An adaptive generator excitation controller based on linear optimalcontrol

An adaptive excitation controller for a synchronous generator based on the linear optimal control theory is proposed. The generator operating conditions are tracked by a model whose parameters are identified every sampling interval using the actual input and output of the generator. The control is computed by solving a third-order Riccati equation and the identified model parameters. Studies on a single-machine infinite-bus system and a three-machine infinite-bus system show that the proposed controller exhibits better performances than an automatic voltage regulator (AVR) with a conventional power system stabilizer (PSS)     

Reducing the effect of penstock pressure pulsations on hydroelectric plant power system stabilizer signals

A characteristic trait of Francis turbines operating at low-head is pressure pulsations that occur during certain load levels of the generator. These stem from pressure variations across the turbine due to pulsating flow in the draft tube. This surging action of the water column is related to draft tube geometry and flow rate of water in the penstock. The pressure pulsations cause torque variations on the turbine and corresponding electric power pulsations. If electric power is used as a feedback signal to the power system stabilizer (PSS), then MVAr and terminal voltage pulsations will occur when the generator is operating in the "rough zone". This paper describes field test results for investigating feedforward control from the penstock, draft tube and spiral case pressure to reduce the effects of MW pulsations on PSS output signals. This investigation involved a PSS with generator power as the feedback signal and the PSS tuned for local and inter-area damping     

Application of an inverse input/output mapped ANN as a power systemstabilizer

An artificial neural network (ANN), trained as an inverse of the controlled plant, to function as a power system stabilizer (PSS) is presented in this paper. In order to make the proposed ANN PSS work properly, it was trained over the full working range of the generating unit with a large variety of disturbances. Data used to train the ANN PSS consisted of the control input and the synchronous machine response with an adaptive PSS (APSS) controlling the generator. During training, the ANN was required to memorize the reverse input/output mapping of the synchronous machine. After the training, the output of the synchronous machine was applied as the input of the ANN PSS and the output of the ANN PSS was used as the control signal. Simulation results show that the proposed ANN PSS can provide good damping of the power system over a wide operating range and significantly improve the system performance     

Multimachine System Transient Stability Improvement using Transient Power System Stabilizers (TPSS)

Power system stabilizers (PSS) have been designed and installed [1,2] to improve the dynamic (smnall signal) response of multimachine systems. This paper presents the theory and test results for improving the transient (large disturbance) behaviour of a multimachine system by supplementing the conventional PSS with a transient power system stabilizer (TPSS). Each generator unit is fitted with a TPSS which, after computation, injects supplementary control signals into both the automatic voltage regulator (AVR) and speed governor control loops.     

新型电力系统稳定器模型分析及参数协调优化

针对新型电力系统稳定器(PSS4B)参数众多且整定优化困难的现状,提出一种基于相位补偿法的PSS4B参数优化方法。在详细分析PSS4B模型的基础上,将待优化参数划分为两部分,采用粒子群优化算法通过两次相位补偿实现参数协调优化,提高了优化效率,且优化后的PSS4B相频特性能更好地满足性能要求。通过Matlab编程建立单机无穷大系统,并改变发电机的转子惯性时间常数以实现PSS4B在不同频段上的仿真,结果表明优化后的PSS4B能兼顾多个频段,有效抑制了低频振荡。     

Stability investigation of a longitudinal power system and itsstabilization by a coordinated application of power system stabilizers

This paper presents the results of a stability investigation of a power system with longitudinal structure and its stabilization by coordinated power system stabilizers (PSSs). The effects of the existing controllers on system stability are studied. If no PSSs are present, the damping of various swing modes in the system will be very poor and low frequency oscillations present. Eigenvalue analysis shows that the undamped modes are sensitive to excitation control while speed governors have little influence on damping. In order to enhance the overall system stability through excitation control, a coordinated design procedure for power system stabilizers has been developed based on generation coherency, total coupling factor and nonlinear simulation. A PSS designed using this procedure is robust to different operating conditions and very effective for damping oscillations. Comprehensive simulation studies were conducted and results are presented     

An adaptive power system stabilizer using on-line trained neuralnetworks

This paper presents an approach to the design of an adaptive power system stabilizer (PSS) based on on-line trained neural networks. Only the inputs and outputs of the generator are measured and there is no need to determine the states of the generator. The proposed neural adaptive PSS (NAPSS) consists of an adaptive neuro-identifier (ANI), which tracks the dynamic characteristics of the plant, and an adaptive neuro-controller (ANC) to damp the low frequency oscillations. These two subnetworks are trained in an on-line mode utilizing the backpropagation method. The use of a single-element error vector along with a small network simplifies the learning algorithm in terms of computation time. The improvement of the dynamic performance of the system is demonstrated by simulation studies for a variety of operating conditions and disturbances     

Tuning of power system stabilizers using an artificial neuralnetwork

A new approach using an artificial neural network is proposed to adapt power system stabilizer (PSS) parameters in real time. A pair of online measurements i.e., generator real-power output and power factor which are representative of the generator's operating condition, are chosen as the input signals to the neural net. The outputs of the neural net are the desired PSS parameters. The neural net, once trained by a set of input-output patterns in the training set, can yield proper PSS parameters under any generator loading condition. Digital simulations of a synchronous machine subject to a major disturbance of a three-phase fault under different operating conditions are performed to demonstrate the effectiveness of the proposed neural network     

励磁调节对水力发电机组过渡过程的影响分析

为深入研究励磁调节对水力发电机组过渡过程的影响,在Matlab/Simulink平台上,采用面向对象的程序设计技术,建立了包括水力、机械及电气部分的联合计算模型,研究了机组并入不同容量的电力系统时,励磁调节和电力系统稳定器(PSS)对机组频率波动特性和水力过渡过程的影响。计算结果表明,在有限容量的电力系统中,机组安装励磁调节和PSS除了能有效地对无功功率和电压进行调节之外,对机组频率波动也有良好的改善作用,对调压室水位波动有一定的抑制作用,有利于提高电能质量。     

Robust controller design for generator excitation systems

This paper deals with the design and evaluation of a robust controller for generator excitation systems to improve the steady-state and transient stabilities. The unique approach used is to first treat the nonlinear characteristics of the system as model uncertainties, and then to take into account such uncertainties at the controller design stage using a robust control methodology. The performance of the controller has been evaluated extensively by nonlinear simulation. It is concluded that the robust controller provides better damping to the oscillatory modes of the system than the conventional PSS in all the cases studied     

Integrated fuzzy logic generator controller for stabilityenhancement

An integrated fuzzy logic controller is proposed in this paper for the generator excitation and speed governing control. The proposed controller has three control loops: the first one is the voltage control loop which has the function of automatic voltage regulator (AVR), the second one is the damping control loop which has the function of power system stabilizer (PSS), and the last one is the speed governing control loop which has the function of governor (GOV). A simple fuzzy logic control scheme is applied to all these three loops. The control scheme is simple enough so as not to require heavy computation for the controller, therefore, its real time application is feasible. The effectiveness is demonstrated through nonlinear simulations using a one machine infinite bus system. Comparison studies are also performed to show the advantages of the proposed controller with conventional excitation and speed governing control systems     

Modelling and ride‐through capability of variable speed wind turbines with permanent magnet generators

A model for a variable speed wind turbine with a permanent magnet, multipole, synchronous generator is developed and implemented in the simulation tool PSS/E as a user‐written model. The model contains representations of the permanent magnet generator, the frequency converter system with control, the aerodynamic rotor and a lumped mass representation of the shaft system. This model complexity is needed for investigations of the short‐term voltage stability and ride‐through capability of such wind turbines. Ride‐through capability is a major issue and, for the given concept, can be achieved by applying blocking and restart sequences to the frequency converter at the voltage drop in the power grid. Copyright © 2005 John Wiley & Sons, Ltd.     

用于励磁控制器参数优化的发电机外部动态等值系统参数辨识

针对静态等值系统不能完全反映近端机组对被研究发电机的动态影响,提出了一种动态等值系统,即将远方复杂的大电网和近端同母线机组分别等值为无穷大母线和动态机组,通过Matlab编程搭建了动态等值系统,提出了穷举辨识算法,仅根据研究发电机机端数据即可辨识出动态等值系统的参数,并通过大电网数据辨识及PSS参数优化验证了动态等值系统参数辨识的有效性。     

Influence of Tower Shadow and Wind Turbulence on the Performance of Power System Stabilizers for DFIG-Based Wind Farms

The aim of the paper is to demonstrate the way in which mechanical power variations, due to tower shadow and wind turbulence, influence control performance of power system stabilizer (PSS) loops for doubly-fed induction generators (DFIGs). The PSS auxiliary loops are applied on a specific DFIG control scheme, the flux magnitude and angle controller (FMAC). However, since the PSS signal is applied at the output of the basic controller, the PSS performance characteristics displayed are deemed typical for DFIG control schemes in general. The relative capabilities of PSS controllers based on stator power, rotor speed, and network frequency, when the DFIG turbine is subjected to aerodynamic torque variations, are investigated via simulation studies. A two-generator aggregate model of a wind farm is introduced, which enables the influence of tower shadow and wind turbulence on both an individual turbine and on the overall wind farm itself to be assessed.     

Reduced models of doubly fed induction generator system for wind turbine simulations

This article compares three reduced models with a detailed model of a doubly fed induction generator system for wind turbine applications. The comparisons are based on simulations only. The main idea is to provide reduced generator models which are appropriate to simulate normal wind turbine operation in aeroelastic wind turbine models, e.g. for control system design or structural design of the wind turbine. The electrical behaviour such as grid influence will therefore not be considered. The work presented in this article shows that with an ideal, undisturbed grid the dynamics of the doubly fed induction generator system is very well represented by the dynamics due to the generator inertia and the generator control system, whereas the electromagnetic characteristics of the generator can be represented by the steady state relations. The parameters for the proposed models are derived from parameters typically available from the generator data sheet and from the controller settings. Thus the models are simple to apply in any case where the generator data sheet is available. Copyright © 2005 John Wiley & Sons, Ltd.     

An adaptive power system stabilizer based on recurrent neuralnetworks

Application of recurrent, neural networks in the design of an adaptive power system stabilizer (PSS) is presented in this paper. The architecture of the proposed adaptive PSS has two recurrent neural networks. One functions as a tracker to learn the dynamic characteristics of the power plant and the second one functions as a controller to damp the oscillations caused by the disturbances. In the proposed approach, the weights of the neural networks are updated on-line. Therefore, any new information available during actual control of the plant is considered. Simulation studies show that the artificial neural network (ANN) based PSS can provide very good damping over a wide range of operating conditions     

A neural network-based power system stabilizer using power flowcharacteristics

A neural network-based power system stabilizer (neuro-PSS) is designed for a generator connected to a multi-machine power system utilizing the nonlinear power flow dynamics. The use of power flow dynamics provides a PSS for a wide range of operation with reduced size neural networks. The neuro-PSS consists of two neural networks: neuro-identifier and neuro-controller. The low-frequency oscillation is modeled by the neuro-identifier using the power flow dynamics, then a generalized backpropagation-through-time (GBTT) algorithm is developed to train the neuro-controller. The simulation results show that the neuro-PSS designed in this paper performs well with good damping in a wide operation range compared with the conventional PSS     

An input‐output linearization–based control strategy for wind energy conversion system to enhance stability

This paper proposes a novel control strategy for doubly fed induction generator (DFIG)‐based wind energy conversion system to investigate the potential of enhancing the stability of wind energy transmission system, a synchronous generator weakly integrated to a power system with a DFIG‐based wind farm. The proposed approach uses state feedback to exactly linearize the nonlinear wind energy transmission system from control actions (active power and reactive power control order of DFIG) to selected outputs (power angle and voltage behind transient resistance of synchronous generator) at first. Then, on account of the linearized subsystem, the stability enhancement controller is designed based on linear quadratic regulator algorithm to contribute adequate damping characteristics to oscillations of the synchronous generator system under various operation points. The proposed control strategy successfully deals with the nonlinear behaviors exist from the inputs to outputs and improve the robustness with respect to the variation of system operation points. Furthermore, not only the rotor angle stability but also the voltage stability is enhanced by using the proposed control strategy. The simulation results carried on the studied system verify the effectiveness of the proposed control strategy of wind energy conversion system for system stability enhancement and the robustness against various system operation points.     

风气互补发电系统与电力系统相互影响的研究

为研究风气互补发电系统对电网的影响,首先搭建了由风电机组、燃气轮机、电网线路、静止无功补偿器、电力系统稳定器和大型水力发电机组成的仿真系统,并对该系统的负载侧和电网线路中部节点进行了稳定性分析。仿真结果表明,电网在加载了风气互补系统后运行能保持稳定,并能在发生短时故障后恢复到原来状态。该文为进一步研究风气互补系统与电网的相互影响提供了良好的模型基础。     

Theory and method for selection of power system stabilizer location

An approach for the selection of best PSS (power system stabilizer) locations in multimachine power systems is proposed. Study shows that the right-eigenvector measures the activity of state variables and the left-eigenvector measures the control effect of control signals. Based on the right and left eigenvector, the concept of sensitivity of PSS effect (SPE) is presented and used to identify the best PSS locations. The method is used to identify the best PSS location is a 13-machine system to increase the damping of an interarea mode. The time-domain simulation results confirm that the prediction of the best PSS location by the SPE method is correct and accurate