Application of multi objective and hybrid techniques in power system operation and control

Abstract

This thesis mainly contributes in the area of power system stability improvement by the application of Artificial Intelligence (AI) techniques to ensure stable and secured operation. An attempt has been made in the present study for the application of various AI techniques to improve the stability of a power system. In this regard, improved AI techniques and hybridization of these AI techniques as well as new controller structures are proposed for performance enhancement of power systems. newlineOver the years, many techniques have been suggested for tuning of the PID parameters. These techniques includes classical Ziegler/Nichols method, gain-phase margin method, Cohen/Coon and pole placement method as3e well as some advanced methods such as minimum variance, gain scheduling and predictive techniques. Some disadvantages of these control techniques for tuning PID controllers are: (i) excessive number of rules to set the gains, (ii) inadequate dynamics of closed loop responses, (iii) difficulty to deal with nonlinear processes, and (iv) mathematical complexity of the control design. In traditional techniques, problem formulation must satisfy mathematical restrictions, and may suffer from numerical problems. Further, in a complex system consisting of number of controllers, the optimization of several controller parameters using the traditional techniques is very complicated process and sometimes gets struck at local minima resulting in sub-optimal controller parameters. newline