Optimal robust adaptive fuzzy synergetic power system stabilizer design

A new particle swarm optimized robust indirect adaptive power system stabilizer is developed based on recently developed synergetic control methodology. Fuzzy systems are used in an adaptive scheme to approximate the system using a nonlinear model while synergetic control guarantees robustness and the use of a chatter free continuous control law which makes the controller easy to implement. In addition the controller parameters are optimized using PSO approach. Simulation of severe operating conditions of a power system is conducted to validate the effectiveness of the proposed approach while stability is guaranteed via Lyapunov synthesis.     

Design of a nonlinear power system stabilizer using synergetic control theory

Electromechanical oscillations of small magnitude and low frequency exist in the interconnected power system and often persist for long periods of time. Power system stabilizers (PSSs) are traditionally used to provide damping torque for the synchronous generators to suppress the oscillations by generating supplementary control signals for the generator excitation system. Numerous techniques have previously been proposed to design PSSs but many of them are synthesized based on a linearized model. This paper presents a nonlinear power system stabilizer based on synergetic control theory. Synergetic synthesis of the PSS is based fully on a simplified nonlinear model of the power system. The dynamic characteristics of the proposed PSS are studied in a typical single-machine infinite-bus power system and compared with the cases with a conventional PSS and without a PSS. Simulation results show the proposed PSS is robust for such nonlinear dynamic system and achieves better performance than the conventional PSS in damping oscillations.     

基于最小二乘法的最优自适应电力系统稳定器

针对电力系统的强非线性特征及其运行过程中易受扰动的特点,采用基于系统辨识的自适应控制方法,通过选取合适的线性模型对典型的电力系统进行线性化处理,研究了对一般最小二乘法的改进,并结合最优自适应控制方法,设计出一种新型的最优自适应电力系统稳定器.在单机-无穷大系统中将其与传统的电力系统稳定器分别进行仿真.结果表明,在系统受到多种扰动时,这种最优自适应电力系统稳定器都能够有效地抑制低频振荡,使系统迅速恢复稳定运行,从而显示出了该最优自适应电力系统稳定器的设计具有理论研究和实际应用价值.     

模糊电力系统稳定器的设计与实现

针对模糊控制系统具有多参数和非线性的特点，给出了一种基于Matlab的模糊电力系统稳定器快速设计开发方法，以克服传统的设计方法所具有的实现复杂且开发周期长等不足，简要介绍了如何由模糊逻辑工具箱和集成仿真环境Simulink来建立整个系统的仿真模型，由Real-Time Workshop将已取得满意仿真效果的模型转换为应用程序，然后将其下载到目标环境中运行，在线调整参数以达到最佳控制效果，从而实现快速原型开发，即可应用于实际系统。仿真结果表明所设计的模糊电力系统稳定器比传统的电力系统稳定器能更有效地抑制系统低频振荡。     

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.     

Damping inter-area modes of oscillation using an adaptive fuzzy power system stabilizer

This paper introduces an indirect adaptive fuzzy controller as a power system stabilizer used to damp inter-area modes of oscillation following disturbances in power systems. Compared to the IEEE standard multi-band power system stabilizer (MB-PSS), indirect adaptive fuzzy-based stabilizers are more efficient because they can cope with oscillations at different operating points. A nominal model of the power system is identified on-line using a variable structure identifier. A feedback linearization-based control law is implemented using the identified model. The gains of the controller are tuned via a particle swarm optimization routine to ensure system stability and minimum sum of the squares of the speed deviations. A bench-mark problem of a 4-machine 2-area power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature.     

Optimal tunning of type-2 fuzzy logic power system stabilizer based on differential evolution algorithm

In this paper, a type-2 fuzzy logic power system stabilizer with differential evolution algorithm is proposed. As an extension of type-1 fuzzy logic theory, type-2 fuzzy logic theory can effectively improve the control performance by uncertainty of membership function especially when we have to confront with less expert knowledge or unpredicted external disturbances. The corresponding parameters and rule base of type-2 fuzzy logic power system stabilizer are optimally tuned by using differential evolution algorithm for multi-machine power system. Through simulation under different operational conditions, the results demonstrate the effectiveness of the proposed approach for damping the power system electromechanical oscillations.     

调速器侧模糊电力系统稳定器改善水电系统稳定性的仿真研究

由于水力系统的水锤效应和强非线性特性，水轮发电机组采用常规控制难以取得令人满意的效果。介绍了水轮发电机组调速器侧模糊电力系统稳定器FGPSS(Fuzzy Governor Power System Stabilizer)的设计原理。应用Simulink仿真软件构建了以水力系统弹性水击模型和同步发电机非线性模型为基础的仿真模型，并对采用PID，PID 常规GPSS和PID FGPSS三种控制方式的控制效果进行了仿真对比研究。结果表明，FGPSS对于改善电力系统的稳定性具有良好的作用，而且具有较强的鲁棒性。     

电力系统稳定器相位补偿方式对次同步振荡的影响

除了输入信号类型之外,电力系统稳定器(PSS)的相位补偿方式也是其影响次同步振荡的非常重要的因素。设计了四种不同类型的PSS:采用一级超前补偿的速度反馈型PSS,采用两级超前补偿的速度反馈型PSS,采用滞后补偿再反相的速度反馈型PSS,采用滞后补偿的功率反馈型PSS;分析了各PSS的频率特性,加入PSS前后系统的电气阻尼特性,PSS相位补偿方式对次同步频段信号的影响,以及滞后补偿再反相的速度反馈型PSS的可行性。结果表明,采用滞后补偿再反相的速度反馈型PSS对次同步振荡几乎没有影响,该PSS既能利用理想的转速偏差作为输入信号,又能避免对轴系扭振敏感,还能有效抑制低频振荡,具有可行性。     

基于Prony算法的模糊电力系统稳定器设计

在简介Prony算法步骤的基础上,阐述了电力系统低频振荡分析的Prony方法。提出了可将Prony算法应用于模糊电力系统稳定器FPSS(Fuzzy Power System Stabilizer)修正因子、比例因子的调节、整定。采用Prony算法为一个单机无穷大系统设计的FPSS作仿真试验,仿真结果显示了其可行性和有效性,为FPSS的设计提供了一种新方法。     

Design of a power system stabilizer using decentralized adaptive model following tracking control approach

This paper presents the design of a power system stabilizer using decentralized adaptive model following tracking control (DAMFTC) approach to damp oscillations of generators in transient response subjected to uncertainties and generating fault actuators. The power system is represented as a collection of interconnected dynamical subsystems each described by a set of differential/algebraic equations using a clear representation of load voltage magnitude with matched and unmatched time‐varying uncertainties. All adaptive learning algorithms in this control system are derived in the sense of Lyapunov stability analysis subject to state errors due to uncertainties and fault section, so that stability and robustness of the closed‐loop system are ensured and asymptotic‐state tracking can be achieved. An adaptive bound estimation algorithm is investigated to relax the requirement for the bound of uncertainties. The effectiveness of the proposed approach is demonstrated by distributing a detailed simulation of the three‐machine nine‐bus system with nonlinear interactions, uncertainties, and fault actuators. The simulation includes the effects of network and stator transients. Copyright © 2009 John Wiley & Sons, Ltd.     

An adaptive neuro-control approach for multi-machine power systems

We investigate an adaptive neuro-control approach, namely goal representation heuristic dynamic programming (GrHDP), and study the nonlinear optimal control on the multi-machine power system. Compared with the conventional control approaches, the proposed controller conducts the adaptive learning control and assumes unknown of the power system mathematic model. Besides, the proposed design can provide an adaptive reward signal that guides the power system dynamic performance over time. In this paper, we integrate the novel neuro-controller into the multi-machine power system and provide adaptive supplementary control signals. For fair comparative studies, we include the control performance with the conventional heuristic dynamic programming (HDP) approach under the same conditions. The damping performances with and without the conventional power system stabilizer (PSS) are also presented for comparison. Simulation results verify that the investigated neuro-controller can achieve improved performance in terms of the transient stability and robustness under different fault conditions.     

一种神经网络变结构电力系统稳定器的设计

在变结构控制理论的基础上 ,设计了一种基于神经网络的电力系统稳定器 (NNPSS)。利用BP神经网络对系统的状态进行辨识 ,通过对网络的训练 ,使神经网络能对不同的运行状态及扰动产生相对应的附加励磁控制。仿真实验证实了神经网络电力系统稳定器的可行性 ,所设计的NNPSS有效改善了电力系统的稳定性。     

Robust fuzzy logic power system stabilizer based on evolution and learning

A robust fuzzy logic power system stabilizer (FLPSS) based on evolution and learning is proposed in this paper. A hybrid algorithm that combines learning and evolution is developed whereby each one complements other’s strength. Parameters of FLPSS are encoded in chromosome (individual) of genetic algorithm (GA) population. Population of FLPSS in GA learns to stabilize electromechanical oscillations in power system at an operating point, as the best fitness becomes large steady value during successive generations. Operating region of FLPSS is enlarged by learning more operating points over the operating domain. Best FLPSS drawn from last generation is saved as designed FLPSS. Effectiveness of the proposed method is validated on a single machine infinite bus (SMIB) power system. Promising optimal stabilizing performance with designed FLPSS for considered power system is obtained at wide range of operating points.     

An indirect adaptive fuzzy-logic power system stabiliser

An indirect adaptive fuzzy power system stabiliser (AFPSS) is developed using the concept of fuzzy basis functions. The power system is modelled using differential equations with nonlinear parameters which are functions of the state of the system. These nonlinear functions may not be known, however, some linguistic information is available about them. Utilising this information, fuzzy logic systems are designed to model the system behaviour. The control law is obtained using the uncertainty principle. Based on the Lyapunov's synthesis method, adaptation rules are developed to make the controller adaptive to changes in operating conditions of the power system. The simulation studies are carried out for an industrial cogenerator and utilise a one-machine infinite-bus model. Nonlinear simulations reveal that the performance of AFPSS is better than the performance of a conventional (linear) power system stabiliser for a wide range of operating conditions.     

Stabilizing control of power system using fuzzy control

This paper presents an application of fuzzy control to enhance power system stability. The proposed control consists of the controller for large disturbance (FU 1), the fuzzy controller for small disturbance (FU 2), and the fuzzy judgment mechanism (FU 3). FU 1 is determined based on the fuzzy controller [FU 1(F)] is determined according to the control rules and its input signals, i.e., speed deviation and acceleration at every sampling time of the machine. FU 2 consists of two controllers, namely, FU 2-ω and FU 2-P; FU 2-ω has the same mechanism as FU 1, while the output signal of FU 2-P is determined according to the rules together with the change of error of electrical power and terminal voltage. To obtain the optimal desired control signal during both the large and the small disturbances, the operations of FU 1 and FU 2 are judged by FU 3, where the magnitude of speed deviation is chosen as its input signal. The determined control signal is fed to AVR of the machine. The implementation of the proposed control is simple due to the small amount of calculations and required data. The effectiveness of the proposed control is demonstrated by the one-machine infinite-bus system model and very good system performance is obtained throughout all the simulations.     

A novel power swing blocking scheme using adaptive neuro-fuzzy inference system

A power swing may be caused by any sudden change in the configuration or the loading of an electrical network. During a power swing, the impedance locus moves along an impedance circle with possible encroachment into the distance relay zone, which may cause an unnecessary tripping. In order to prevent the distance relay from tripping under such condition, a novel power swing blocking (PSB) scheme is proposed in this paper. The proposed scheme uses an adaptive neuro-fuzzy inference systems (ANFIS) for preventing distance relay from tripping during power swings. The input signals to ANFIS, include the change of positive sequence impedance, positive and negative sequence currents, and power swing center voltage. Extensive tests show that the proposed PSB has two distinct features that are advantageous over existing schemes. The first is that the proposed scheme is able to detect various kinds of power swings thus block distance relays during power swings, even if the power swings are fast or the power swings occur during single pole open conditions. The second distinct feature is that the proposed scheme is able to clear the blocking if faults occur within the relay trip zone during power swings, even if the faults are high resistance faults, or the faults occur at the power swing center, or the faults occur when the power angle is close to 180°.     

Improved synergetic excitation control for transient stability enhancement and voltage regulation of power systems

This paper proposes decentralized improved synergetic excitation controllers (ISEC) for synchronous generators to enhance transient stability and obtain satisfactory voltage regulation performance of power systems. Each generator is considered as a subsystem, for which an ISEC is designed. According to the control objectives, a manifold, which is a linear combination of the deviation of generator terminal voltage, rotor speed and active power, is chosen for the design of ISEC. Compared with the conventional synergetic excitation controller (CSEC), a parameter adaptation scheme is proposed for updating the controller parameter online in order to improve the transient stability and voltage regulation performance simultaneously under various operating conditions. Case studies are undertaken on a single-machine infinite-bus power system and a two-area four-machine power system, respectively. Simulation results show the ISEC can provide better damping and voltage regulation performance, compared with the CSEC without parameter adaptation scheme and the conventional power system stabilizer.     

Design and allocation of power system stabilizers using the particle swarm optimization technique for an interconnected power system

In this paper, three particle swarm optimization (PSO) based power system stabilizers (PSSs) are developed for three power systems. The system under study here is a power pool consisting of 3 power systems. System I represents the Egyptian power system, system II represents the Jordan and Syrian power systems, and system III for the Libyan power system, which are originally self standing and completely independent systems. As a matter of fact each of them should equipped with its own PSS. For this reason this work is started by designing an optimum power stabilizer for each of them standing alone. After which, the developed PSSs are firstly installed one at a time. Then the three PSSs are installed together in the interconnected power system and their effect on its dynamic performance is studied.As a test for stabilization efficiency, the detailed power system model is subjected to a forced outage of a 600-MW generator, which is the biggest unit in the pool, when it is fully loaded. This outage results in loosing of about 3% of the spinning capacity of system I and about 2% of the spinning capacity of the whole interconnected system. The obtained results show an improvement in the power pool performance accompanied with an improvement in the inter-area oscillation.