Tuning Of Power System Stabilizers Research Articles

Bat Intelligence For Tunning Power System Stabilizer At Barru Power Plant

Changes in load on the power system suddenly, can cause dynamic disruption. This disturbance can not be responded well by the generator, so it can affect the system dynamic stability, such as the occurrence of oscillation speed and rotor angle. Conventional control of excitation and governor, also unable to repair the oscillations, so that additional controllers such as Power System Stabilizer (PSS) are required. In the use of PSS, there are several problems that often arise, namely the correct tuning of PSS parameters. In this research, we proposed a method of smart computing based on bat algorithm, for tuning PSS parameters. From the analysis results can be concluded, the performance performance of generator barru increased with the installation of Power System Stabilizer with optimal PSS parameter, with parameters respectively Kpss = 44.0828, T1 = 0.0284, T2 = 0.0146, T3 = 0.7818, T4 = 1.2816.

Online tuning of power system stabilizer employing genetic programming for stability enhancement

This paper aims to design optimal power system stabilizer (PSS) employing genetic programming (GP) to enhance system stability through damping the low-frequency oscillations out. GP is used to develop model equations for PSS parameters where the inputs are generator terminal voltage, active and reactive powers. The dynamic performance of the proposed technique is validated through the values of statistical performance measures. The mean squared error (MSE) and mean absolute percentage error (MAPE) are quite low whereas the coefficient of determination (R2) is reasonably high for the developed model. In addition, the eigenvalue and minimum damping ratio analysis, as well as time domain simulation, were carried out, which also demonstrate the efficacy of the proposed model.

Development of PSS tuning rules using multi-objective optimization

This paper explores the process of tuning controllers for conditions that better reflect realistic operating conditions, such as input signals of different shapes. In this study, controllers are tuned simultaneously for input signals of different shapes, using the tools of double objective optimization. For this purpose, a novel performance index is proposed to evaluate a system’s ramp response. At the same time, a novel method is proposed for faster and more efficient generation of Pareto plots and Pareto frontiers. The proposed method retrieves the dominant Pareto solutions only, and produces the Pareto frontier directly. The study is applied on the tuning of a Power System Stabilizer (PSS) of a simple power system, at several operating points of the synchronous machine. Finally, a relation between the optimum PSS parameters and the operating points is sought. A linear regression model is used for this purpose, and the tuning rules are tested in an application study. Finally, the optimization technique is applied on a multiple machine system. The results show significant improvement, while maintaining fault resilience.

Optimal design of controllers for power network connected SOFC using of multi-objective PSO

In this paper, we study the concept and forming manner of Solid Oxide Fuel Cell (SOFC) into the electrical system and then, its effect on small signal stability is investigated. The paper illustrates the essential module, mathematical analysis and small signal modeling of the SOFC joined to single machine system. The aim of this study is to reduce power oscillations in the presence of the SOFC with optimal stabilizer. The multi-objective Particle Swarm Optimization (MOPSO) technique has been used for designing a Power System Stabilizer (PSS) in order to improve the performance of the system. Two objective functions are regarded for the design of PSS parameters in order to maximize the damping factor and the damping ratio of the system. To evaluate the efficiency of the proposed optimal stabilizers, four scenarios are considered and then, its results have been analyzed. The proposed PSS tuning technique can be applied to a multi-machine system connected to the SOFC. The efficiency of MOPSO based proposed PSS on the oscillations the system related to SOFC is illustrated by time-domain simulation and also, the comparison of the MOPSO based proposed PSS with the PSS based-single objective method has been prepared.

Tuning of power system stabilizer for small signal stability improvement of interconnected power system

This paper reports a new technique for achieving optimized design for power system stabilizers. In any large scale interconnected systems, disturbances of small magnitudes are very common and low frequency oscillations pose a major problem. Hence small signal stability analysis is very important for analyzing system stability and performance. Power System Stabilizers (PSS) are used in these large interconnected systems for damping out low-frequency oscillations by providing auxiliary control signals to the generator excitation input. In this paper, collective decision optimization (CDO) algorithm, a meta-heuristic approach based on the decision making approach of human beings, has been applied for the optimal design of PSS. PSS parameters are tuned for the objective function, involving eigenvalues and damping ratios of the lightly damped electromechanical modes over a wide range of operating conditions. Also, optimal locations for PSS placement have been derived. Comparative study of the results obtained using CDO with those of grey wolf optimizer (GWO), differential Evolution (DE), Whale Optimization Algorithm (WOA) and crow search algorithm (CSA) methods, established the robustness of the algorithm in designing PSS under different operating conditions.

PSS Based Angle Stability Improvement Using Whale Optimization Approach

This paper introduced a new swarm based optimization technique for tuning Power System Stabilizer (PSS) that attached to a synchronous generator in a single machine infinite bus (SMIB) system. PSS which is installed with Lead-Lag (LL) controller is introduced to elevate the damping capability of the generator in the low frequency mode. For tuning PSS-LL parameters, a new technique called Whale Optimization Algorithm (WOA) is proposed. This method mimics the social behavior of humpback whales which is characterized by their bubble-net hunting strategy in order to enhance the quality of the solution. Based on eigenvalues and damping ratio results, it is confirmed that the proposed technique is more efficient than Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) in improving the angle stability of the system. Comparison between WOA, PSO and EP optimization techniques showed that the proposed computation approach give better solution and faster computation time.

Gradient based hybrid metaheuristics for robust tuning of power system stabilizers

Power System Stabilizers are controllers installed on synchronous generators to damp power system oscillations through the excitation control. These controllers can have either a conventional fixed structure composed by stages of gain and phase compensation or a flexible modern structure composed by three bands that correspond to a specific frequency range (low, intermediate and high frequency) in which each band is composed by two branches that are based on differential filters (with a gain, lead-lag blocks and a hybrid block). Power system stabilizers design is a hard and time consuming task and an alternative for tuning controllers is by using optimization methods. This paper presents three hybrid metaheuristics for the robust and coordinated design of power system stabilizers. The tuning procedure is modeled as an optimization problem which aims at maximizing the damping ratio coefficients in closed-loop operation. Robustness requirement is met by using multiple operating scenarios in the design stage. For solving the optimization problem, three metaheuristics (Gravitational Search Algorithm, Bat Algorithm and Particle Swarm Optimization) are combined with the Steepest Descent Method for local search capability enhancement. The proposed hybrid algorithms are applied to benchmark systems for validation.

Tuning of Velocity PID-Fuzzy Power System Stabilizer by Particle Swarm Optimization

Power system stabilizer (PSS) is used to damping power system oscillation. It will act as supplementary feedback through the generator excitation system, which produce a component of electrical torque in phase with speed variation. Fuzzy controllers are nonlinear. It is more difficult to set the fuzzy controller gains compared to conventional PID controller. This research proposed velocity (PID-FPSS) its gains are tuned by particle swarm optimization technique (PSO). The objective is to damp local-area oscillation that occur following power system small or large disturbances. The effectiveness of the proposed technique is illustrated by applying the velocity PID-FPSS to a single-machine infinite bus power system that is typically used in the literature to test the performance of power system stabilizers. The simulation has been conducted in MATLAB, SIMULINK (R2013a) package. A comparison between the proposed PID-FPSS and a well-designed robust power system stabilizer (RPSS) confirms the superiority of the proposed technique.

Optimal Tuning and Placement of Power System Stabilizers Based Eigenvalue

<p>In this paper, an eigenvalue assignment based Particle Swarm Optimization and Participation Factor for Optimal tuning and placement of power system stabilizers is proposed. The proposed approach presents a two-step methodology to find optimal location and parameters of PSS. The Participation Factor method is computed using the modal analysis toolbox from DIgSILENT, and used to determine the power system stabilizers optimal location. A Particle Swarm Optimization algorithm is written in MATLAB to search the power system stabilizers optimal parameters. Two eigenvalue-based objective functions to ensure a maximum damping of the inter-area modes as well as of the local modes by assigning them in a robust stability area are considered. The performance of the proposed approach is tested and examined on the four-machine two-area power system. Linear modal analysis and non-linear time domain simulations show the robustness of the proposed approach.</p>

Design of PSS and TCSC Damping Controller Using Particle Swarm Optimization

In this paper, we propose a methodology to tune power system stabilizers and thyristor-controlled series capacitor damping controllers simultaneously. The particle swarm optimization algorithm is incorporated into a power system model to tune the parameters of supplementary damping controllers. A test power system of 10 generators, 39 buses and 46 transmission lines is simulated to validate the use of this optimization algorithm. The tuning of supplementary damping controllers using the proposed methodology increases their performance to provide additional damping to low-frequency oscillation modes in the simulated power system. The controller position is determined by the participation factors (power system stabilizers) and the distance between the interest pole and the zero of the open-loop transfer function of the power oscillation damping controller (thyristor-controlled series capacitor-power oscillation damping). The results show the operating efficiency of the power system after using the optimization technique to tune damping parameters, thereby improving power system integrity. The power sensitivity model is used for the simulations presented in this work focusing on the analysis small-signal stability.

Quasi-Steady-State Approach for Analysis of Frequency Oscillations and Damping Controller Design

This paper proposes a quasi-steady-state modeling approach for an approximation of long-term frequency dynamics in power systems. A specific phenomenon of concern is an onset of frequency swings during load/generation imbalance scenarios. The effects of system voltage characteristics, system inertia, and, more importantly, damping controllers are explained and quantified using the described quasi-steady-state models. Application of the methodology to a 14-generator benchmark system demonstrates that described models are suitable for simulation of different disturbance scenarios that can trigger frequency instability. Moreover, linearization of the proposed models can provide convenient means for impact assessment and coordinated design of damping controllers. To demonstrate this, coordinated tuning of multiband power system stabilizers to improve frequency dynamics has been performed and validated through nonlinear simulations using a commercial transient stability software.

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.

An Efficient Enhancement of Rotor Angle Stability using a Hybrid BBO-DE Approach

Power System Stabilizers (PSS) are mainly used as add-on controllers to damp out the low frequency oscillations in the power system stability operation. The tuning of Conventional Power System Stabilizer (CPSS) parameters for a system should be robust such that overall system stability phenomena can be improved. In the recent decades, various population based heuristic algorithms are available to sort out the stability problem in the electric Power System (PS). In this paper presents a new heuristic optimization algorithm named as hybrid Biogeography Based Optimization adapted Differential Evolution (BBO-DE) algorithm for finding the optimal CPSS parameters for Single Machine Infinite Bus (SMIB) and multi-machine system under various operating conditions. The location of the PSS has been carried by participation factor and optimal design of PSS parameters have been obtained by its eigen value approach. Simulations are carried out for the SMIB and three machine nine bus systems. The proposed hybrid BBO-DE technique is robust and highly efficient as compared with its related heuristic algorithms such as Biogeography Based Optimization involved Power System Stabilizer (BBOPSS) and Differential Evolution based Power System Stabilizer (DEPSS). From the simulation results the proposed method enhances the dynamic stability of the system remarkably, especially when the system operating condition changes.

Ubicación y Calibración Óptima de Dispositivos PSS Considerando Criterios Multimáquina y Algoritmos Heurísticos de Optimización

Este trabajo presenta una metodología integral basada en criterios multimáquina de ubicación y sintonización de estabilizadores de sistemas de potencia que ayudará a solucionar el problema de estabilidad oscilatoria de un sistema de prueba, causado por la presencia de modos con amortiguamientos negativos o pobremente amortiguados. Esto se puede lograr con el desarrollo de aplicativos en forma de programa dentro de la herramienta tecnológica de DIgSILENT PowerFactory (scripts DPL). La metodología consiste en realizar el análisis de estabilidad de pequeña señal en el sistema de prueba, obtener los valores propios, vectores propios, y factores de participación que serán utilizados para identificar los posibles lugares de ubicación de PSSs. Posteriormente, un optimizador heurístico será utilizado para identificar los parámetros óptimos de cada PSS con el fi n de amortiguar los modos oscilatorios pobremente amortiguados.

Coordination Tuning PID-PSS and TCSC Based Model of Single Machine Infinite-Bus Using Combination Bacteria Foraging-Particle Swam Optimization Method

The power system requires optimal tuning of automatic voltage regulator (AVR) controller and power system stabilizer (PSS) parameters to get a satisfactory operation. With the increase of transmission line loading over long distances, the use of PSS in some cases may not provide sufficient damping. Application method to get the optimal parameter tuning individual controller causes the AVR to improve voltage regulation and PSS to increase the damping of the system. Simultaneous tuning of AVR, PSS and flexible ac transmission systems (FACTS) damping controller is needed to guarantee a kind closed loop system outcome and to obtain a better voltage regulation and oscillation damping in the system. This paper presents coordination tuning power system stabilizer and a thyristor controlled series compensator (TCSC) using evolutionary computation. The problem of obtaining the optimal controller parameters was formulated as an optimization problem and bacteria foraging-particle swarm optimization with time varying acceleration-differential evolution algorithm applied to solve the optimization problem. The parameters such as proportional gain, integral factor, differential coefficient were selected and optimized by bacteria foraging-particle swarm optimization with time varying acceleration-differential evolution algorithm (BFOPSOTVACDE). The suggested methods applied to tuning PSS and TCSC are compared to another method, as shown in the result. Performance index of systems obtained using suggested method was 0.9053.

Optimal design and tuning of novel fractional order PID power system stabilizer using a new metaheuristic Bat algorithm

Abstract This paper proposes a novel robust power system stabilizer (PSS), based on hybridization of fractional order PID controller (PIλDμ) and PSS for optimal stabilizer (FOPID-PSS) for the first time, using a new metaheuristic optimization Bat algorithm (BA) inspired by the echolocation behavior to improve power system stability. The problem of FOPID-PSS design is transformed as an optimization problem based on performance indices (PI), including Integral Absolute Error (IAE), Integral Squared Error (ISE), Integral of the Time-Weighted Absolute Error (ITAE) and Integral of Time multiplied by the Squared Error (ITSE), where, BA is employed to obtain the optimal stabilizer parameters. In order to examine the robustness of FOPID-PSS, it has been tested on a Single Machine Infinite Bus (SMIB) power system under different disturbances and operating conditions. The performance of the system with FOPID-PSS controller is compared with a PID-PSS and PSS. Further, the simulation results obtained with the proposed BA based FOPID-PSS are compared with those obtained with FireFly algorithm (FFA) based FOPID-PSS. Simulation results show the effectiveness of BA for FOPID-PSS design, and superior robust performance for enhancement power system stability compared to other with different cases.

An Integrated Method for Optimal Placement and Tuning of a Power System Stabilizer Based on Full Controllability Index and Generator Participation

In this paper, an integrated architecture for optimal placement and tuning of power system stabilizers (PSSs) in multimachine systems is proposed in order to improve system stability, damp oscillations, and increase damping of the power system oscillatory modes. The proposed approach provides full-rank optimal conditions for the PSS placement, which provide complete controllability of the system. In addition, this method allows optimal tuning of PSS parameters based on real and imaginary coefficients for damping. Test cases are performed to evaluate the proposed concept, and it has been found that the proposed architecture fully captures system dynamics and provides an efficient way for PSS placement and tuning. The architecture is also verified using a real-time digital simulator on a real experimental test bed and found that the method provides improvement in system stability and reduces low-frequency oscillations in local and inter-area modes of oscillations.

Frequency Response as Tuning of Power System Stabilizer on Rotor Speed Dynamic Stability

Power system stability is the ability of an electric power system unit, for giving operating conditions beginning to recover operating state of equilibrium after being subjected to a physical interference. Power system stability has been recognized as an important problem for safe operation of system unit. Stability of power system is similar to the stability of any dynamic system, and has basic mathematical. Concepts from the mathematics and theoretical stability control are first revised to provide background information related to stability of dynamic system generally and establish a connection theoretical. This paper presents to improve of dynamic power system stability using frequency response as tuning of system stabilizer. It is started by electrical power systems mathematic modeling in state variable equation then set the expertise function of frequency response as tuning of system stabilizer. The plant controlled by function of frequency response is tuned to left half plane (LHP) as system stabilizer which their input from the rotor speed. When the system occur fault, the rotor speed should be synchronized, for this case one electrical controller is needed to make sure the system is stable.

Comparison of Different Techniques For Tuning of Power System Stabilizer

Abstract. The power system is subjected to different types of disturbances such as small changes in the load that affects its efficiency and sometimes leads to unstable system. These disturbances cause oscillations at low frequencies that are undesirable since it affects the amount of transferred power through the transmission lines and leads to external stress to the mechanical shaft. In order to compress low-frequency oscillations, a common solution is use the power system stabilizer (PSS). In this paper different techniques for Tuning of power system stabilizer is proposed. The parameters of the power system stabilizer has been tuned by the three ways, particle swarm optimization (PSO), genetic algorithm (GA) and teaching–learning based optimization (TLBO). The simulation results indicate the performance of the teaching learning based power system stabilizer is much better than the particle swarm optimization power system stabilizer and genetic algorithm based power system stabilizer.

Optimal design of power system stabilizer for power systems including doubly fed induction generator wind turbines

This paper presents an evolutionary algorithm-based approach for optimal design of power system stabilizer (PSS) for multi-machine power systems that include doubly fed induction generator wind turbines. The proposed evolutionary algorithm is an improved particle swarm optimization named chaotic particle swarm optimization with passive congregation (CPSO-PC) applied for finding the optimal settings of PSS parameters. Two different eigenvalue-based objectives are combined as the objective function for the optimization problem of tuning PSS parameters. The first objective function comprises the damping factor of lightly damped electro-mechanical modes and the second one includes the damping ratio of these modes. The effectiveness of the proposed method to design PSS for the power systems including DFIG (Doubly Fed Induction Generator) is extensively demonstrated through eigenvalue analysis and time-domain simulations and also by comparing its simulation results with the results of other heuristic optimization approaches.