Abstract:
This paper presents Adaptive Neuro – Fuzzy Inference system (ANFIS) based control scheme to improve the performance of grid connected hybrid microgrid system. The proposed system consists of solar, wind, Static VAR Compensator (SVC) and load. Distributed Energy Resources (DERs) such as solar and wind which are connected in the microgrid will meet the power demand. Static Var Compensators (SVC) is used to compensate the reactive power, reduce oscillation and to improve grid voltage. The change in solar irradiance is considered and Maximum Power Point tracking (MPPT) scheme is used to extract maximum power from PV system. Permanent Magnet Synchronous Generator coupled with variable speed wind turbine is connected to grid. ANFIS is a adaptive and non-linear controller. It is more accurate and has the merits of both neural network and Fuzzy Inference systems. The main objective of proposed simulation model is focused on SVC based hybrid PV / Wind power system integrated with microgrid power network using ANFIS intelligent controller. The ANFIS intelligent controller monitors the power grid every half cycle and generates the control signal for microgrid integrated inverter for maintaining synchronization of grid and hybrid system at various operating conditions. The proposed ANFIS controller also reduces the THD (Total Harmonic Distortion) value of voltage and current profile of Point of Common Coupling (PCC) as well as load distribution side also. Simulation is carried out in MATLAB/Simulink environment. The robustness of this controller scheme is verified and MPPT performance of wind, MPPT performance of PV, voltage on distribution side, power extraction from PV and wind under variable load and environmental condition of the system are improved.
