Power System Stability Control Research Articles

Simultaneous Coordinated Tuning of PSS and FACTS Damping Controllers in Large Power Systems

This work deals with the simultaneous coordinated tuning of the flexible AC transmission systems (FACTS) power oscillation damping controller and the conventional power system stabilizer (PSS) controllers in multi-machine power systems. Using the linearized system model and the parameter-constrained nonlinear optimization algorithm, interactions among FACTS controller and PSS controllers are considered. Furthermore, the parameters of the damping controllers are optimized simultaneously. Simulation results of multi-machine power system validate the efficiency of this approach. The proposed method is effective for the tuning of multi-controllers in large power systems.

Transient stability control of multimachine power systems using flywheel energy injection

Owing to advances in many technologies, the high-speed flywheel energy storage system (FESS), flywheel battery, has become a viable alternative to electrochemical batteries and attracted much research attention in recent years. A self-organising fuzzy neural network controller is presented for FESS to improve transient stability and increase transfer capability of power systems. The main difference from a traditional control approach lies in the model-free description of the control system and parallel computing capability. Simulation results from the Taiwan power system (Taipower) show that FESS with the proposed controller has produced significant improvement in power system performance.

An intelligent based LQR controller design to power system stabilization

This paper presents an intelligent model, named as free model, approach for a closed-loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. Also, it is shown that the free model is controllable, observable, and robust to disturbance. In this paper, the feasibility of the proposed method is demonstrated in a three-machine nine-bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS and LQR controller based on the ARMA-model. The free-model based (FMB) PSS is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.

Comparison of PSS, SVC, and STATCOM controllers for damping power system oscillations

This paper discusses and compares different control techniques for damping undesirable interarea oscillation in power systems by means of power system stabilizers (PSS), static VAr compensators (SVCs), and shunt static synchronous compensators (STATCOMs). The oscillation problem is analyzed from the point of view of Hopf bifurcations, an extended eigenanalysis to study different controllers, their locations, and the use of various control signals for the effective damping of these oscillations. The comparisons are based on the results obtained for the IEEE 50-machine, 145-bus test system, which is a benchmark for stability analysis.

Systematic method for the design of a full-scale fuzzy PID controller for SVC to control power system stability

A systematic method was introduced to design a full-scale fuzzy PID controller for power system stability control. The proposed controller uses the incremental form of a conventional PID controller as its underlying structure. To show the effectiveness of this method a form of full-scale fuzzy PID controller is designed. The rule-generated function is used to generate the rule base. The parameters of a conventional PID controller, which can be achieved by several well-known methods in control theory such as Ziegler-Nichols, Cohen-Cool and the genetic algorithm, make it possible to simplify the design process, as is desirable from an industrial point of view. One advantage of the new full-scale fuzzy PID controller is that it has the same structure and simplicity of its conventional counterparts but with more effectiveness and robustness. In order to illustrate the effectiveness of this controller a SVC-based stabiliser is designed using the proposed fuzzy PID controller.

Dynamic stability improvement via coordination of static var compensator and power system stabilizer control actions

Power system controllers such as the static var compensators and the power system stabilizers are receiving a wide interest since many technical studies have proven their effects on damping system oscillations and stability enhancement. This paper is mainly concerned with coordinating the control actions of static var compensators and power system stabilizers to achieve improved dynamic performance of the power system using the newly developed concept of ‘domains of influence’. Novel sensitivity-based algorithms are presented for the purpose of effectively identifying the domains of influence of various control parameters on critical dynamic system modes. Applications to the Saudi Consolidated Electric Company (SCECO) power system show that significant improvement in power network stability can be achieved via coordinating the control actions of both static var compensator and power system stabilizer instead of using them individually in an uncoordinated manner.

New Lyapunov function for transient stability analysis and control of power systems with excitation control

Abstract In this paper, a direct method of transient stability analysis for power systems with excitation control is presented using Hamiltonian system theory. A modified transient energy function is regarded as Hamiltonian function which is used to formulate a type of standard Hamiltonian equation. A new Lyapunov function is then constructed, and based on it, a novel excitation control strategy is obtained directly from a nonlinear power system. Numerical results demonstrate the effectiveness of the proposed approach.

Coordinated synthesis of PSS parameters in multi-machine power systems using the method of inequalities applied to genetic algorithms

A new method has been proposed based on the method of inequalities for the coordinated synthesis of power system stabilizer (PSS) parameters in multi-machine power systems in order to enhance overall system small signal stability. Since the coordination and control of PSSs is a Pareto-optimization problem, a comprehensive list of design objectives has been presented in terms of a set of inequalities. To solve these inequalities, genetic algorithms have been applied to determine the PSS parameters.

00/01386 Modelling of TCSC dynamics for control and analysis of power system stability

00/01386 Modelling of TCSC dynamics for control and analysis of power system stability

Coordinated design of under-excitation limiters and power system stabilizers

Summary form only given as follows. The inherent dynamical relationship between the under-excitation limiter (UEL) and the power system stabilizer (PSS) control loops in synchronous generators is studied using the frequency response technique. While the stabilizers are effective in introducing electromechanical damping torque components into the generators, it is shown that the limiters should be designed to effect a much slower response characteristics as their main function is to prevent excessive stator end-core heating. The analysis also shows that a reduction in the values of the slope of the boundary curves, which prescribe the operating region of the limiters, is accompanied by a decrease in the damping level of the closed-loop excitation control systems. A method which decouples the design procedure of the UEL from that of the PSS is then proposed.

Modelling of TCSC dynamics for control and analysis of power system stability

A Thyristor Controlled Series Compensator (TCSC) exhibits great nonlinearity and performs in a complex dynamic process. The aim of this paper is to propose a method that can accurately simulate this process when carrying out power system stability analysis, so that the impact of TCSC on power system stability can be more reasonably evaluated. A method that can incorporate the analysis of the electromagnetic transient process of TCSC into the power system stability analysis is described. Simulation studies using different modelling methods of TCSC are presented. The simulation results show the advantages of using the utilisation of the modelling method in power system control and stability analysis.

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.

Applications of fuzzy logic in power systems. Part 3: Example applications

The first tutorial of this three-part series (see ibid., p.219, October 1997) gave a general introduction to fuzzy logic and the second one (see ibid., p.185, August 1998) examined comparison and integration with other techniques. This third and last tutorial discusses the general issues in applying fuzzy logic in power systems and presents some example applications including power system stability control, power system optimisation fuzzy programming, fuzzy pattern recognition for power system stability assessment, and fuzzy neural network approach to transmission line fault location.

Annotated bibliography on power system stability controls: 1986-1994

This bibliography is a subset of a more complete version which can be obtained via email using FTP. This bibliography was prepared by the IEEE working group on Special Stability Controls as an expanded continuation of an earlier bibliography (entry [87.8]). The entries here are grouped by year with a grouping by subject located in the appendix. The emphasis of the selections presented here is on applied controls and field experience.

Power System Stability Control with Robust Multi-Loop Automatic Voltage Regulators

The primary voltage regulation for synchronous generator control is addressed in the context of modern interconnected power system problems. Voltage regulation in the synchronous generators is maintained by the Automatic Voltage Regulators (AVR). A brief review of the role of AVR in the overall power system problem is given. The use of a multi-loop AVR control structure involving advanced optimal control theories is also presented to improve the performance of generator terminal voltage control in primary regulation and system stability

可変制御則と可変ゲインを有するファジー理論を用いたSVCによる電力系統の安定化制御

可変制御則と可変ゲインを有するファジー理論を用いたSVCによる電力系統の安定化制御

On-line decoupled identification of transient and sub-transient generator parameters

This paper describes a method of identifying the transient parameters of a generator under normal operating conditions using on-line measurements of the generator current output or the voltage of the bus to which the generator is connected through a transformer. A decoupled method is developed to identify the parameters of the generator in any power system and under any operating conditions. The method is based on Park's two-axis model, and the parameters to be estimated have definite physical meanings, which are suitable for stability analysis and control of power systems. The continuous corrected extended Kalman filter is used as the identification algorithm, so the model does not need to be changed into a discrete form. The identification converges to within 1% of the actual parameter values in most power system structures. >

147 Adaptive and supplementary intelligent control of power system stabilizers

147 Adaptive and supplementary intelligent control of power system stabilizers

Stabilization of power systems by governor-turbine control

In this paper, the possibility of applying a Power System Stabilizer (PSS) via the governor-turbine system of a generating unit is studied for both single-machine and multimachine power systems. The results of analysis and simulation show that the conventional exciter-based PSS can be used in conjunction with the modern high-speed governor to suppress low-frequency oscillations in power systems. This arrangement of stabilizer possesses better robustness to the changes of power system operating conditions. Furthermore, in the environment of a multimachine power system, the control of PSS on the governor of every generator can be locally synthesized to stabilize the whole system, PSS design becomes much easier and simpler.

Adaptive and Supplementary Intelligent Control of Power System Stabilizers

The presentation is devoted to the methodology of design of an adaptive control algorithm combined with knowledge-based rules to improve the robustness of power-voltage control under variable load conditions and with a variable number of turbogenerators, which are connected to the tie line system. This presentation is centered around a control-research project in the Netherlands. The power-generator system is modeled and field tests are carried out for verification. The purpose of the research project is to design and to implement an adaptive algorithm, based upon the PSS-approach, combined with observer filters. Because of the fact that already a power system consisting of a cluster of generators with variable load conditions, operating in an isolated area, has several well-known boundary conditions, related to different operating points, the MRAC adaptive control algorithm has to be supervised by a set of rules, governed by a knowledge base. This expert-oriented knowledge is based upon the normal "intelligent" control actions as they are carried out by the unit operators. These rules are non-analytic and can be described by fuzzy membership functions. In the presentation this fuzzy-set approach, in this project used to improve the adaptive-controlled behaviour, will be explained. Experimental results of the total system will be presented.