Title :
Adaptive and artificial intelligence based PSS
Author_Institution :
Calgary Univ., Alta., Canada
Abstract :
The supplementary stabilizing signal input to the excitation system of a synchronous generator enhances system damping by producing a torque in phase with the speed of the generator. The most common PSS (CPSS) is based on the use of a linear transfer function designed by applying the linear control theory to the system model linearized at a pre-assigned operating point. Power systems are non-linear and operate over a wide range. Due to the non-linear characteristics, wide operating conditions and unpredictability of perturbations in a power system, the CPSS, a linear controller, generally cannot maintain the same quality of performance under all conditions of operation. To further improve the performance and stability of the power system, various other approaches using the linear quadratic optimal control, H-infinity, variable structure, rule base, and artificial intelligence (AI) techniques have been proposed in the literature to design a fixed parameter PSS. One common feature of all fixed parameter controllers is that the design is done off-line.
Keywords :
H∞ control; adaptive control; artificial intelligence; neurocontrollers; power system control; power system stability; self-adjusting systems; H-infinity; artificial intelligence techniques; linear adaptive controller; linear control theory; linear quadratic optimal control; power system stabilizer; rule base; supplementary stabilizing signal input; synchronous generator; variable structure; Artificial intelligence; Control theory; Damping; Nonlinear control systems; Power system modeling; Power system stability; Signal generators; Synchronous generators; Torque; Transfer functions;
Conference_Titel :
Power Engineering Society General Meeting, 2003, IEEE
Print_ISBN :
0-7803-7989-6
DOI :
10.1109/PES.2003.1267428