Control of the static synchronous compensator (STATCOM) by using artificial neural network (ANN)

Due to improving technology, the demand of the energy has significantly increased and as a result of this circumstances the power systems have become more complicated over this period. Thus, to both develop the carrying capacity and make the transfer system stable have become an essential issue. In this dissertation, it is proved that applying reactive compensation to the power systems results that the load carrying ability and the stability of the system are enhanced. As a consequence of on going process in the power systems, traditional capacitor, reactor groups and devices using exciters became insufficient. The compensation of power systems applied with sophisticated power devices allows complete and flexible control of the power systems. Devices which are called FACTS are implemented to control dynamic compensation and energy flow in the power systems, and also obtain a beter stability .In this study, a computer simulation of STATCOM which is FACTS devices based on converter for power flow in transmission line is carried out by using MATLAB SIMULINK Toolbox. The computer simulation results show that STATCOM have fast response ability for any change in the power system. The static parameter PI controllers with Neural Networks (NN) have been used in the STATCOM controler. PI controller design complexity is eliminated and automatic tuning of the PI controller parameters is provided by utilizing the learning and generalization capabilities of the neural networks. STATCOM DC controller has been done by NN-PI. Simulation result showing, between PI with NN difference was given.