INTERVAL TYPE-2 FUZZY LOGIC CONTROLLERS FOR POWER SYSTEM APPLICATIONS

Abstract

In this thesis interval type-2 fuzzy logic controllers are used for power system applications. The motivation for the development of interval type-2 fuzzy logic controllers are from the properties of interval type-2 fuzzy sets. Interval type-2 fuzzy sets are the special type of type-2 fuzzy sets whose secondary membership grades are all equal to 1. Fuzzy logic control, which is a task oriented control successfully applied in almost all areas of engineering and science. But it lags on its performance, when it is required to handle complex, unstructured and most importantly uncertain environment. There is absolutely no uncertainty in the definition of membership functions of a type-1 fuzzy set. The membership function of a type-2 fuzzy set is itself a fuzzy set which is due to the presence of its third dimension called as footprint of uncertainty. This footprint of uncertainty generally determines the capacity to handle uncertainty. Interval type-2 fuzzy logic controller is designed with the help of interval type-2 fuzzy sets and is applied in different power system problems. The main objectives of the proposed research work are; • Design of an interval type-2 fuzzy logic controller for automatic voltage regulator (AVR) system. • Power System Stabilizer (PSS) design using interval type-2 fuzzy logic control. • Interval type-2 fuzzy logic controller design for thyristor controlled series compensator (TCSC) to improve the damping of power system oscillations. • Stability analysis of interval type-2 fuzzy logic controller as applied to TCSC. Excitation control of the synchronous generator is an important measure to enhance the power system stability and to maintain the quality of power it provides. AVR generally maintain the terminal voltage of a synchronous generator at a specified level. Controller is one of the important components of AVR system. Proportional integral derivative (PID) controller is very popular in industry due to its simple design methodology, easy to use, low development and maintenance cost. But when the system is more complex and its parameter changes due to sudden disturbances, the performance of the PID controller decreases due to improper tuning of the controller parameters. Earlier either the conventional or an optimally tuned PID controller is used as a controller for the AVR system. In this work an interval type-2 fuzzy vi logic controller ( IT2FLC) replaces the particle swarm optimization (PSO) tuned PID controller for the AVR system. For the IT2FLC design, memberships of system variables are represented using interval value fuzzy sets. Fuzzy logic based on interval value sets is capable of modeling the uncertainty and imprecision in a better way. The proposed controller surpasses the best performance obtained by an optimized PID controller in improving the step response of AVR system. Robustness of the proposed controller is tested subjected to changes in system parameters. Power system stabilizers (PSSs) add damping to the electromechanical oscillations of the synchronous generator by controlling its excitation using auxiliary stabilizing signal. Lead lag compensator is one of the important components of PSS. It is required to provide desired phase lead for the compensation to compensate for the phase lag between the exciter input and the electrical torque. In this work a new interval type-2 fuzzy logic controller (IT2FLC) as a PSS is designed by exploring the property of type-2 fuzzy sets for a single machine infinite bus (SMIB) and multi machine (MM) system with brushless AC1A exciter. The IT2FLC rule base is designed based on the performance dynamics of a generic power system stabilizer in which the rotor speed deviation signal of the synchronous machine and its active power are the inputs and the stabilizing voltage signal to be applied to the voltage regulator is considered as the output. Its performance is compared with particle swarm optimized lead lag and type-1 fuzzy logic controller based PSS respectively. The proposed controller performance surpasses the PSO optimized lead lag and type-1 Fuzzy logic controller results. It is also robust subjected to system parameter variation, different operating conditions and at various applied faults as applied to multi machine systems. Thyristor controlled series compensator (TCSC) is one of the important members of flexible AC transmission systems (FACTS) family. FACTS are a technology used to improve the quality of transmission with minimum investment on infrastructure, environment impact and implementation time compared to the construction of new transmission lines. FACTS controllers can be utilized to control power flow and enhance system stability by improving the damping of power system oscillations. In this work an IT2FLC is proposed for TCSC to improve power system damping. For controller design, memberships of system variables are represented using interval type-2 fuzzy sets. The three-dimensional membership function of type-2 fuzzy sets provides additional degree of freedom that makes it possible to directly vii model and handle uncertainties. Simulations conducted on a single machine infinite bus (SMIB) power system shows that proposed controller is more effective than particle swarm optimization (PSO) tuned lead lag compensator and type-1 fuzzy logic (T1FL) based damping controllers. Robust performance of the proposed controller is also validated at different operating conditions, various disturbances and parameter variation of the transmission line parameters. In another study of IT2FLC based TCSC for SMIB system the lead lag compensator is used to modulate the reactance offered by TCSC to improve the power flow. The two inputs to the IT2FLC are the speed deviation, its derivative and the output is the change in the conduction angle. The tuning parameters of the lead lag controller is optimized by the differential evolution algorithm. A type-1 fuzzy logic controller is also designed based on the same rule base of IT2FLC. All the three controller performance is compared. The proposed controller performance is also tested in the presence of disturbance. Simulation results demonstrated the better performance of the proposed controller compared to other two. Stability is one of the important issue concerned to fuzzy control system. Most of the critical comments to fuzzy control are due to the lack of the general method for stability analysis. In most industrial application, reliability of control system is much more important than the stability. However it does not mean that we don’t go for stability analysis. It certainly gives a wider view about the future development of fuzzy control. In this problem fuzzy Lyapunov synthesis method is applied to develop both stable type-1 and type-2 fuzzy logic controller for a SMIB system with TCSC. The state variables are selected from the SMIB system model with TCSC. A positive definite scalar Lyapunov function is assumed for the stability analysis. The rule base of the controller is designed in such a way that it satisfies both the requirement i.e. the control objective and also for verification of negative definiteness of the derivative of Lyapunov function to ascertain the stability criteria of the designed controller. A comparison has been made among both type-1 and type-2 fuzzy logic controller stability results