Adaptive neuro-fuzzy estimation of diffuser effects on wind turbine performance

Wind power is generating interest amongst many countries to produce sustainable electrical power. It is well known that the main drawback of wind power is the inherent variable behavior of wind speed. Significant research has been carried out to improve the performance of the wind turbines and establish the power system stability. As power output is proportional to the cubic power of the incident airspeed, any small increase in the incident wind yields a large increase in the energy output. One of the more promising advanced concepts for overcoming the inherent variable behavior of wind speed is the DAWT (diffuser-augmented wind turbine). The diffuser or flanged diffuser generates separation regions behind it, where low-pressure regions appear to draw more wind through the rotors compared to a bare wind turbine. Thus, the output power of the DAWT is much larger than for a unshrouded turbine. To estimate rotor performance of the diffuser-augmented wind turbine, this paper constructed a process which simulates the power output, torque output and rotational speed of the rotor in regard to diffuser effect and wind input speed with ANFIS (adaptive neuro-fuzzy) method. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated.

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