Recurrent neuro fuzzi controller power system stabilizer

Power system stabilizers (PSS) have been widely used to damp low frequency electromechanical oscillations which occur in power systems due to disturbances. If no adequate damping is available, the oscillation can increase and cause system separation. Power system stabilizers (PSS) are installed in power system generator to help the damping of power system oscillations. There are many approaches to enhance damping while extending the power stability limit. To improve power system stabilizer (PSS) design problem include optimal control ,adaptive and self-tuning control, PID control, robust control, variable structure control and intelligent control. In this paper the power stabilizer is based on Recurrent Neuro-fuzzy Inference System (RNFIS) design controller. In order to test the robustness of the proposed design procedure of the (RNFIS), simulations will be carried out for the three-phase to ground fault and 1- phase fault at the middle of one of the transmission line. After these simulations, we will compare the result between a lead-lag and recurrent neuro-fuzzy controllers to see their difference in disturbances. The optimal solutions will be compared where the expected result will show that the oscillations in time response of the machine speed and the rotor angle is damped more effectively when the recurrent neuro-fuzzy controller and applied to the system

Robust fuzzy PSS design using ABC

This paper presents an Artificial Bee Colony (ABC) algorithm to tune optimal rule-base of a Fuzzy Power System Stabilizer (FPSS) which leads to damp low frequency oscillation following disturbances in power systems. Thus, extraction of an appropriate set of rules or selection of an optimal set of rules from the set of possible rules is an important and essential step toward the design of any successful fuzzy logic controller. Consequently, in this paper, an ABC based rule generation method is proposed for automated fuzzy PSS design to improve power system stability and reduce the design effort. The effectiveness of the proposed method is demonstrated on a 3-machine 9-bus standard power system in comparison with the Genetic Algorithm based tuned FPSS under different loading condition through ITAE performance indices

Comparative Studies Of Fuzzy Logic Base Power System Stabilizers In Enhancing Dynamic Stability Of A Generator Connected To Infinite Bus

Power system stabilizers (PSS) are added to excitation system to enhance the damping during low frequency oscillations. This paper presents a study of fuzzy logic power system stabilizer for stability enhancement of a single machine connected to infinite bus (SMIB) power system. Recently fuzzy logic as a novel robust control design method has shown promising results. The emphasis in fuzzy control design center is around uncertainties in the system parameters and operating conditions. Fuzzy logic controller (FLC) has been suggested as a possible solution to overcome this problem, thereby using linguist information and avoiding a complex system mathematical model, while giving good performance under different operating conditions. The proposed approach is found to have stable convergence characteristics and resulted in good voltage regulation and damping characteristics. The stabilizing signals were computed using the fuzzy membership functions with variations of angular speed and acceleration as the inputs. The simulations were tested under different operating conditions, with different membership functions using MATLAB /SIMULINK. The simulation results are quite encouraging and satisfactory

Indirect adaptive fuzzy finite time synergetic control for power systems

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults. Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems. Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller

Designing power system stabilizer for multimachine power system using neuro-fuzzy algorithm

This paper describes a design procedure for a fuzzy logic based power system stabilizer (FLPSS) and adaptive neuro-fuzzy inference system (ANFIS) and investigates their robustness for a multi-machine power system. Speed deviation of a machine and its derivative are chosen as the input signals to the FLPSS. A four-machine and a two-area power system is used as the case study. Computer simulations for the test system subjected to transient disturbances i.e. a three phase fault, were carried out and the results showed that the proposed controller is able to prove its effectiveness and improve the system damping when compared to a conventional lead-lag based power system stabilizer controller

A survey of fuzzy control for stabilized platforms

This paper focusses on the application of fuzzy control techniques (fuzzy type-1 and type-2) and their hybrid forms (Hybrid adaptive fuzzy controller and fuzzy-PID controller) in the area of stabilized platforms. It represents an attempt to cover the basic principles and concepts of fuzzy control in stabilization and position control, with an outline of a number of recent applications used in advanced control of stabilized platform. Overall, in this survey we will make some comparisons with the classical control techniques such us PID control to demonstrate the advantages and disadvantages of the application of fuzzy control techniques

Chaotic multi-objective optimization based design of fractional order PI{\lambda}D{\mu} controller in AVR system

In this paper, a fractional order (FO) PI{\lambda}D\mu controller is designed to take care of various contradictory objective functions for an Automatic Voltage Regulator (AVR) system. An improved evolutionary Non-dominated Sorting Genetic Algorithm II (NSGA II), which is augmented with a chaotic map for greater effectiveness, is used for the multi-objective optimization problem. The Pareto fronts showing the trade-off between different design criteria are obtained for the PI{\lambda}D\mu and PID controller. A comparative analysis is done with respect to the standard PID controller to demonstrate the merits and demerits of the fractional order PI{\lambda}D\mu controller.Comment: 30 pages, 14 figure