Development of an advanced noise propagation model for noise optimization in wind farm

Increasing demand in renewable energy has resulted in large wind energy deployment. Even though wind turbines are among the most environmentally friendly way of generating electricity, the noise emitted by them is one of the main obstacles for further installation. Wind farm developers rely on noise mapping tools for environmental impact assessment studies.

Inaccurate noise mapping during wind farm development phase may result in under or overprediction of the sound pressure levels. The former causes downregulation of wind turbines under certain atmospheric conditions (e.g. for some incoming wind directions or time of the day). The latter causes turbines to be located at less resourceful sites in advance.

Both of these scenarios increase the cost of energy. Hence there is a need for more accurate noise mapping tools. The thesis addresses this issue via development of a new tool based on combined source, propagation and flow models.The parabolic wave equation method is used for modelling the frequency dependent wave propagation.

Different numerical techniques such as FFT’s or finite difference method are implemented to solve the equations. The wind speed and temperature distributions are obtained either from Large Eddy Simulation or Reynolds-Averaged Navier-Stokes computations. The course levels and locations are obtained from aeroelastically coupled semi empirical airfoil noise models.

Via the developed tool the effects of various atmospheric phenomena and turbine operation conditions on far field noise are investigated. Classical propagation effects (i.e. shadow zones at the upwind of the turbine, absorbing character of grass versus hard ground) and source level changes due to the operational conditions are well captured.

Additionally, throughout the thesis the effects of wake on far field sound pressure levels are addressed both in steady and unsteady manner. Enhanced far fields amplitude modulation is observed and associated with the wake dynamics and the rotating blades. Lastly, the developed tool is used for an onshore wind farm noise prediction taking the terrain and the flow field around it into account.