Robust stability power in the transmission line with the use of a UPFC system and neural controllers based adaptive control

The main purpose of this paper is to design a regulator which enables a power system to track reference signals precisely and to be robust in the presence of uncertainty of system parameters and disturbances. The performances of the proposed controllers (NEWELM and NIMC) are based neural adaptive control and simulated on a two-bus test system and compared with a conventional PI controller with decoupling (PI-D). The studies are performed based on well known software package MATLAB/Simulink tool box. Flexible Alternating Current Transmission System devices (FACTS) are power electronic components. Their fast response offers potential benefits for power system stability enhancement and allows utilities to operate their transmission systems even closer to their physical limitations, more efficiently, with improved reliability, greater stability and security than traditional mechanical switching technology. The most used component of FACTS systems is the Unified Power Flow Controller (UPFC). According to high importance of power flow control in transmission lines, new controllers are designed based on the Elman Recurrent Neural Network (NEWELM) and Neural Inverse Model Control (NIMC) with adaptive control.