A Design and Modeling Techniques for Maximum Power Optimization on Wind Electrical Power System with Variable Speed Generation Using Neuro Fuzzy

One of the greatest challenges associated with wind power is the unpredictable character of the wind. Wind energy is one of the lowest-priced renewable energy technologies available today, costing between 4 and 6 cents per kilowatt-hour, depending upon the wind resource and project financing of the particular project. In our research, a design and modeling technique has been proposed to optimize the maximum power extraction. An intelligent neuro fuzzy controller can keep track of variable speed generator with respect to the velocity of wind. The main objective of this paper is to fully control the wind turbine system with induction generator to maximize the power generation. The output power of a wind turbine is function of wind velocity cubed. The system has been optimized for operating around 15 m/s, and though the wind power continues to increase above this point. In addition, a neuro-fuzzy controller is also proposed for obtaining maximum power optimization. A variable speed wind turbine utilizes the available wind resource more efficiently than a fixed speed wind turbine, especially during light wind conditions.