Potential of neuro-fuzzy methodology to estimate noise level of wind turbines

• Wind turbine noise is major hindrance for the widespread use of wind energy.
• Aerodynamic noise from the blades is dominant noise source.
• Adaptive neuro-fuzzy inference system (ANFIS) as alternative to analytical approach.
• ANFIS offers no required knowledge of internal system parameters.
• ANFIS predicts the wind turbine sound power level.

Wind turbines noise effect became large problem because of increasing of wind farms numbers since renewable energy becomes the most influential energy sources. However, wind turbine noise generation and propagation is not understandable in all aspects. Mechanical noise of wind turbines can be ignored since aerodynamic noise of wind turbine blades is the main source of the noise generation. Numerical simulations of the noise effects of the wind turbine can be very challenging task. Therefore in this article soft computing method is used to evaluate noise level of wind turbines. The main goal of the study is to estimate wind turbine noise in regard of wind speed at different heights and for different sound frequency. Adaptive neuro-fuzzy inference system (ANFIS) is used to estimate the wind turbine noise levels.