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In this study, we determine spectral characteristics and amplitude decays of wind turbine induced seismic signals in the far field of a wind farm (WF) close to Uettingen/Germany. Average power spectral densities (PSD) are calculated from 10 min time segments extracted from (up to) 6-months of continuous recordings at 19 seismic stations, positioned along an 8 km profile starting from the WF. We identify 7 distinct PSD peaks in the frequency range between 1 Hz and 8 Hz that can be observed to at least 4 km distance; lower-frequency peaks are detectable up to the end of the profile. At distances between 300 m and 4 km the PSD amplitude decay can be described by a power law with exponent b. The measured b-values exhibit a linear frequency dependence and range from b = 0.39 at 1.14 Hz to b = 3.93 at 7.6 Hz. In a second step, the seismic radiation and amplitude decays are modeled using an analytical approach which approximates the surface-wave field. Since we observe temporally varying phase differences between seismograms recorded directly at the base of the individual wind turbines (WTs), source-signal phase information is included in the modeling approach. We show that phase differences between source signals have significant effects on the seismic radiation pattern and amplitude decays. Therefore, we develop a phase-shift-elimination-method to handle the challenge of choosing representative source characteristics as an input for the modeling. To optimize the fitting of modeled and observed amplitude decay curves, we perform a grid search to constrain the two model parameters, i.e., the seismic shear wave velocity and quality factor. The comparison of modeled and observed amplitude decays for the 7 prominent frequencies shows very good agreement and allows to constrain shear velocities and quality factors for a two-layer model of the subsurface. The approach is generalized to predict amplitude decays and radiation patterns for WFs of arbitrary geometry.
In this study, we determine spectral characteristics and amplitude decays of wind turbine induced seismic signals in the far field of a wind farm (WF) close to Uettingen, Germany. Average power spectral densities (PSDs) are calculated from 10 min time segments extracted from (up to) 6 months of continuous recordings at 19 seismic stations, positioned along an 8 km profile starting from the WF. We identify seven distinct PSD peaks in the frequency range between 1 and 8 Hz that can be observed to at least 4 km distance; lower-frequency peaks are detectable up to the end of the profile. At distances between 300 m and 4 km the PSD amplitude decay can be described by a power law with exponent b. The measured b values exhibit a linear frequency dependence and range from b=0.39 at 1.14 Hz to b=3.93 at 7.6 Hz. In a second step, the seismic radiation and amplitude decays are modeled using an analytical approach that approximates the surface wave field. Since we observe temporally varying phase differences between seismograms recorded directly at the base of the individual wind turbines (WTs), source signal phase information is included in the modeling approach. We show that phase differences between source signals have significant effects on the seismic radiation pattern and amplitude decays. Therefore, we develop a phase shift elimination method to handle the challenge of choosing representative source characteristics as an input for the modeling. To optimize the fitting of modeled and observed amplitude decay curves, we perform a grid search to constrain the two model parameters, i.e., the seismic shear wave velocity and quality factor. The comparison of modeled and observed amplitude decays for the seven prominent frequencies shows very good agreement and allows the constraint of shear velocities and quality factors for a two-layer model of the subsurface. The approach is generalized to predict amplitude decays and radiation patterns for WFs of arbitrary geometry.
This thesis presents the experimental and numerical analysis of seismic waves that are produced by wind farms. With the aim to develop renewable energies rapidly, the number of wind turbines has been increased in recent years. Ground motions induced by their operation can be observed by seismometers several kilometers away. Hence, the seismic noise level can be significantly increased at the seismic station. Therefore, this study combines long-term experiments and numerical simulations to improve the understanding of the seismic wavefields emitted by complete wind farms and to advance the prediction of signal amplitudes.
Firstly, wind-turbine induced signals that are measured at a small wind farm close to Würzburg (Germany) are correlated with the operational data of the turbines. The frequency-dependent decay of signal amplitudes with distance from the wind farm is modeled using an analytical method including the complex effects of interferences of the wavefields produced by the multiple wind turbines. Specific interference patterns significantly affect the wave propagation and therefore the signal amplitude in the far field of a wind farm. Since measurements inside the wind turbines show that the assumption of in-phase vibrating wind turbines is inappropriate, an approach to calculate representative seismic radiation patterns from multiple wind turbines, which allows the prediction of amplitudes in the far field of a complete wind farm, is proposed.
In a second study, signals with a frequency of 1.15 Hz, produced by the Weilrod wind farm (north of Frankfurt, Germany) are observed at the seismological observatory TNS (Taunus), which is located at a distance of 11 km from the wind farm. The propagation of the wavefield emitted by the wind farm is numerically modeled in 3D, using the spectral element method. It is shown that topographic effects can cause local signal amplitude reductions, but also signal amplification along the travel path of the seismic wave. The comparison of simulations with and without topography reveals that the reduction and amplification are spatially linked to the shape of the topography, which could be an explanation for the relatively high signal amplitude observed at TNS.
Finally, the reduction of the impact of wind turbines on seismic measurements using borehole installations is studied using 2D numerical models. Possible effects of the seismic velocity, attenuation, and layering of the subsurface are demonstrated. Results show that a borehole can be very effective in reducing the observed high-frequency signals emitted by wind turbines. However, a borehole might not be beneficial if signals with frequencies of about 1 Hz (or lower) are of interest, due significant wavelength-dependent effects. The estimations of depth-dependent amplitudes with a layered subsurface are validated with existing data from wind-turbine-induced signals measured at the top and bottom of two boreholes.
The experimental analysis of measurements conducted at wind farms and the advances of modeling such signals improve the understanding of the propagation of wind-farm induced seismic wave fields. Furthermore, the methods developed in this work have a high potential of universal application to the prediction of signal amplitudes at seismometers close to wind farms with arbitrary layout and geographic location.