V.Vinothkumar 2

Abstract — Recent years have seen a rapidly growing number of hybrid neuro fuzzy based applications in the process engineering field, covering estimation, modeling and control among others. By this technology integrates distributed generations, energy storage elements and loads. In this paper, dynamic performance enhancement of a grid consisting of wind turbine was investigated using permanent magnet synchronous generation (PMSG) and photovoltaic (PV). In order to maximize the output of solar array and wind, maximum power point tracking (MPPT) technique was used by an adaptive neuro-fuzzy inference system (ANFIS). These proposed methodology based reference model is trained to generate maximum power corresponding to varying the values of solar and wind. Simulation results reveal that the response of proposed ANFIS based MPPT method is more accurate and fast as compared to the conventional techniques like Incremental Conductance (IC). The analytical and simulation results of this research are presented to validate the concept. The proposed method also precedes the performance of the error reduction by the function of droop control method which exist the equal power sharing. The improved droop control can share active and reactive power to improve the power quality of the grid and also have a good dynamic performance