Neural Network based Statcom for Grid Connected wind Generator

Due to the increasing demand and restriction in building of the new lines complex modern power system presents serious challenges regarding stability of power system. Transient stability is also known as main source of the system insecurity. Because of that in the event of faults and disturbances it has to be maintained for power systems stable operation. In earlier power system to improve the transient stability supplementary controllers are used. These supplementary controllers are the shunt FACT devices like STATCOM (Static Synchronous Compensator) and SVC (Static VAR Compensator). Thesis suggests an application regarding NN (Neural Network). NN determines controller signal of STATCOM for grid active power and reactive power hence this improves stability of power system. Suggested controller is tested on 3-bus 2-machine system. The parameters like terminal voltage of buses, active power transmission line and reactive power of the system. The results which obtained are compared with the FLC system, Neural Network (NN). This proved that the Neural Network STATCOM gives better power result compare to that of STATCOM with FLC system. The effectiveness is verified by the Mat Lab/Simulink Software