ANN based Harmonic Extraction in DFIG Fed DSTATCOM System

The evolution of the renewable energy is the best solution for environment to reduce the pollution. Due to the fastest development of the Wind power penetration in the power system many countries offer the stable operations of power system. The most widely installed machine in the wind farm is Doubly Fed Induction Generator (DFIG).The operation of a wind energy conversion system (WECS) is based on a DFIG which is Sensitive to unbalanced non-linear load. In the proposed system the AC source is given to the non-linear load, to reduce the fluctuation the control function Distribution Static Synchronous Compensator (DSTATCOM) is used where the Input power is fed to the DFIG, it converts the AC voltage to DC and fed to Voltage Source Invertor (VSI). The reference and actual current get combined and passes to the Proportional Integral (PI) controller which is used to adjust reference and actual values and then fed to the Pulse Width Modulation (PWM) generator. The source voltage and source current are given to the DQ theory which produce the reference current and then fed to Artificial Neural Network (ANN) classifier which is used to reduce the harmonics. The PWM generator which improve the power quality and generate pulses which is applied to VSI and thereby, the generation of an opposing current is injected to the Point of Common Coupling (PCC). The design process is accessed by the MATLAB simulation.