ANFIS Controller based PV-DSTATCOM for Improving Power Quality

ANFIS (Adaptive Neuro-Fuzzy Inference System) is considered as one of the most efficient topologies to enhance the quality of power by regulating voltage and mitigating harmonic distortions in the distribution system. The ANFIS controller, is a hybrid of artificial neural networks and fuzzy logic, is used to optimize the control of the PV-DSTATCOM (Photovoltaic - Distribution Static Compensators), by adapting the changes in the system parameters. A PV-DSTATCOM, is a power electronic device that combines the capabilities of a distributed generation system with those of a distribution static compensator. The PV- DSTATCOM is a custom-built device designed to mitigate voltage sags and harmonics caused by nonlinear loads in distribution systems. The proposed system achieves, quality of power in the system by implementing the ANFIS based PV-DSTATCOM. From solar system the maximum power is tracked by P&O (Perturbation and observation) algorithm for controlling the voltage at the DC Link. The ability of the structure is evaluated and validated using Matlab/ Simulink model. The result show that the proposed ANFIS controller-based PV-DSTATCOM is more effective in improving power quality by mitigating voltage sags and harmonics distortions than the conventional PI controller that contributes to the development of efficient and reliable power quality system.