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.     

Pole placement technique for PSS and TCSC-based stabilizer design using simulated annealing

A pole placement technique for power system stabilizer (PSS) and thyristor controlled series capacitor (TCSC) based stabilizer using simulated annealing (SA) algorithm is presented in this paper. The proposed approach employs SA optimization technique to PSS (SAPSS) and TCSC-based stabilizer (SACSC) design. The design problem is formulated as an optimization problem where SA is applied to search for the optimal setting of the proposed SAPSS and SACSC parameters. A pole placement-based objective function to shift the dominant eigenvalues to the left in the s-plane is considered. The proposed SAPSS and SACSC have been examined on a weakly connected power system with different disturbances, loading conditions, and system parameter variations. Eigenvalue analysis and nonlinear simulation results show the effectiveness and the robustness of the proposed stabilizers and their ability to provide efficient damping of low frequency oscillations. In addition, the performance of the proposed stabilizers outperforms that of the conventional power system stabilizer (CPSS). It is also observed that the proposed SACSC improves greatly the voltage profile of the system under severe disturbances.     

Strict-Tabu Based Eigenvalue Optimization of Power System Stabilizer

A Strict-Tabu (S-Tabu) optimization of power system stabilizer (PSS) parameters has been developed and presented in this paper. To achieve good damping characteristics over a wide range of operating conditions, S-Tabu is used to search for the best eigenvalue of the PSS and later installed into the phase lead-lag controller. The implementation studies are carried out on both singlemachine, infinite-bus, and multimachine power systems, respectively. Simulation studies for a variety of disturbances on the power system with optimized PSS demonstrate its effectiveness in improving system performance. Comparison studies are also performed to show the advantages of the proposed controller over the nonoptimized Conventional PSS (CPSS).     

A fuzzy basis function network based power system stabilizer for generator excitation control

A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. 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 retune 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 synchronous machine equipped with the proposed stabilizer subject to major disturbances are investigated. The performance of the proposed FBFN PSS is compared with that of a conventional power system stabilizer (CPSS) to demonstrate the superiority of the proposed stabilizer. The effect of parameter changes on the proposed stabilizer performance is also examined. The results show the robustness of the proposed FBFN PSS and its capability to enhance system damping over a wide range of operating conditions.     

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     

Power system stabilizer design using Strength Pareto multi-objective optimization approach

Power system stabilizers (PSSs) are the most well-known and effective tools to damp power system oscillation caused by disturbances. To gain a good transient response, the design methodology of the PSS is quite important. The present paper, discusses a new method for PSS design using the multi-objective optimization approach named Strength Pareto approach. Maximizations of the damping factor and the damping ratio of power system modes are taken as the goals or two objective functions, when designing the PSS parameters. The program generates a set of optimal parameters called Pareto set corresponding to each Pareto front, which is a set of optimal results for the objective functions. This provides an excellent negotiation opportunity for the system manager, manufacturer of the PSS and customers to pick out the desired PSS from a set of optimally designed PSSs. The proposed approach is implemented and examined in the system comprising a single machine connected to an infinite bus via a transmission line. This is also done for two familiar multi-machine systems named two-area four-machine system of Kundur and ten-machine 39-bus New England system. Parameters of the Conventional Power System Stabilizer (CPSS) are optimally designed by the proposed approach. Finally, a comparison with famous GAs is given.     

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.     

Coordinated Design of Power System Stabilizers and Static Phase Shifters Using Genetic Algorithm

Coordinated design of a power system stabilizer (PSS) and a static phase shifter (SPS) using genetic algorithm (GA) is investigated in this paper. The design problem of PSS and SPS controller is formulated as an optimization problem. An eigenvalue-based objective function to increase the system damping is proposed. Then, GA is employed to search for optimal controller parameters. Different control schemes have been proposed and tested on a weakly connected power system with different disturbances, loading conditions, and parameter variations. It was observed that although the PSS enhances the power system stability, the SPS controller provides most of the damping and improves the voltage profile of the system. The nonlinear simulation results show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and system parameter variations.     

Design of a robust PID-PSS for an uncertain power system with simplified stability conditions

In a deregulated power system uncertainty exists and lack of sufficient damping can lead to Low Frequency Oscillations (LFO). The problem can be addressed using robust Power System Stabilizers (PSS). In this paper, an optimal procedure to design a robust PID-PSS using interval arithmetic for the Single Machine Infinite Bus (SMIB) power system is proposed. The interval modelling captures the wide variations of operating conditions in bounds of system coefficients. In the proposed design procedure, simple and new closed loop stability conditions for an SMIB interval system are developed and are used to design an optimum PID-PSS for improving the performance of an SMIB system. The optimum PID-PSS is attained by tuning the parameters using the FMINCON tool provided in MATLAB. The robustness of the proposed PID-PSS design is validated and compared to other notable methods in the literature when the system is subjected to different uncertainties. The simulation results and performance error values show the effectiveness of the proposed robust PID-PSS controller.     

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.     

Chaotic ant swarm optimization for fuzzy-based tuning of power system stabilizer

In this paper, chaotic ant swarm optimization (CASO) is utilized to tune the parameters of both single-input and dual-input power system stabilizers (PSSs). This algorithm explores the chaotic and self-organization behavior of ants in the foraging process. A novel concept, like craziness, is introduced in the CASO to achieve improved performance of the algorithm. While comparing CASO with either particle swarm optimization or genetic algorithm, it is revealed that CASO is more effective than the others in finding the optimal transient performance of a PSS and automatic voltage regulator equipped single-machine-infinite-bus system. Conventional PSS (CPSS) and the three dual-input IEEE PSSs (PSS2B, PSS3B, and PSS4B) are optimally tuned to obtain the optimal transient performances. It is revealed that the transient performance of dual-input PSS is better than single-input PSS. It is, further, explored that among dual-input PSSs, PSS3B offers superior transient performance. Takagi Sugeno fuzzy logic (SFL) based approach is adopted for on-line, off-nominal operating conditions. On real time measurements of system operating conditions, SFL adaptively and very fast yields on-line, off-nominal optimal stabilizer variables.     

新疆电网电力系统稳定器设计与仿真

采用传统频域方法进行电力系统稳定器(power system stabilizer,PSS)参数设计时只考虑本机组的运行,忽视了电网的整体运行情况。为此,文章基于降阶选择模式分析法对PSS参数进行优化,形成了系统的降阶状态方程。通过计算状态方程特征根与状态变量的相关性及灵敏度,确定了PSS的配置点。文中的方法不必计算系统全部特征根,所需的计算时间较少。针对新疆实际电网,文章还进行了PSS参数设计,确定了PSS的安装地点及安装机组,仿真结果表明文中的PSS抑制振荡的效果良好,验证了文中方法的正确性和有效性。     

Robust coordinated design of multiple and multi-type damping controller using differential evolution algorithm

A robust coordination scheme to improve the stability of a power system by optimal design of multiple and multi-type damping controllers is presented in this paper. The controllers considered are power system stabilizer (PSS) and static synchronous series compensator (SSSC)-based controller. Local measurements are provided as input signals to all the controllers. The coordinated design problem is formulated as an optimization problem and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performance of the proposed controllers is evaluated for both single-machine infinite-bus power system and multi-machine power system. Nonlinear simulation results are presented over a wide range of loading conditions and system configurations to show the effectiveness and robustness of the proposed coordinated design approach. It is observed that the proposed controllers provide efficient damping to power system oscillations under a wide range of operating conditions and under various disturbances. Further, simulation results show that, in a multi-machine power system, the modal oscillations are effectively damped by the proposed approach.     

Parameter optimization of multimachine power system stabilizers using genetic local search

A genetic local search (GLS) algorithm for optimal design of multimachine power system stabilizers (PSSs) is presented in this paper. The proposed approach hybridizes the genetic algorithm (GA) with a heuristic local search in order to combine their strengths and overcome their shortcomings. The potential of the proposed approach for optimal parameter settings of the widely used conventional lead–lag PSSs has been investigated. Unlike the conventional optimization techniques, the proposed approach is robust to the initial guess. The performance of the proposed GLS-based PSS (GLSPSS) under different disturbances, loading conditions, and system configurations is investigated for different multimachine power systems. Eigenvalue analysis and simulation results show the effectiveness and robustness of the proposed GLSPSS to damp out local as well as interarea modes of oscillations and work effectively over a wide range of loading conditions and system configurations.     

A GENETIC-BASED POWER SYSTEM STABILIZER

ABSTRACT

A Genetic-based Power System Stabilizer (GPSS) is presented in this paper to improve power system dynamic stability. The proposed GPSS parameters are optimized using Genetic Algorithms (GA). The main advantage of the proposed GPSS is that far less information than other design techniques is required without the need for linearization process. Time domain simulations of a synchronous machine subject to major disturbances are investigated. The performance of the proposed GPSS is compared with that of conventional lead-lag power system stabilizer (CPSS) to demonstrate the superiority of the proposed GPSS. The effect of parameter changes on the proposed stabilizer performance is also examined. The results show the robustness of the proposed GPSS and its capability to enhance the system damping over a wide range of operating conditions and system parameter variations.     

Adaptive tuning of power system stabilizers using radial basis function networks

A novel approach for on-line adaptive tuning of power system stabilizer (PSS) parameters using radial basis function networks (RBFNs) is presented in this paper. The proposed RBFN is trained over a wide range of operating conditions and system parameter variations in order to re-tune PSS parameters on-line based on real-time measurements of machine loading conditions. The orthogonal least squares (OLS) learning algorithm is developed for designing an adequate and parsimonious RBFN model. The simulation results of the proposed radial basis function network based power system stabilizer (RBFN PSS) are compared to those of conventional stabilizers in case of a single machine infinite bus (SMIB) system as well as a multimachine power system (MMPS). The effect of system parameter variations on the proposed stabilizer performance is also examined. The results show the robustness of the proposed RBFN PSS and its ability to enhance system damping over a wide range of operating conditions and system parameter variations. The major features of the proposed RBFN PSS are that it is of decentralized nature and does not require on-line model identification for tuning process. These features make the proposed RBFN PSS easy to tune and install.     

Coordinated design of PSS and TCSC to mitigate interarea oscillations

Thyristor controlled series compensator (TCSC) as a promising series flexible AC transmission system (FACTS) device is generally used for controlling the real power flow in transmission lines. It can increase the system stability as the complementary functionality by minimizing the power oscillations. The effectiveness of TCSC in its primary and supplementary applications depends on the selection of its optimal location and defining a proper input signal. In this paper, a new method based on the active power sensitivity approach is applied to find the optimal location of TCSC. In addition, Hankel singular values (HSVs) and right half plane-zeros (RHP-zeros) analyses have been proposed to find the most appropriate stabilizing input signal for the supplementary functionality of TCSC to damp out the interarea modes of oscillation. Finally, the optimal design of power oscillation damper (POD) and simultaneous coordinated design of power system stabilizer (PSS) and POD are implemented separately in a large-scale power system. The tuning problem of POD-TCSC parameters as well as the coordinated POD-TCSC & PSS are converted to a multi-objective optimization problem and solved using particle swarm optimization (PSO) algorithm. The performance of the proposed method has been validated through eigenvalue analysis and nonlinear time domain simulation in a 16-machine 68-bus test system. The simulation results show a satisfactory robust performance with an excellent capability in damping of local and interarea power oscillations.     

Multi-machine power system stabilizer design by rule based bacteria foraging

Several power system stabilizers (PSS) connected in number of machines in a multi-machine power systems, pose the problem of appropriate tuning of their parameters so that overall system dynamic stability can be improved in a robust way. Based on the foraging behavior of Escherichia coli bacteria in human intestine, this paper attempts to optimize simultaneously three constants each of several PSS present in a multi-machine power system. The tuning is done taking an objective function that incorporates a multi-operative condition, consisting of nominal and various changed conditions, into it. The convergence with the proposed rule based bacteria foraging (RBBF) optimization technique is superior to the conventional and genetic algorithm (GA) techniques. Robustness of tuning with the proposed method was verified, with transient stability analysis of the system by time domain simulations subjecting the power system to different types of disturbances.     

Comparison of different robust control methods in design of decentralized UPFC controllers

The unified power flow controller (UPFC) integrates properties of both shunt and series compensations, and can effectively alter power system parameters in such a way that increases power transfer capability and enhances system stability. In practice, simple proportional–integral (PI) controllers are used to control the UPFC. However, the PI control parameters are usually tuned based on classical or trial-and-error approaches and as such, they are incapable of obtaining good dynamic performance for a wide range of operating conditions and various loads in power systems. Hence, in this article robust control approaches are proposed based on the quantitative feedback theory (QFT), H_∞ loop-shaping and μ-synthesis, to design UPFC controllers (power-flow and DC-voltage regulator). The three mentioned methods are compared with each other and a supplementary damping controller is developed to improve damping power system oscillations. Here, a single-machine infinite-bus (SMIB) power system, installed with a UPFC (with system parametric uncertainties) is considered as a case study. The system parametric uncertainties are obtained following 40% simultaneous alterations in parameters and load from their typical values. The simulation results indicate satisfactory verifications of the robust control methods in dealing with the uncertainties considered. When the above three methods and the PI controller are compared in performance in several time-domain simulation tests, the results show clear superiority of the three methods over the PI controller, with the QFT presenting the best performance amongst the three robust control.     

Reaching phase free adaptive fuzzy synergetic power system stabilizer

In this paper, an adaptive fuzzy power system stabilizer is developed based on robust synergetic control theory and terminal attractor techniques. The main contribution consists in making the dynamic system insensitive to parameters variation. This aim is achieved using a new synergetic controller design such that power system states start, evolve and remain on a designer chosen attractor toward the equilibrium point therefore avoiding transient mode. Rendering the design more robust, fuzzy logic systems are used to approximate the unknown power system dynamic functions without calling upon usual model linearization and simplifications. Based on an indirect adaptive scheme and Lyapunov theory, adaptation laws are developed to make the controller handle parameters variations due to the different operating conditions occurring on the power system and to guarantee stability. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results show the effectiveness and robustness of the proposed stabilizer in damping power system oscillations under various disturbances and better overall performance than classical PSS and some other types of power stabilizers.