Results of a study on location and tuning of power system stabilizers

In this paper a procedure to locate power system stabilizers (PSS) is proposed. Different linear techniques are applied to this task, such as participation, balanced realizations, controllability, observability and residues. A method of constrained nonlinear optimization is employed for tuning of the PSS parameters. The proposed technique is applied to the location and tuning of PSS in a model of the Mexican Interconnected System (MIS), possessing 140 buses and 46 machines.     

基于双层规划的非线性鲁棒电力系统稳定器参数整定方法

使用先进的励磁控制技术是改善电力系统稳定性和动态品质的有效手段。采用反馈线性化和鲁棒控制理论设计的非线性鲁棒电力系统稳定器(NR-PSS)是一种先进的励磁控制装置。在深入研究电力系统稳定器(PSS)参数整定原理和NR-PSS现有参数整定方法的基础上,提出了一种基于双层规划的NR-PSS线性部分参数整定方法,以满足阻尼频带宽和控制代价低两方面要求。通过等价非线性规划可求出最优参数。仿真结果表明,应用所提出方法设定的参数可以改善NRPSS的控制效果。     

Power System Control With an Embedded Neural Network in Hybrid System Modeling

Output limits of the power system stabilizer (PSS) can improve the system damping performance immediately following a large disturbance. Due to nonsmooth nonlinearities arising from the saturation limits, these values cannot be determined by the conventional tuning methods based on linear analysis. Only ad hoc tuning procedures can been used. A feedforward neural network (with a structure of multilayer perceptron neural network) is applied to identify the dynamics of an objective function formed by the states and, thereafter, to compute the gradients required in the nonlinear parameter optimization. Moreover, its derivative information is used to replace that obtained from the trajectory sensitivities based on the hybrid system model with the differential-algebraic-impulsive-switched structure. The optimal output limits of the PSS tuned by the proposed method are evaluated by time-domain simulation in both a single-machine infinite bus system and a multimachine power system.      

PSS与VSC-HVDC附加阻尼控制器参数协调优化设计

将含参数约束的线性优化方法应用于交\直流混合系统的电力系统稳定器和基于电压源型换流器的高压直流输电系统附加阻尼控制器的参数协调优化中。该算法考虑了不同阻尼控制方式间的相互影响和作用,在迭代过程中通过修正优化可行域区间,使系统低频振荡模式对应的特征根最终移动到复平面上期望区域内。系统的特征值分析和时域仿真结果验证了上述方法的有效性和实用性。     

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     

基于微粒群优化算法的最优电力系统稳定器设计

传统电力系统稳定器的性能受其参数影响很大,为提高电力系统机电暂态模型的阻尼,文中提出了一种优化电力系统稳定器参数的新方法。该方法以两个特征值基目标函数为基础,采用改进的微粒群优化技术对电力系统稳定器进行参数优化。特征值分析和非线性仿真结果表明,经过参数优化的电力系统稳定器能有效抑制本地和区域间振荡,提高系统的鲁棒性。     

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.     

Knowledge domain states mapping concept for controller tuning in an interconnected power network

This paper presents novel power system stabilizers (PSS) tuning approach with particles swarm optimization (PSO) driven knowledge domain states mapping for multi area power system. Tuning of PSS parameters has been done by PSO technique offline at different operating conditions as load dynamics change. The objective function for PSS parameters tuning is integral time multiplied by absolute error (ITAE). The sets of tuned parameters at different operating conditions thus obtained are termed as knowledge domain. The process is viewed as knowledge domain mapping. The dynamical system response has been linked with states, and if there is any violation from desired limits, control action is initiated and thus retuned control parameters obtained straight away from the respective knowledge domain helps to provide quick response and precise damping of signals of interest. Proposed concept also demonstrates that if one controller (PSS) fails to stabilize the system at certain operating condition then another controller (UPFC) connected in the system acts as supplementary controller in automation which assists PSS functioning and thus entire system operation improves by way of modulating the signal dynamics at interface points which quickly damps oscillations. The system study has been performed on a sample six area power systems comprising of UPFC connected between area two and three and PSS to all areas. The proposed concept demonstrates auto tuning of PSS for quick oscillation damping as the operating conditions change and also under situations of PSS failure due to relatively larger perturbation, UPFC acts as supplementary controller by assisting the entire system PSS to recover ensuring stability.     

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.     

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 PSSs and SVC via bacteria foraging optimization algorithm in a multimachine power system

This paper develops a novel algorithm for simultaneous coordinated designing of power system stabilizers (PSSs) and static var compensator (SVC) in a multimachine power system. The coordinated design problem of PSS and SVC over a wide range of loading conditions is formulated as an optimization problem. The Bacterial Foraging Optimization Algorithm (BFOA) is employed to search for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is improved. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the bacterial foraging based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BFOA (BFPSS) and optimized SVC controller based on BFOA (BFSVC). Moreover, a statistical T test is performed to ensure the effectiveness of coordinated controller versus uncoordinated one.     

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.     

Coordinated Synthesis of Multimachine Power System Stabilizer Using an Efficient Decentralized Modal Control (DMC) Algorithm

This paper presents a new method for simultaneously selecting the power system stabilizer (PSS) parameters in multimachine power systems. Design of local output feedback power system stabilizer using local signal of the generator (e.g. speed or power) is formulated as a decentralized modal control (DMC) problem. Exact model reduction based on modal control theory is proposed to make the determination of PSS parameters highly efficient. Results obtained from the coordinated tuning of the parameters of three power system stabilizers equipped on a multimachine power system show that exact assignment of the eigenvalues associated with the poorly damped electromechanical modes can be achieved in a very efficient manner.     

Power system stabilization control based on the wide area phasor measurement

This paper presents a method of tuning power system stabilizers (PSS) in order to damp low‐frequency oscillations in a multimachine power system based on wide area phasor measurements. The authors have developed a method for detecting interarea low‐frequency modes from measured small oscillations associated with load fluctuations by approximating the oscillations as a coupled vibration model. In this paper, the coupled vibration model is extended to include the effect of PSS. PSS are tuned directly by using the extended model, since the model includes parameters of PSS. The advantage of this method is that steady state phasor fluctuations are available for tuning PSS and assessing the effect of the tuning control. That is, a large disturbance like a line fault is not necessary since the stability of major modes can be investigated directly by using eigenvalues of the extended model. The identification process does not require information on the input to the system for perturbation. Some numerical analyses demonstrate the effectiveness of the method by using phasor dynamical data obtained by a power system simulation package. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 163(1): 16–24, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20640     

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.     

永磁同步发电机与Boost斩波型变换器非线性速度控制

直驱式永磁同步风电系统电机侧变换器的一种常见拓扑结构为二极管整流桥后接Boost斩波电路。此结构具有较强的非线性,采用普通PI控制器很难使系统在正常运行范围内保持较好的动态性能。针对其非线性特性,分区间建立了发电机与变换器整体非线性数学模型,在单区间内采用输入-输出反馈线性化方法将非线性系统转换为线性系统,在此基础上设计了转速最优控制器。该设计方法数学转换过程较为简单,参数整定方法较为成熟,且不同区间内线性控制器的参数相同。通过一套3kVA的实验系统,验证了该方法能明显改善系统动态性能,对此类风电系统电机侧变换器控制策略的设计具有一定的参考价值。     

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.     

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.     

Comparative seeker and bio-inspired fuzzy logic controllers for power system stabilizers

Seeker optimization algorithm (SOA) is a new heuristic population-based search algorithm. In this paper, SOA is utilized to tune the parameters of both single-input and dual-input power system stabilizers (PSSs). In SOA, the act of human searching capability and understandings are exploited for the purpose of optimization. In SOA-based optimization, the search direction is based on empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. Conventional PSS (CPSS) and the three dual-input IEEE PSSs (namely PSS2B, PSS3B and PSS4B) are optimally tuned to obtain the optimal transient performances. From simulation study it is revealed that the transient performance of the dual-input PSS is better than the single-input PSS. It is further explored that among the dual-input PSSs, PSS3B offers the best optimal transient performance. While comparing the SOA with recently reported optimization algorithms like bacteria foraging optimization (BFO) and genetic algorithm (GA), it is revealed that the SOA is more effective than either BFO or GA in finding the optimal transient performance. 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 parameters.     

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。