scholarly journals Predicting migration routes for three species of migratory bats using species distribution models

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11177
Author(s):  
Jamin G. Wieringa ◽  
Bryan C. Carstens ◽  
H Lisle Gibbs
Keyword(s):  
North America ◽  
Wind Farm ◽  
Wind Farms ◽  
Small Scale ◽  
Migration Routes ◽  
Distribution Models ◽  
Global Biodiversity Information Facility ◽  
Lasiurus Borealis ◽  
Data Points ◽  
Seasonal Basis

Understanding seasonal variation in the distribution and movement patterns of migratory species is essential to monitoring and conservation efforts. While there are many species of migratory bats in North America, little is known about their seasonal movements. In terms of conservation, this is important because the bat fatalities from wind energy turbines are significant and may fluctuate seasonally. Here we describe seasonally resolved distributions for the three species that are most impacted by wind farms (Lasiurus borealis (eastern red bat), L. cinereus (hoary bat) and Lasionycteris noctivagans (silver-haired bat)) and use these distributions to infer their most likely migratory pathways. To accomplish this, we collected 2,880 occurrence points from the Global Biodiversity Information Facility over five decades in North America to model species distributions on a seasonal basis and used an ensemble approach for modeling distributions. This dataset included 1,129 data points for L. borealis, 917 for L. cinereus and 834 for L. noctivagans. The results suggest that all three species exhibit variation in distributions from north to south depending on season, with each species showing potential migratory pathways during the fall migration that follow linear features. Finally, we describe proposed migratory pathways for these three species that can be used to identify stop-over sites, assess small-scale migration and highlight areas that should be prioritized for actions to reduce the effects of wind farm mortality.

scholarly journals Noise assessment of the small-scale wind farm

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.

scholarly journals Integrating social and ecological research on the impacts of offshore wind farms in North America | Preprint for book: Researching people and the sea: methodologies and traditions, Chapter: 11, Palgrave

2020 ◽  
Author(s):  
Talya ten Brink ◽  
Tracey Dalton ◽  
Julia Livermore
Keyword(s):  
North America ◽  
Wind Farm ◽  
Early Stage ◽  
Wind Farms ◽  
Demersal Fish ◽  
Interdisciplinary Studies ◽  
Offshore Wind ◽  
Ecological Data ◽  
Science Data ◽  
Biological Studies

Ten Brink et. al. identified insights from their social-ecological study on the impacts of the first offshore wind farm in North America. They analysed ecological data from demersal fish trawl and lobster surveys and qualitative social science data from commercial and recreational fishermen. They found that challenges include the integration of different types of data, temporal and spatial ranges of data, framing of the studies, and mismatch in fish species targeted. Benefits include more comprehensive capture of impacts and guidance on how to design better biological studies. Early stage collaboration during research design, aligned goals, and comprehensive planning can allow for more integrated data collection and analysis and have relevance to other interdisciplinary studies of marine and fisheries domains.

scholarly journals Benefits of Energy Storage Systems for Small-Scale Wind Farm Development in Latvia

2021 ◽  
Vol 58 (2) ◽  
pp. 11-18
Author(s):  
E. Groza ◽  
M. Balodis ◽  
K. Gulbis ◽  
J. Dirba
Keyword(s):  
Energy Storage ◽  
Small Area ◽  
Wind Farm ◽  
Storage Systems ◽  
Wind Farms ◽  
Small Scale ◽  
High Wind ◽  
Energy Storage Systems ◽  
Grid Connection ◽  
Wind Potential

Abstract The paper covers the main aspects and restrictions on siting small-scale wind farms in Latvia and benefits of using energy storage systems with small-scale wind farms. The restrictions of siting have been analysed. Grid connection restrictions are addressed as the main issues for small-scale wind farm development in Latvia. Two small-scale wind farm models with similar properties have been made and analysed within the framework of the research. The paper proposes the idea for maximising the production of small-scale wind farm in a small area site with high wind potential.

scholarly journals CFD-based surrogate modelling of urban wind farms using artificial neural networks: double rotor arrangements

2021 ◽  
Vol 2042 (1) ◽  
pp. 012093
Author(s):  
Sadra Sahebzadeh ◽  
Abdolrahim Rezaeiha ◽  
Hamid Montazeri
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Vertical Axis ◽  
Power Coefficient ◽  
Vertical Axis Wind Turbine ◽  
Power Performance ◽  
Marquardt Algorithm ◽  
Data Points ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Abstract Extensive characterization studies are required to identify optimal wind farm layouts and achieve high power density, i.e., power per land area. Performing such studies using experimental or high-fidelity numerical methods can be timely and computationally expensive. To alleviate this obstacle, surrogate models can be developed to mimic the behavior of the simulation/experiment. In this paper, a shallow feed-forward artificial neural network (ANN) surrogate model is developed. The Levenberg-Marquardt algorithm is used to train a model with 3 layers and 10 hidden nodes. The model correlates the arrangement of a double-rotor vertical axis wind turbine array, as the fundamental generating cell of the wind farm, with its overall power performance. The inputs are the relative distance (R) and angle (®) between the rotors, and the output is the overall power coefficient of the array. In total, 96 CFD-simulated arrangements are used as data points to train, validate and test the model. The trained model has a mean square error of 2.10 × 10-5 and R-squared of 0.99, indicating its accuracy and generalizability. The average and maximum errors are 3% and 10%, respectively. The employed method can be expanded to accommodate more rotors towards optimal urban wind farm layout design.

scholarly journals Floating Offshore Vertical Axis Wind Turbines: Opportunities, Challenges and Way Forward

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8000
Author(s):  
Abel Arredondo-Galeana ◽  
Feargal Brennan
Keyword(s):  
Wind Turbines ◽  
Deep Water ◽  
Wind Farm ◽  
Structural Integrity ◽  
Wind Farms ◽  
Vertical Axis ◽  
Offshore Wind ◽  
Small Scale ◽  
Offshore Wind Farms ◽  
Vertical Axis Wind Turbines

The offshore wind sector is expanding to deep water locations through floating platforms. This poses challenges to horizontal axis wind turbines (HAWTs) due to the ever growing size of blades and floating support structures. As such, maintaining the structural integrity and reducing the levelised cost of energy (LCoE) of floating HAWTs seems increasingly difficult. An alternative to these challenges could be found in floating offshore vertical axis wind turbines (VAWTs). It is known that VAWTs have certain advantages over HAWTs, and in fact, some small-scale developers have successfully commercialised their onshore prototypes. In contrast, it remains unknown whether VAWTs can offer an advantage for deep water floating offshore wind farms. Therefore, here we present a multi-criteria review of different aspects of VAWTs to address this question. It is found that wind farm power density and reliability could be decisive factors to make VAWTs a feasible alternative for deep water floating arrays. Finally, we propose a way forward based on the findings of this review.

scholarly journals Wind Energy Generation Assessment at Specific Sites in a Peninsula in Malaysia Based on Reliability Indices

Processes ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 399 ◽  
Author(s):  
Athraa Ali Kadhem ◽  
Noor Izzri Abdul Wahab ◽  
Ahmed N. Abdalla
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Sequential Monte Carlo ◽  
Wind Farms ◽  
Test System ◽  
Peninsular Malaysia ◽  
Distribution Models ◽  
Reliability Indices ◽  
Wind Energy Generation ◽  
The Impact

This paper presents a statistical analysis of wind speed data that can be extremely useful for installing a wind generation as a stand-alone system. The main objective is to define the wind power capacity’s contribution to the adequacy of generation systems for the purpose of selecting wind farm locations at specific sites in Malaysia. The combined Sequential Monte Carlo simulation (SMCS) technique and the Weibull distribution models are employed to demonstrate the impact of wind power in power system reliability. To study this, the Roy Billinton Test System (RBTS) is considered and tested using wind data from two sites in Peninsular Malaysia, Mersing and Kuala Terengganu, and one site, Kudat, in Sabah. The results showed that Mersing and Kudat were best suitable for wind sites. In addition, the reliability indices are compared prior to the addition of the two wind farms to the considered RBTS system. The results reveal that the reliability indices are slightly improved for the RBTS system with wind power generation from both the potential sites.

Multi-Scale Measurements in Wind Farms in Complex and Flat Terrain

2015 ◽  
Author(s):  
M. Zendehbad ◽  
N. Chokani ◽  
R. S. Abhari
Keyword(s):  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Wake Flow ◽  
Small Scale ◽  
Energy Yield ◽  
Lidar System ◽  
Flow Measurements ◽  
Flat Terrain

Large-scale (that is over the kilometre scale of a whole wind farm) and small-scale (over the metre scale of an individual wind turbine) wind flow measurements are made with a mobile-based LIDAR system. The large-scale measurements detail the multiple wakes in the wind farm, including both single and double wakes, that result in up to 70% less power generation for a given wind direction, and 2.5% loss of the wind farm’s annual energy yield. The small-scale measurements show that there is a non-uniform work extraction of the turbine across the vertical extent of the wind turbine rotor. This non-uniform work extraction is accompanied by an upward pitching of the flow that is as much as 50° immediately downstream of the turbine and reduces to 10° two diameters downstream. Measurements with the mobile-based LIDAR system are made in both complex and flat terrains. A comparison of the wake profiles show that whereas in complex terrain the profiles are self-similar up to two-and-half rotor diameters downstream, this is not the case in flat terrain. It is shown that these measurements, which are made at the full-scale Reynolds number in the field, may be useful to support the development of wake flow prediction tools.

scholarly journals Autumn migration of soaring birds in North Dobrogea, Romania: a study with implications for wind farm development

2012 ◽  
Vol 20 (2) ◽  
pp. 73-85 ◽  
Author(s):  
Attila Fülöp ◽  
Lőrinc Bărbos ◽  
Gábor M. Bóné ◽  
Szilárd J. Daróczi ◽  
Luca A. Dehelean ◽  
...  
Keyword(s):  
Wind Farm ◽  
Bird Migration ◽  
Negative Impact ◽  
Significant Proportion ◽  
Wind Farms ◽  
Local Scale ◽  
Autumn Migration ◽  
Migration Routes ◽  
Soaring Birds ◽  
Energy Exploitation

Abstract In Dobrogea, a core area for wind energy exploitation in Romania, existing knowledge regarding the intensity and pattern of bird migration is limited. In the absence of enumerated data, wind farms may be constructed in areas where large aggregations of migrants pass. In this study we recorded the intensity of the autumn migration of soaring birds in three locations within the Măcin Mountains, where wind farms are planned to be built. The locations chosen were at Văcăreni, Greci and Cerna villages. Furthermore we categorized all migrating individuals as threatened or non-threatened by the planned wind farms, based on their migration routes and height at local scale. At Văcăreni 4.716 individuals were counted, 3.394 raptors and 1.322 non-raptors, at Greci 2.387 individuals, 2.064 raptors and 323 non-raptors, and finally at Cerna, 5.268 individuals, 4.529 raptors and 739 non-raptors. At all three sites a significant proportion of birds, both raptors and non-raptors, were found to be threatened by the proposed wind farms. At Văcăreni 68.33% of raptors and 84.95% of non-raptors were at threat, at Greci 44.48% and 54.18% respectively, and at Cerna 59.37% and 94.86%. As such we conclude that intensive migration occurs in North Dobrogea and wind farms would have a considerable negative impact on migrants in the studied areas

Selection of a leading edge noise prediction method for PNoise

2018 ◽  
pp. 214-223
Author(s):  
AM Faria ◽  
MM Pimenta ◽  
JY Saab Jr. ◽  
S Rodriguez
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Prediction Method ◽  
Leading Edge ◽  
Wind Farms ◽  
Broadband Noise ◽  
Turbulence Energy ◽  
Noise Prediction ◽  
Migration Routes ◽  
Turbulent Inflow

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.

Evaluating Community Engagement and Benefit-Sharing Practices in Australian Wind Farm Development

2017 ◽  
Vol 1 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Nina Lansbury Hall ◽  
Jarra Hicks ◽  
Taryn Lane ◽  
Emily Wood
Keyword(s):  
Community Engagement ◽  
Community Involvement ◽  
Wind Farm ◽  
Social Acceptance ◽  
Wind Farms ◽  
Clean Energy ◽  
Benefit Sharing ◽  
Delphi Panel ◽  
Government Organizations

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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