Bird-Community Shifts in Relation to Wind Farms: A Case Study Comparing a Wind Farm, Croplands, and Secondary Forests in Southern Mexico

The wind industry is positioned to contribute significantly to a clean energy future, yet the level of community opposition has at times led to unviable projects. Social acceptance is crucial and can be improved in part through better practice community engagement and benefit-sharing. This case study provides a “snapshot” of current community engagement and benefit-sharing practices for Australian wind farms, with a particular emphasis on practices found to be enhancing positive social outcomes in communities. Five methods were used to gather views on effective engagement and benefit-sharing: a literature review, interviews and a survey of the wind industry, a Delphi panel, and a review of community engagement plans. The overarching finding was that each community engagement and benefit-sharing initiative should be tailored to a community’s context, needs and expectations as informed by community involvement. This requires moving away from a “one size fits all” approach. This case study is relevant to wind developers, energy regulators, local communities and renewable energy-focused non-government organizations. It is applicable beyond Australia to all contexts where wind farm development has encountered conflicted societal acceptance responses.

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Constant and seasonal drivers of bird communities in a wind farm: implications for conservation

PeerJ ◽

10.7717/peerj.2105 ◽

2016 ◽

Vol 4 ◽

pp. e2105 ◽

Cited By ~ 4

Author(s):

Zuzanna M. Rosin ◽

Piotr Skórka ◽

Paweł Szymański ◽

Marcin Tobolka ◽

Andrzej Luczak ◽

...

Keyword(s):

Environmental Variables ◽

Wind Farm ◽

Environmental Planning ◽

Negative Relationship ◽

Wind Farms ◽

Bird Community ◽

Water Bodies ◽

Field Size ◽

Individual Species ◽

Bird Populations

Background.One of the most difficult challenges for conservation biology is to reconcile growing human demands for resources with the rising need for protecting nature. Wind farms producing renewable energy have been recognised to be a threat for birds, but clear directives for environmental planning are still missing.Methods.Point counts were performed to study the relationship between eight environmental variables and bird populations in different parts of a year on the largest Polish wind farm between March 2011 and February 2013. Variables potentially related to species richness (Chao 1 estimator) and the abundance of the entire bird community as well as five selected farmland species were analysed with the use of generalized linear mixed models.Results.Some associations between the studied variables and bird populations were season/year specific, while others had a constant direction (positive or negative) across seasons and/or years. The latter were distance to the nearest turbine, field size, number of wind turbines, proximity of settlements and water bodies. Spatial autocorrelation and counting time were significantly correlated with bird population estimates but the directions of these relationships varied among seasons and years. Associations between abundance of individual species and environmental variables were species-specific.Conclusions.The results demonstrated a constant negative relationship between wind turbine proximity and bird numbers. Other environmental variables, such as field size, proximity of settlements and water bodies that also had constant associations with bird populations across seasons may be taken into account when minimizing adverse effects of wind farm development on birds or choosing optimal locations of new turbines.

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Use of Analytic Hierarchy Process for Wind Farm Installation Region Prioritization–Case Study

Energies ◽

10.3390/en13092284 ◽

2020 ◽

Vol 13 (9) ◽

pp. 2284 ◽

Cited By ~ 1

Author(s):

Rômulo Lemos Bulhões ◽

Eudemário Souza de Santana ◽

Alex Álisson Bandeira Santos

Keyword(s):

Decision Making ◽

Analytic Hierarchy Process ◽

Wind Farm ◽

Greenhouse Gas Emission ◽

Wind Farms ◽

Clean Energy ◽

Poor Quality ◽

Analytic Hierarchy ◽

Hierarchy Process

Electricity generation via renewable sources is emerging as a possible solution to meet the growing demand for electricity worldwide. Additionally, the need to produce clean energy, with little or no pollutants or greenhouse gas emission is paramount. Due to these factors, wind farms are noticeably increasing in number, especially in Brazil. However, the vast size of the country and the poor quality of its infrastructure are among several factors that make it difficult for effective decision-making to accelerate the growth of this segment in Brazil. With the purpose of assisting government agencies, regulatory agencies and other institutions in this area, the use of a multi-criteria selection method called the analytic hierarchy process is proposed here to assist in decision-making and to select priority regions for implementing wind farms. This work focuses on a case study of the state of Bahia, in which 27 territories were selected for an installation priority evaluation. Computational tools were used to hierarchize these chosen territories, including Matlab, for the construction of the computational algorithm. The results indicate the priority pf the regions according to the established criteria, which allows installation locations to be mapped—these could serve as a basis for regional investment.

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Noise assessment of the small-scale wind farm

E3S Web of Conferences ◽

10.1051/e3sconf/201911202011 ◽

2019 ◽

Vol 112 ◽

pp. 02011

Author(s):

Cristian-Gabriel Alionte ◽

Daniel-Constantin Comeaga

Keyword(s):

Power Systems ◽

Large Scale ◽

Wind Farm ◽

Wind Farms ◽

Small Scale ◽

Large Power ◽

Small Power ◽

Noise Assessment ◽

The Impact

The importance of renewable energy and especially of eolian systems is growing. For this reason, we propose the investigation of an important pollutant - the noise, which has become so important that European Commission and European Parliament introduced Directive 2002/49/CE relating to the assessment and management of environmental noise. So far, priority has been given to very large-scale systems connected to national energy systems, wind farms whose highly variable output power could be regulated by large power systems. Nowadays, with the development of small storage capacities, it is feasible to install small power wind turbines in cities of up to 10,000 inhabitants too. As a case study, we propose a simulation for a rural locality where individual wind units could be used. This specific case study is interesting because it provides a new perspective of the impact of noise on the quality of life when the use of this type of system is implemented on a large scale. This option, of distributed and small power wind turbine, can be implemented in the future as an alternative or an adding to the common systems.

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Performance Analysis of Offshore Mono-Pile Wind Turbine Co-Located With Floating Photovoltaic Systems in Shark Bay, Australia

10.1115/omae2021-63852 ◽

2021 ◽

Author(s):

Morteza Bahadori ◽

Hassan Ghassemi

Keyword(s):

Wind Turbine ◽

Hybrid System ◽

Wind Farm ◽

Wind Farms ◽

Power Production ◽

Offshore Wind ◽

Offshore Wind Farm ◽

Offshore Wind Farms ◽

Shark Bay

Abstract In recent years, as more offshore wind farms have been constructed, the possibility of integrating various offshore renewable technologies is increased. Using offshore wind and solar power resources as a hybrid system provides several advantages including optimized marine space utilization, reduced maintenance and operation costs, and relieving wind variability on output power. In this research, both offshore wind and solar resources are analyzed based on accurate data through a case study in Shark Bay (Australia), where bathymetric information confirms using offshore bottom-fixed wind turbine regarding the depth of water. Also, the power production of the hybrid system of co-located bottom-fixed wind turbine and floating photovoltaic are investigated with the technical characteristics of commercial mono-pile wind turbine and photovoltaic panels. Despite the offshore wind, the solar energy output has negligible variation across the case study area, therefore using the solar platform in deep water is not an efficient option. It is demonstrated that the floating solar has a power production rate nearly six times more than a typical offshore wind farm with the same occupied area. Also, output energy and surface power density of the hybrid offshore windsolar system are improved significantly compared to a standalone offshore wind farm. The benefits of offshore wind and solar synergies augment the efficiency of current offshore wind farms throughout the world.

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Community Participation for the Use of Renewable Energies in Ciudad Ixtepec, Oaxaca (2008–2015)

Journal of Risk and Financial Management ◽

10.3390/jrfm13080167 ◽

2020 ◽

Vol 13 (8) ◽

pp. 167

Author(s):

Wendy Sánchez-Casanova ◽

Bendreff Desilus

Keyword(s):

Wind Farm ◽

Wind Farms ◽

Energy Requirements ◽

Structured Interviews ◽

Private Companies ◽

Case Study Methodology ◽

Study Methodology ◽

Isthmus Of Tehuantepec

This paper aims to examine the redefinition of rural actors and practices in the context of the Wind Farm Corridor of the Isthmus of Tehuantepec. That redefinition addresses issues such as the benefits of wind farms, the role of the land in the use of wind energy, requirements for the use of wind, arguments of disagreement with wind farms, manifestations of that disagreement, and the feasibility of community wind farms. Adopting a case study methodology from a qualitative perspective, and “worded” data collected through semi-structured interviews, it was detected that, despite the disapproval of residents of the Oaxacan Isthmus due to a dispossession claimed to the Federal Electricity Commission (Comisión Federal de Electricidad, CFE) and private companies, many of the landowners in Ciudad Ixtepec have decided to become wind entrepreneurs by a community wind farm, facing opposition and mistrust regarding their capacities.

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A case study of wind farm effects using two wake parameterizations in WRF (V3.7) in the presence of low level jets

10.5194/gmd-2020-358 ◽

2020 ◽

Author(s):

Xiaoli G. Larsén ◽

Jana Fischereit

Keyword(s):

Wind Farm ◽

Wrf Model ◽

Wind Farms ◽

Weather Research And Forecasting ◽

Flow Acceleration ◽

Low Level ◽

Low Level Jets ◽

Flight Measurements

Abstract. While the wind farm parameterization by Fitch et al. (2012) in Weather Research and Forecasting (WRF) model has been used and evaluated frequently, the Explicit Wake Parameterization (EWP) by Volker et al. (2015) is less well explored. The openly available high frequency flight measurements from Bärfuss et al. (2019) provide an opportunity to directly compare the simulation results from the EWP and Fitch scheme with in situ measurements. In doing so, this study aims to compliment the recent study by Siedersleben et al. (2020) by (1) comparing the EWP and Fitch schemes in terms of turbulent kinetic energy (TKE) and velocity deficit, together with FINO 1 measurements and Synthetic Aperture Radar (SAR) data and (2) exploring the interactions of the wind farm with Low Level Jets. Both the Fitch and the EWP schemes can capture the mean wind field in the presence of the wind farm consistently and well. However, their skill is limited in capturing the flow acceleration along the farm edge. TKE in the EWP scheme is significantly underestimated, suggesting that an explicit turbine-induced TKE source should be included in addition to the implicit source from shear. The position of the LLJ nose and the shear beneath the jet nose are modified by the presence of wind farms.

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

Fluctuation and Noise Letters ◽

10.1142/s0219477515500200 ◽

2015 ◽

Vol 14 (02) ◽

pp. 1550020 ◽

Cited By ~ 7

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.

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On the wake effect in wind farm power forecasting: a new data-driven approach

E3S Web of Conferences ◽

10.1051/e3sconf/202019708016 ◽

2020 ◽

Vol 197 ◽

pp. 08016

Author(s):

Fabio Famoso ◽

Sebastian Brusca ◽

Antonio Galvagno ◽

Michele Messina ◽

Rosario Lanzafame

Keyword(s):

Power Generation ◽

Wind Power ◽

Wind Farm ◽

Wind Farms ◽

Wind Power Generation ◽

Physical Models ◽

Production Forecast ◽

Innovative Method ◽

Power Forecasting

Wind power generation differs from other energy sources, such as thermal, solar or hydro, due to the inherent stochastic nature of wind. For this reason wind power forecasting, especially for wind farms, is a complex task that cannot be accurately solved with traditional statistical methods or needs large computational systems if physical models are used. Recently, the so-called learning approaches are considered a good compromise among the previous methods since they are able to integrate physical phenomena such as wake effects without presenting heavy computational loads. The present work deals with an innovative method to forecast wind power generation in a wind farm with a combination of GISbased methods, neural network approach and a wake physical model. This innovative method was tested with a wind farm located in Sicily (Italy), used as a case study. It consists of 30 identical wind turbines (850 kW each one), located at different heights, for an overall Power peak of 25 MW. The time series dataset consists of one year with a sampling time of 10 minutes considering wind speeds and wind directions. The output of this innovative model leaded to good results, especially for medium-term overall energy production forecast for the case study.

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The Influence of Climate Parameters on Maintenance of Wind Farms—A Galician Case Study

Sensors ◽

10.3390/s21010040 ◽

2020 ◽

Vol 21 (1) ◽

pp. 40

Author(s):

José A. Orosa ◽

Ángel M. Costa ◽

Diego Vergara ◽

Feliciano Fraguela

Keyword(s):

Wind Farm ◽

Extreme Values ◽

Wind Farms ◽

Working Hours ◽

Weather Conditions ◽

Electrical Network ◽

Economic Implications ◽

Power Regulation ◽

The Cost

There are different monitoring procedures in wind farms with two main objectives: (i) to improve energy production by the capability of the national electrical network and (ii) to reduce the stooped hours due to preventive and or corrective maintenance activities. In this sense, different sensors are employed to sample in real-time the working conditions of equipment, the electrical production and the weather conditions. Despite this, just the anemometer measurement can be related to the more important errors of interruption of power regulation and anemometer errors. Both errors are related to gusty winds and contribute to more than 33% of the cost of a wind farm. The present paper reports some mathematical relations between weather and maintenance but there are no extreme values of each variable that let us predict a near failure and its corresponding loss of working hours. To achieve this, statistical analysis identifies the relation between weather variables and errors and different models are obtained. What is more, due to the difficulty and economic implications involving the implementation of complex algorithms and techniques of artificial intelligence, it is still a challenge to optimize this process. Finally, the obtained results show a particular case study that can be extrapolated to other wind farms after different case studies to adjust the model to different weather regions, and serve as a useful tool for weather maintenance.

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