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.     

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。     

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.     

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.     

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.     

Coordinated design of probabilistic PSS and SVC damping controllers

This paper presents an application of probabilistic theory to the coordinated design of power system stabilizers (PSSs) and FACTS controllers, taking static VAr system (SVC) as an example. The aim is to enhance the damping of multi electro-mechanical modes in a multimachine system over a large and pre-specified set of operating conditions. In this work, conventional eigenvalue analysis is extended to the probabilistic environment in which the statistical nature of eigenvalues corresponding to different operating conditions is described by their expectations and variances. Probabilistic sensitivity indices (PSIs) are used for robust damping controller site selection and for optimization objective functions. A probabilistic eigenvalue-based objective function is employed for coordinated design of PSS and SVC controller parameters. The effectiveness of the proposed controllers is demonstrated on an 8-machine system.     

基于分散控制理论的多机系统低频振荡抑制

常规的电力系统低频振荡抑制措施是在发电机励磁系统中加装电力系统稳定器(PSS),然而它在多机电力系统中的应用并没有充分的理论研究.将大系统分散控制原理应用于多机电力系统低频振荡抑制问题,只要分散阻尼控制器(DDC)的阶数足够高,分散闭环控制系统的低频振荡模态总可以在复平面内任意配置.分析了PSS与DDC的关系,论证了PSS是DDC的一种特殊形式,因而从理论上说明了DDC比PSS优越.将DDC的优化配置表示为一个带不等式约束的非光滑优化问题并用遗传算法求解.以新英格兰测试系统和我国西北电网为算例的计算结果表明,在发电机励磁系统中加装DDC是一种有效的低频振荡抑制新措施.     

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.     

Optimal Power System Stabilizers design via Cuckoo Search algorithm

Cuckoo Search (CS) algorithm is introduced in this paper for optimal Power System Stabilizers (PSSs) design in a multimachine power system. The PSSs parameter tuning problem is formulated as an optimization problem which is solved by CS Algorithm. An eigenvalues based objective function involving the damping ratio, and the damping factor of the lightly damped electromechanical modes is considered for the PSSs design problem. The performance of the proposed CS based PSSs (CSPSS) has been compared with Genetic Algorithm (GA) based PSSs (GAPSS) and the Conventional PSSs (CPSS) under different operating conditions and disturbances. The results of the developed CSPSS are verified through time domain analysis, eigenvalues and performance indices. Also, the effectiveness of the proposed algorithm in providing good damping characteristics is confirmed.     

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。     

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.     

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。     

Effective damping of local low frequency oscillations in power systems integrated with bulk PV generation

High penetration of renewable sources into conventional power systems results in reduction of system inertia and noticeable low-frequency oscillations (LFOs) in the rotor speed of synchronous generators. In this paper, we propose effective damping of LFOs by incorporating a supplementary damping controller with a photovoltaic (PV) generating station, where the parameters of this controller are coordinated optimally with those of a power system stabilizer (PSS). The proposed method is applied to damp local electromechanical modes by studying a system comprising a synchronous generator and a PV station connected to an infinite bus. The PV station is modeled following the instructions of the Western Electricity Coordinating Council. The problem is modeled as an optimization problem, where the damping ratio of the electromechanical modes is designed as the objective function. Constraints including upper and lower limits of decision parameters and damping ratio of other modes are considered by imposing penalties on the objective function. Different optimization algorithms are used to pursue the optimal design, such as political, improved gray wolves and equilibrium optimizers. The results validate the effectiveness of the proposed controller with PSS in damping local modes of oscillations.     

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.     

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.     

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.     

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     

多机系统调速侧电力系统稳定器GPSS的设计

低频振荡是一种不利于电力系统安全和稳定运行的现象,而电力系统稳定器(PSS)可以有效抑制低频振荡。由于励磁系统和电力系统运行方式及工况之间的密切关系,致使电力系统中PSS的协调设计和安装地点的选择成了PSS能否用于电力系统的关键。作者设计了一种调速侧电力系统稳定器,其设计原理和传统的PSS一样简单,且具有较好的鲁棒性,同时还具有多机解耦特性,给本机带来阻尼的同时不会给其它机组带来负阻尼,避免了参数协调和安装地点的选择。最后利用算例仿真验证了调速侧电力系统稳定器不仅可以抑制低频振荡,还可以提高电力系统暂态稳定性。     

基于Prony方法的大型互联电网PSS参数优化设计

提出了一种完全基于仿真曲线Prony分析的电力系统稳定器(PSS)参数优化设计方法.该方法通过对仿真曲线的Prony分析辨识系统的弱阻尼区域振荡模式信息,以提高区域振荡模式下的阻尼为优化目标,在限定的参数空间中进行PSS参数优化设计.采用单纯形法对PSS参数进行优化,以Prony方法辨识的PSS参数作为单纯形区域的初始中心点可克服算法的收敛性问题.云南电网发电机组实际PSS参数优化设计的结果表明:在云南电网多种运行方式下,均可很好地抑制系统的区域振荡,验证了PSS参数优化设计方法的有效性和鲁棒性.所提出的基于Prony算法的PSS参数优化方法优于传统PSS设计方法,适用于大型互联电网发电机组的PSS设计.     

Power system feedback stabilizer design via optimalsubeigenstructure assignment

Power system stabilizer (PSS) design is addressed using an optimal reduced order model whose state variables are torque angles and speeds. System damping can be improved by using eigenvalue assignment, and the coordination of stabilizers can be achieved through eigenvector assignment by maintaining system mode shapes. The proportional-integral PSSs are derived by the optimal reduced order model. The effectiveness of the stabilizer is evaluated. By using the output feedback only, the result of eigenstructure assignment is more stable and much better than the assignment method based on the whole system model. Examples, a single-machine to infinite bus system and a multimachine system, are given to illustrate the advantages and effectiveness of the proposed approach. Results based on the whole system model are included for comparative analyses