调节器上装设电力系统稳定器(PSS)。多机系统中，PSS的配置包括PSS安装位置的选择和参数整定。现有的研究工作主要考虑一种运行方式来进行PSS的优化配置，本文提出了一种同时适应系统的多种运行方式来进行PSS优化配置的方法。通过对西北电网三种典型运行方式的计算结果表明：为了获得更好的抑制低频振荡的效果，PSS的放大倍数不应限定为正值；如按一种运行方式对PSS的参数进行优化则对其它运行方式效果较差，而同时考虑多种运行方式，统一地进行PSS的优化配置则对各种运行方式都能良好地抑制低频振荡。     

基于自校正方法的多机电力系统稳定器设计

低频振荡危害了电力系统的安全和稳定,电力系统稳定器(PSS)是抑止低频振荡的有效方法。但是在复杂系统中,配置和整定电力系统稳定器是一个难题。本文利用自校正方法(ACD)设计了一类新型非线性电力系统稳定器。该稳定器通过在线训练进行设计,摆脱了对系统数学模型的依赖,同时能够对系统中不确定性予以充分考虑,适用于复杂多机环境中PSS的优化设计。训练成功的PSS能够在各种工况下有效抑制系统振荡,同传统稳定器相比具有很强的鲁棒性。文中以四机二区域系统为例,证实了这种新型电力系统稳定器用于多机系统时的优良特性。     

Optimal power system stabilizers for multi machine systems

Excitation supplementary control is used in power systems to enhance the damping of low frequency oscillations due to the mechanical modes of the generators. Traditionally, frequency deviation is fed back to the exciter through phase lag-lead compensators to form the supplementary control. This supplementary control is known as power system stabilizer (PSS). An optimal power system stabilizer (OPSS) based on linear quadratic regulator design and utilizing the conventional phase lag-lead structure of PSS is presented in this paper. Furthermore, a suboptimal power system stabilizer (SOPSS) is proposed by neglecting the coupling gains between machines and feeding back only the speed deviation and the PSS states. The OPSS and SOPSS are compared with the conventional phase lag-lead power system stabilizer and simulation results of several power system examples are presented.     

双馈风电机组附加阻尼控制器与同步发电机PSS协调设计

针对大规模双馈风电机组接入电力系统后的区间低频振荡问题,提出了一种协调双馈风电机组附加阻尼控制器和同步发电机电力系统稳定器(PSS)的设计策略。首先,考虑风电机组的机械部分、电气部分和控制结构,建立了双馈风电机组的机电暂态模型和附加阻尼控制器模型。在闭环电力系统线性化模型的基础上,提出利用动态指标值的优化模型来协调整定双馈风电机组附加阻尼控制器和同步发电机PSS的控制参数,并使用粒子群算法求解优化模型的全局最优解。最后,通过2个标准仿真系统算例,对比传统的阻尼控制器设计策略,验证了所设计策略的有效性和实用性。     

互联电力系统中PSS的全局协调优化

分析了互联电力系统中常规分散、局部设计的PSS之间可能存在的不良相互作用,指出了对相关机组的PSS进行全局协调优化的必要性,并提出了一种多机互联系统中常规 PSS的全局协调优化方法。该方法使用在NETOMAC程序中实现的非线性优化算法,其主要目标是同时优化具有因定参数的PSS的预选参数,以处理电力系统复杂的非线性特性,通过最小化包含相关发电机转子振荡模式和区域间振荡特性的非显式目标函数,使互联电力系统在暂态条件下功率振荡的阻尼特性得到全面改善,因而该方法对大规模电力系统中控制器的全局协调具有独特的优势。4机测试系统和欧洲电网的仿真结果证明了文中所提方法的有效性和鲁棒性。     

A Hybrid Power System Stabilizer Using Neuro-identifier and Predictive Controller

This paper presents the development of a hybrid power system stabilizer (PSS) model designed to enhance the damping characteristics of a practical power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system. The PSS consists of a predictive controller and a neuro-identifier which has been developed based on the functional link network (FLN) model. A recursive on-line training algorithm has been proposed to train the neural network. Simulation results have been obtained under various operating conditions and severe disturbance cases that show that the proposed PSS can provide a better damping to the local as well as interarea modes of oscillations, as compared with a conventional PSS.