Performance Analysis of Customer Power Device by Intelligent Controller in Wind Generation based DG System

Background: Distributed Generation (DG) is facing a rapid development as a new means of power generation. DG is affecting the power quality of the system due to uncertainty condition and fault. Artificial Neuro Fuzzy Inference System (ANFIS) based DVR controller is planned to regulate the voltage at the Point of Common Coupling (PCC) within the limits and stabilize the operation of the system in the event of disturbances. The simulated results reveal that ANFIS based control scheme shows better performance compared to traditional controller. Methods: This system analysis the performance of dq0 based Proportional Integral and Adaptive Neuro Fuzzy Inference System controllers with DVR, which incorporates a solar system as a DC voltage source. Incremental Conductance MPPT Algorithm method tracks the maximum power point of solar system. An ANFIS based DVR controller method is implemented for the maximum injected voltage, ANFIS based on Takagi Sugeno Fuzzy inference System (FIS) is introduced. The generated fuzzy rules can be trained by using neural network and attain desired output. So as to mitigate the voltage sags /swells condition in the test system. Results: It is observed from the results, ANFIS based DVR controller can compensate the load voltage is kept at a constant value and to maintain the stable operation of DG systems under, voltage sag/swell and fault conditions, further harmonic voltage is compensated and the voltage is made sinusoidal. Conclusions: ANFIS based DVR conditioner has better dynamic response and Total Harmonic Distortion is less compared with conventional controller.