APPLICATION OF ARTIFICIAL INTELLIGENCE TO STATIC VAR SOURCE CONTROL FOR IMPROVING POWER SYSTEM DAMPING

Static Var Compensators (SVCs) have been widely used in power systems to keep terminal voltages within bounds. The other application is to improve power systems damping, especially for loosely connected power systems. However, contributions to the damping of system oscillations from the conventional control of SVC are usually small. Supplementary control is resorted to achieve significant damping. Two kinds of Fuzzy Logic Control (FLC) based SVC controllers are proposed. The first kind of FLC mechanism is based on the power system oscillation energy analysis and makes use of genetic algorithm to tune the rule base of FLC. The second is based on Lyapunov function analysis and applies bang-bang control theory. With the FLC controllers, the total SVC control configuration is composed of a conventional voltage regulation branch as well as an auxiliary FLC branch arranged in parallel. Control signals are generated from each control branch, and summed to form the total control output. Effective damping of the proposed controllers has been demonstrated on a three-machine power system. Simulation results show that the proposed controllers are capable of improving the system damping dramatically for the studied cases. Several factors that may influence the performance of the controller are also discussed in detail.

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• YU QIZHI