scholarly journals Response to Noise Emitted by Wind Farms in People Living in Nearby Areas

2018 ◽  
Vol 15 (8) ◽  
pp. 1575 ◽  
Author(s):  
Małgorzata Pawlaczyk-Łuszczyńska ◽  
Kamil Zaborowski ◽  
Adam Dudarewicz ◽  
Małgorzata Zamojska-Daniszewska ◽  
Małgorzata Waszkowska
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Plants ◽  
Sound Pressure ◽  
Road Traffic ◽  
Wind Farms ◽  
Specific Area ◽  
Well Being ◽  
Wind Turbine Noise ◽  
Health And Well Being

The aim of this study was to evaluate the perception and annoyance of noise from wind turbines in populated areas of Poland. A questionnaire inquiry was carried out among 517 subjects, aged 18–88, living within 204–1726 m from the nearest wind turbine. For areas where respondents lived, A-weighted sound pressure levels (SPLs) were calculated as the sum of the contributions from the wind power plants in the specific area. It has been shown that the wind turbine noise at the calculated A-weighted SPL of 33–50 dB was perceived as annoying or highly annoying by 46% and 28% of respondents, respectively. Moreover, 34% and 18% of them said that they were annoyed or highly annoyed indoors, respectively. The perception of high annoyance was associated with the A-weighted sound pressure level or the distance from the nearest wind turbine, general attitude to wind farms, noise sensitivity and terrain shape (annoyance outdoors) or road-traffic intensity (annoyance indoors). About 48–66% of variance in noise annoyance rating might be explained by the aforesaid factors. It was estimated that at the distance of 1000 m the wind turbine noise might be perceived as highly annoying outdoors by 43% and 2% of people with negative and positive attitude towards wind turbines, respectively. There was no significant association between noise level (or distance) and various health and well-being aspects. However, all variables measuring health and well-being aspects, including stress symptoms, were positively associated with annoyance related to wind turbine noise.

scholarly journals Annoyance Related to Wind Turbine Noise

2015 ◽  
Vol 39 (1) ◽  
pp. 89-102 ◽  
Author(s):  
Małgorzata Pawlaczyk-łuszczyńska ◽  
Adam Dudarewicz ◽  
Kamil Zaborowski ◽  
Małgorzata Zamojska-Daniszewska ◽  
Małgorzata Waszkowska
Keyword(s):  
Mental Health ◽  
Health Status ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Power Plants ◽  
General Health Questionnaire ◽  
Wind Farms ◽  
Specific Area ◽  
Mental Health Status ◽  
Wind Turbine Noise

Abstract A questionnaire inquiry on response to wind turbine noise was carried out on 361 subjects living in the vicinity of 8 wind farms. Current mental health status of respondents was assessed using Goldberg General Health Questionnaire GHQ-12. For areas where respondents lived, A-weighted sound pressure levels (SPLs) were calculated as the sum of the contributions from the wind power plants in the specific area. Generally, 33.0% of respondents were annoyed outdoors by wind turbine noise at the calculated A-weighted SPL of 31-50 dB, while indoors the noise was annoying to 21.3% of them. The proportion of subjects evaluating the noise produced by operative wind turbines as annoying decreased with increasing the distance from the nearest wind turbine (27.6% at the distance of 400-800 m vs 14.3% at the distance above 800 m, p < 0.016). On the other hand, the higher was the noise level, the greater was the percentage of annoyed respondents (14.0% at SPL up to 40 dB vs 28.1% at SPL of 40-45 dB, p < 0.016). Besides noise and distance categories, subjective factors, such as general attitude to wind turbines, sensitivity to landscape littering and current mental health status, were found to have significant impact on the perceived annoyance. About 50% of variance in annoyance rating might be explained by the aforesaid subjective factors.

Amplitude modulations increase annoyance due to wind turbine noise immission

2021 ◽  
Vol 263 (2) ◽  
pp. 4048-4057
Author(s):  
Christoph Pörschmann ◽  
Stephan Großarth ◽  
Johannes M. Arend ◽  
Sebastian Schmitter ◽  
Dirk Schreckenberg ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Current Literature ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pressure Level ◽  
Wind Turbine Noise ◽  
Control Location ◽  
Noise Characteristics ◽  
Study Sites

Current literature suggests that annoyance of wind turbine noise is strongly affected by amplitude modulations (AM). A survey was carried out at five German residential study sites near wind turbines with a total of about 500 residents to study the effects of AM in more detail. Annoyance, disturbances, and the perception of wind turbine noise characteristics, including AM, were assessed. For each participant, address-related exposure to rating levels of wind turbines was estimated. Further, we carried out headphone-based listening experiments with participants from three of the five study areas and with non-exposed participants from another 'control' location. In the listening experiments, perceived annoyance was rated for varying AM and for different A-weighted sound pressure levels for a total number of 79 subjects. As expected, the results show an increase in annoyance with sound pressure level. Furthermore, annoyance increased significantly with the extent of amplitude modulations. Interestingly, annoyance showed a strong rise as soon as amplitude modulations became audible in the signal and this rise was hardly affected by the sound pressure level. In our contribution, we present comparisons of the results of the survey and the listening experiments.

Effect of Wind Turbine Noise on Workers' Sleep Disorder: A Case Study of Manjil Wind Farm in Northern Iran

2015 ◽  
Vol 14 (02) ◽  
pp. 1550020 ◽  
Author(s):  
Milad Abbasi ◽  
Mohammad Reza Monnazzam ◽  
SayedAbbolfazl Zakerian ◽  
Arsalan Yousefzadeh
Keyword(s):  
Wind Turbine ◽  
Sleep Disorder ◽  
Wind Turbines ◽  
Daytime Sleepiness ◽  
Wind Farm ◽  
Wind Farms ◽  
Sound Level ◽  
Wind Turbine Noise ◽  
The Impact

Noise from wind turbines is one of the most important factors affecting the health, welfare, and human sleep. This research was carried out to study the effect of wind turbine noise on workers' sleep disorder. For this, Manjil Wind Farm, because of the greater number of staff and turbines than other wind farms in Iran, was chosen as case study. A total number of 53 participants took part in this survey. They were classified into three groups of mechanics, security, and official. In this study, daytime sleepiness data of workers were gathered using Epworth Sleepiness Scales (ESS) was used to determine the level of daytime sleepiness among the workers. The 8-h equivalent sound level (LAeq,8h) was measured to determine the individuals' exposure at each occupational group. Finally, the effect of sound, age, and workers' experience on individuals' sleep disorder was analyzed through multiple regression analysis in the R software. The results showed that there was a positive and significant relationship between age, workers' experience, equivalent sound level, and the level of sleep disorder. When age is constant, sleep disorder will increase by 26% as per each 1 dB increase in equivalent sound level. In situations where equivalent sound level is constant, an increase of 17% in sleep disorder is occurred as per each year of work experience. Because of the difference in sound exposure in different occupational groups. The effect of noise in repairing group was about 6.5 times of official group and also 3.4 times of the security group. Sleep disorder effect caused by wind turbine noise in the security group is almost two times more than the official group. Unlike most studies on wind turbine noise that address the sleep disorder among inhabitants nearby wind farms, this study, for the first time in the world, examines the impact of wind turbine noise on sleep disorder of workers who are more closer to wind turbines and exposed to higher levels of noise. So despite all the good benefits of wind turbines, it can be stated that this technology has health risks for all those exposed to its sound. However, further research is needed to confirm the results of this study.

scholarly journals An Aero-acoustic Noise Distribution Prediction Methodology for Offshore Wind Farms

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 18 ◽  
Author(s):  
Jiufa Cao ◽  
Weijun Zhu ◽  
Xinbo Wu ◽  
Tongguang Wang ◽  
Haoran Xu
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Noise Source ◽  
Acoustic Noise ◽  
Turbine Blades ◽  
Wind Farms ◽  
Noise Generation ◽  
Human Beings ◽  
Wind Turbine Noise

Recently attention has been paid to wind farm noise due to its negative health impact, not only on human beings, but also to marine and terrestrial organisms. The current work proposes a numerical methodology to generate a numerical noise map for a given wind farm. Noise generation from single wind turbines as well as wind farms has its basis in the nature of aerodynamics, caused by the interactions between the incoming turbulent flow and the wind turbine blades. Hence, understanding the mechanisms of airfoil noise generation, demands access to sophisticated numerical tools. The processes of modeling wind farm noise include three steps: (1) The whole wind farm velocity distributions are modelled with an improved Jensen’s wake model; (2) The individual wind turbine’s noise is simulated by a semi-empirical wind turbine noise source model; (3) Propagations of noise from all wind turbines are carried out by solving the parabolic wave equation. In the paper, the wind farm wake effect from the Horns Rev wind farm is studied. Based on the resulted wind speed distributions in the wind farm, the wind turbine noise source and its propagation are simulated for the whole wind farm.

scholarly journals A True Hybrid Solar Wind Turbine Electric Generator System for Smaller Hybrid Renewable Energy Power Plants

2018 ◽  
Vol 215 ◽  
pp. 01015
Author(s):  
Mohammad Shafi Al-Ajmi ◽  
Faizal Mustapha ◽  
Mohd. Khairol Anuar b. Mohd Ariffin ◽  
Nurul Amziah Md Yunus ◽  
Izhal Abdul Halin
Keyword(s):  
Solar Wind ◽  
Renewable Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Power Plants ◽  
Electromechanical Coupling ◽  
Wind Farms ◽  
Coupling Mechanism ◽  
Electric Generator ◽  
True Hybrid

Contemporary Hybrid Solar-Wind farms are implemented using separate solar Photovoltaic (PV) cell arrays and wind turbines, where electricity generated from both devices are combined. However, this solution requires a large amount of space to cater for the PV arrays and wind turbines of the system. This paper proposes a new type of renewable energy electric generator with a small power production footprint (PPF) that allows reduction in land usage. The technology introduced in this True Hybrid Wind-Solar (THWS) generator allows for the solar panels to rotate along with a VAWT wind turbine it is attached to through a specially designed electromechanical coupling mechanism. The working principal behind the connections described in this paper. The design of a hybrid circuit module that serves to combine current generated via the solar cells and wind generator and also automatically disconnects inactive wind or solar generators is also described. This is important in order to eliminate unwanted loads generated from the inactive generators from within the THWS itself.

scholarly journals Perceptions of Wind Turbine Noise and Self-Reported Health in Suburban Residential Areas

2021 ◽  
Vol 12 ◽  
Author(s):  
Fei Qu ◽  
Aki Tsuchiya
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Large Scale ◽  
Wind Farms ◽  
Future Research ◽  
Residential Areas ◽  
Noise Mapping ◽  
Wind Turbine Noise ◽  
Reported Health ◽  
The Uk

Wind turbines play an important role in the worldwide mission of producing renewable energy. The development toward integrating large-scale wind turbines in the urban environment has raised concerns over the noise impacts on urban residents. While most of the existing studies on wind turbine noise (WTN) have focused on rural settings, this paper investigates the relationship between WTN, noise perception and self-reported health of people, and controlling for background characteristics of the residents in urbanized areas. Questionnaire surveys were carried out around three suburban wind farms in the UK with 359 respondents. A-weighted sound pressure levels of WTN were predicted using noise mapping, for the most exposed façade of each dwelling of the respondent. The dose-response relationship was found between WTN and annoyance, moderated by age and degree of education. WTN was associated with some aspects of self-reported health, including raised health concerns, having headaches, nausea, and ear discomfort, but was not related to sleep disturbance directly. Noise sensitivity, attitudes to wind energy, and visibility of the wind turbines were found to significantly influence self-reported health. By employing a second variant of the questionnaire with the research aim masked, this study also addressed the focusing effects induced by the questionnaire design. The significant differences in the reported adverse health between questionnaire variants implied focusing bias among the sample who knew the research purpose. This elicited a methodological finding that should be noted in future research.

scholarly journals Novel Application and Validation of a Method to Assess Visual Impacts of Rotating Wind Turbine Blades Within Woodland Areas

2021 ◽  
Vol 89 (1) ◽  
pp. 1-14
Author(s):  
U. Nopp-Mayr ◽  
F. Kunz ◽  
F. Suppan ◽  
E. Schöll ◽  
J. Coppes
Keyword(s):  
Environmental Impact ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Power Plants ◽  
Laser Scanning ◽  
Forest Canopy ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Environmental Impact Assessments ◽  
Independent Field

AbstractIncreasing numbers of wind power plants (WPP) are constructed across the globe to reduce the anthropogenic contribution to global warming. There are, however, concerns on the effects of WPP on human health as well as related effects on wildlife. To address potential effects of WPP in environmental impact assessments, existing models accounting for shadow flickering and noise are widely applied. However, a standardized, yet simple and widely applicable proxy for the visibility of rotating wind turbines in woodland areas was largely lacking up to date. We combined land cover information of forest canopy extracted from orthophotos and airborne laser scanning (LiDAR) data to represent the visibility of rotating wind turbines in five woodland study sites with a high spatial resolution. Performing an in-situ validation in five study areas across Europe which resulted in a unique sample of 1738 independent field observations, we show that our approach adequately predicts from where rotating wind turbine blades are visible within woodlands or not. We thus provide strong evidence, that our approach yields a valuable proxy of the visibility of moving rotor blades with high resolution which in turn can be applied in environmental impact assessments of WPP within woodlands worldwide.

scholarly journals Effect of Wind Turbine Classes on the Electricity Production of Wind Farms in Cyprus Island

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Yiannis A. Katsigiannis ◽  
George S. Stavrakakis ◽  
Christodoulos Pharconides
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farms ◽  
Electricity Production ◽  
Wind Speeds ◽  
Wind Potential

This paper examines the effect of different wind turbine classes on the electricity production of wind farms in two areas of Cyprus Island, which present low and medium wind potentials: Xylofagou and Limassol. Wind turbine classes determine the suitability of installing a wind turbine in a particulate site. Wind turbine data from five different manufacturers have been used. For each manufacturer, two wind turbines with identical rated power (in the range of 1.5 MW–3 MW) and different wind turbine classes (IEC II and IEC III) are compared. The results show the superiority of wind turbines that are designed for lower wind speeds (IEC III class) in both locations, in terms of energy production. This improvement is higher for the location with the lower wind potential and starts from 7%, while it can reach more than 50%.

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