Seismic Noise Induced by Wind Turbine Operation and Wind Gusts

2019 ◽  
Vol 91 (1) ◽  
pp. 427-437
Author(s):  
Weifei Hu ◽  
Rebecca J. Barthelmie ◽  
Frederick Letson ◽  
Sara C. Pryor
Keyword(s):  
Wind Turbine ◽  
Seismic Data ◽  
Seismic Noise ◽  
Meteorological Data ◽  
Power Spectra ◽  
Wind Gust ◽  
Attenuation Coefficients ◽  
Earthquake Detection ◽  
Wind Gusts ◽  
Noise Characterization

Abstract Improved seismic noise characterization, due to varied sources, may benefit traditional applications. Some examples are earthquake detection, Earth structure research, and nuclear testing. This improvement could also permit use of seismic data in transdisciplinary research such as wind gust detection and wind turbine (WT) condition monitoring. However, it is a challenging task to unambiguously quantify relationships between potential sources of seismic noise and the actual seismic response. In this article, we analyze seismic and meteorological data (wind speed and pressure), measured at a remote site in a complex terrain area in eastern Portugal, to examine seismic signatures from WT operational status and wind gusts. Results presented herein show the following: (1) WT signatures in seismic data can be used to accurately determine WT‐operational status. Attenuation of WT signatures in seismic data exhibits an exponential decay with distance, with attenuation coefficients that scale with frequency. (2) After WT signatures are removed from seismic power spectra, wind gust signatures remain. Analyses of these data further indicate that it may be possible to extract quantitative wind gust estimates from seismic data and decompose them into pressure and shear stress drivers of this coupling.

scholarly journals Covid-19 lockdown effects on the seismic recordings of Central America

2021 ◽  
Author(s):  
Mario Arroyo-Solórzano ◽  
Diego Castro-Rojas ◽  
Frédérick Massin ◽  
Lepolt Linkimer ◽  
Ivonne Arroyo ◽  
...  
Keyword(s):  
Costa Rica ◽  
El Salvador ◽  
Central America ◽  
Seismic Data ◽  
Seismic Noise ◽  
Temporal Variations ◽  
Noise Levels ◽  
Seismic Stations ◽  
Earthquake Detection ◽  
Seismic Records

Abstract. A noticeable decrease in seismic noise was registered worldwide during the lockdown measurements of 2020 to prevent the Covid-19. In Central America, strong lockdown measures started during March of 2020. We have used seismic stations from Costa Rica, Guatemala, El Salvador, and Nicaragua to study the effects of these measures on seismic records by characterizing temporal variations in the high-frequency band (4–14 Hz) via spectral and amplitude analyses. In addition, we study the link between the reduction of seismic noise and the number of earthquake detection and felt reports in Costa Rica and Guatemala. We found that seismic stations near the capitals of Costa Rica, Guatemala, and El Salvador, presented a decrease in the typical seismic noise level from 200 to 140 nm, 100 to 80 nm, and 120 to 80 nm, respectively. Our results showed that the largest reduction of ~50 % in seismic noise were observed in seismic stations near main airports, busy roads, and densely populated cities. In Nicaragua, the seismic noise levels remained constant (~40 nm) as no lockdown measures were applied. We noted that the decrease in seismic noise levels allowed to improve earthquake locations and increment the number of reports of low magnitude felt earthquakes. Our results imply that seismic data can be useful to verify the compliance of lockdown measures and to explore effects of the decrease in the seismic noise in the earthquake detection and felt reports.

scholarly journals Wind Gust Characterization at Wind Turbine Relevant Heights in Moderately Complex Terrain

2018 ◽  
Vol 57 (7) ◽  
pp. 1459-1476 ◽  
Author(s):  
W. Hu ◽  
F. Letson ◽  
R. J. Barthelmie ◽  
S. C. Pryor
Keyword(s):  
Complex Terrain ◽  
Power Spectra ◽  
Wind Component ◽  
Length Scale ◽  
Wind Gust ◽  
Atmospheric Conditions ◽  
Length Scales ◽  
Wind Gusts ◽  
Sonic Anemometers ◽  
Gust Factors

AbstractImproved understanding of wind gusts in complex terrain is critically important to wind engineering and specifically the wind energy industry. Observational data from 3D sonic anemometers deployed at 3 and 65 m at a site in moderately complex terrain within the northeastern United States are used to calculate 10 descriptors of wind gusts and to determine the parent distributions that best describe these parameters. It is shown that the parent distributions exhibit consistency across different descriptors of the gust climate. Specifically, the parameters that describe the gust intensity (gust amplitude, rise magnitude, and lapse magnitude; i.e., properties that have units of length per time) fit the two-parameter Weibull distribution, those that are unitless ratios (gust factor and peak factor) are described by log-logistic distributions, and all other properties (peak gust, rise and lapse times, gust asymmetric factor, and gust length scale) are lognormally distributed. It is also shown that gust factors scale with turbulence intensity, but gusts are distinguishable in power spectra of the longitudinal wind component (i.e., they have demonstrably different length scales than the average eddy length scale). Gust periods at the lower measurement height (3 m) are consistent with shear production, whereas at 65 m they are not. At this site, there is only a weak directional dependence of gust properties on site terrain and land cover variability along sectorial transects, but large gust length scales and gust factors are more likely to be observed in unstable atmospheric conditions.

scholarly journals Rain Erosion Maps for Wind Turbines Based on Geographical Locations: A Case Study in Ireland and Britain

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
K. Pugh ◽  
M. M. Stack
Keyword(s):  
Wind Turbine ◽  
Western Europe ◽  
Meteorological Data ◽  
Turbine Blades ◽  
Weather Conditions ◽  
Annual Rainfall ◽  
Wind Turbine Blades ◽  
Weather Patterns ◽  
The Uk

AbstractErosion rates of wind turbine blades are not constant, and they depend on many external factors including meteorological differences relating to global weather patterns. In order to track the degradation of the turbine blades, it is important to analyse the distribution and change in weather conditions across the country. This case study addresses rainfall in Western Europe using the UK and Ireland data to create a relationship between the erosion rate of wind turbine blades and rainfall for both countries. In order to match the appropriate erosion data to the meteorological data, 2 months of the annual rainfall were chosen, and the differences were analysed. The month of highest rain, January and month of least rain, May were selected for the study. The two variables were then combined with other data including hailstorm events and locations of wind turbine farms to create a general overview of erosion with relation to wind turbine blades.

Aerodynamic Noise Characterization of a Full-Scale Wind Turbine through High-Frequency Surface Pressure Measurements

2015 ◽  
Vol 14 (5-6) ◽  
pp. 729-766 ◽  
Author(s):  
Franck Bertagnolio ◽  
Helge Aa. Madsen ◽  
Christian Bak ◽  
Niels Troldborg ◽  
Andreas Fischer
Keyword(s):  
Wind Turbine ◽  
Surface Pressure ◽  
High Frequency ◽  
Full Scale ◽  
Aerodynamic Noise ◽  
Pressure Measurements ◽  
Noise Characterization

scholarly journals Wind Gust Measuring at Low Altitude Using An Unmanned Aerial System

2021 ◽  
Author(s):  
Alton Yeung
Keyword(s):  
Turbulence Models ◽  
Satellite System ◽  
Data System ◽  
Measurement Unit ◽  
Wind Gust ◽  
Wind Gusts ◽  
Low Altitude ◽  
And Performance ◽  
Global Navigation Satellite ◽  
Aerial Platform

A small unmanned aerial vehicle (UAV) was developed with the specific objective to explore atmospheric wind gusts at low altitudes within the atmospheric boundary layer (ABL). These gusts have major impacts on the flight characteristics and performance of modern small unmanned aerial vehicles. Hence, this project was set to investigate the power spectral density of gusts observed at low altitudes by measuring the gusts with an aerial platform. The small UAV carried an air-data system including a fivehole probe that was adapted for this specific application. The air-data system measured the local wind gusts with an accuracy of 0.5 m/s by combining inputs from a five-hole probe, an inertial measurement unit, and Global Navigation Satellite System (GNSS) receivers. Over 20 flights were performed during the development of the aerial platform. Airborne experiments were performed to collect gust data at low altitudes between 50 m and 100 m. The result was processed into turbulence spectrum and the measurements were compared with the MIL-HDBK-1797 von K´arm´an turbulence model and the results have shown the model underpredicted the gust intensities experienced by the flight vehicle. The anisotropic properties of low-altitude turbulence were also observed when analyzing the measured gusts spectra. The wind and gust data collected are useful for verifying the existing turbulence models for low-altitude flights and benefit the future development of small UAVs in windy environment.

Building damage impact forecasting for winter windstorms in Switzerland

2021 ◽  
Author(s):  
Thomas Röösli ◽  
David N. Bresch
Keyword(s):  
False Alarm ◽  
Meteorological Data ◽  
Weather Forecast ◽  
Building Damage ◽  
False Alarms ◽  
Preventive Action ◽  
Wind Gusts ◽  
Geographical Regions ◽  
Forecasting System ◽  
The Impact

<p>Weather extremes can have high socio-economic impacts. Better impact forecasting and preventive action help to reduce these impacts. In Switzerland, the winter windstorms caused high building damage, felled trees and interrupted traffic and power. Events such as Burglind-Eleanor in January 2018 are a learning opportunity for weather warnings, risk modelling and decision-making.</p><p>We have developed and implemented an operational impact forecasting system for building damage due to wind events in Switzerland. We use the ensemble weather forecast of wind gusts produced by the national meteorological agency MeteoSwiss. We couple this hazard information with a spatially explicit impact model (CLIMADA) for building damages due to winter windstorms. Each day, the impact forecasting system publishes a probabilistic forecast of the expected building damages on a spatial grid.</p><p>This system produces promising results for major historical storms when compared to aggregated daily building insurance claims data from a public building insurer of the canton of Zurich. The daily impact forecasts were qualitatively categorized as (1) successful (2) miss or (3) false alarm. The impacts of windstorm Burglind-Eleanor and five other winter windstorms were forecasted reasonably well, with four successful forecasts, one miss and one false alarm.</p><p> The building damage due to smaller storm extremes was not as successfully forecasted. Thunderstorms are not as well forecasted with 2 days’ lead time and as a result the impact forecasting system produces more misses and false alarms outside the winter storm season. For the Alpine-specific southerly Foehn winds, the impact forecasts produce many false alarms, probably caused by an overestimation of wind gusts in the weather forecast.</p><p>The forecasting system can be used to improve weather warnings and allocate resources and staff in the claims handling process of building insurances. This will help to improve recovery time and costs to institutions and individuals. The open-source code and open meteorological data makes this implementation transferable to other hazard types and other geographical regions.</p>

Inferring significant wave height from seismic data: A comparison between methods.

2021 ◽  
Author(s):  
Francisco Bolrão ◽  
Co Tran ◽  
Miguel Lima ◽  
Sheroze Sheriffdeen ◽  
Diogo Rodrigues ◽  
...  
Keyword(s):  
Real Time ◽  
Wave Height ◽  
Seismic Data ◽  
Significant Wave Height ◽  
Transfer Functions ◽  
Seismic Station ◽  
Meteorological Data ◽  
Ocean Waves ◽  
The United States ◽  
Significant Wave

<p>The most pervasive seismic signal recorded on our planet – microseismic ambient noise -results from the coupling of energy between atmosphere, oceans and solid Earth. Because it carries information on ocean waves (source), the microseismic wavefield can be advantageously used to image ocean storms. This imaging is of interest both to climate studies – by extending the record of oceanic activity back into the early instrumental seismic record – and to real-time monitoring – where real-time seismic data can potentially be used to complement the spatially dense but temporally sparse satellite meteorological data.<br>In our work, we develop empirical transfer functions between seismic observations and ocean activity observations, in particular, significant wave height. We employ three different approaches: 1) The approach of Ferretti et al (2013), who compute a seismic significant wave height and invert only for the empirical conversion parameters between oceanic and seismic significant wave heights; 2) The classical approach of Bromirski et al (1999), who computed an empirical transfer function between ground-motion recorded at a coastal seismic station and significant wave height measured at a nearby ocean buoy; and 3) A novel recurrent neural-network (RNN) approach to infer significant wave height from seismic data. <br>We apply the three approaches to seismic and ocean buoy data recorded in the east coast of the United States. All three approaches are able to successfully predict ocean significant wave height from the seismic data. We compare the three approaches in terms of accuracy, computational effort and robustness. In addition, we investigate the regimes where each approach works best.  The results show that the RNN approach is able to predict well the significant wave height recorded at the buoy. The prediction is improved if several nearby seismic stations are used rather than just one. <br>This work is supported by FCT through projects UIDB/50019/2020 – IDL and UTAP-EXPL/EAC/0056/2017 - STORM.</p>

scholarly journals Characterizing wind gusts in complex terrain

2019 ◽  
Vol 19 (6) ◽  
pp. 3797-3819 ◽  
Author(s):  
Frederick Letson ◽  
Rebecca J. Barthelmie ◽  
Weifei Hu ◽  
Sara C. Pryor
Keyword(s):  
Wind Turbines ◽  
Complex Terrain ◽  
Probability Distributions ◽  
Wind Loading ◽  
Wind Gust ◽  
Wind Gusts ◽  
Sonic Anemometers ◽  
Vertical Displacements ◽  
Structural Loading ◽  
Good Agreement

Abstract. Wind gusts are a key driver of aerodynamic loading, especially for tall structures such a bridges and wind turbines. However, gust characteristics in complex terrain are not well understood and common approximations used to describe wind gust behavior may not be appropriate at heights relevant to wind turbines and other structures. Data collected in the Perdigão experiment are analyzed herein to provide a foundation for improved wind gust characterization and process-level understanding of flow intermittency in complex terrain. High-resolution observations from sonic anemometers and vertically pointing Doppler lidars are used to conduct a detailed study of gust characteristics with a specific focus on the parent distributions of nine gust parameters (that describe velocity, time, and length scales), their joint distributions, height variation, and coherence in the vertical and horizontal planes. Best-fit distributional forms for varying gust properties show good agreement with those from previous experiments in moderately complex terrain but generate nonconservative estimates of the gust properties that are of key importance to structural loading. Probability distributions of gust magnitude derived from vertically pointing Doppler lidars exhibit good agreement with estimates from sonic anemometers despite differences arising from volumetric averaging and the terrain complexity. Wind speed coherence functions during gusty periods (which are important to structural wind loading) are similar to less complex sites for small vertical displacements (10 to 40 m), but do not exhibit an exponential form for larger horizontal displacements (800 to 1500 m).

Exploiting wind-turbine noise for seismic imaging and monitoring

2020 ◽  
Author(s):  
Elmer Ruigrok ◽  
Lisanne Jagt ◽  
Britt van der Vleut
Keyword(s):  
Wind Turbine ◽  
Seismic Noise ◽  
Seismic Source ◽  
Seismic Network ◽  
Seismic Sources ◽  
The Novel ◽  
Wind Turbine Noise ◽  
Cost Reductions ◽  
Cost Efficient ◽  
Subsurface Monitoring

<p>Wind turbines (WTs) have proven to be an increasingly cost-efficient source of sustainable energy. With further cost reductions and growth of environmental awareness, the amount and size of WTs will further expand. In the seismic literature, WTs have mainly been considered a threat rather than an opportunity. WTs act as infrasound and seismic sources, whose wavefield might overwhelm signal from earthquakes. Rather than focusing on the detrimental effects, we embrace the WT revolution and focus on the novel possibilities of the WT seismic source. We show detailed characteristics of this source using recordings over the Groningen seismic network. We further show examples of using the WT seismic noise for extracting medium parameters. Moreover, we exploit the repeatable nature of the source for subsurface monitoring.</p>

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