Comprehensive Bird Preservation at Wind Farms

Wind as a clean and renewable energy source has been used by humans for centuries. However, in recent years with the increase in the number and size of wind turbines, their impact on avifauna has become worrisome. Researchers estimated that in the U.S. up to 500,000 birds die annually due to collisions with wind turbines. This article proposes a system for mitigating bird mortality around wind farms. The solution is based on a stereo-vision system embedded in distributed computing and IoT paradigms. After a bird’s detection in a defined zone, the decision-making system activates a collision avoidance routine composed of light and sound deterrents and the turbine stopping procedure. The development process applies a User-Driven Design approach along with the process of component selection and heuristic adjustment. This proposal includes a bird detection method and localization procedure. The bird identification is carried out using artificial intelligence algorithms. Validation tests with a fixed-wing drone and verifying observations by ornithologists proved the system’s desired reliability of detecting a bird with wingspan over 1.5 m from at least 300 m. Moreover, the suitability of the system to classify the size of the detected bird into one of three wingspan categories, small, medium and large, was confirmed.

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A Temporal Boosted YOLO-Based Model for Birds Detection around Wind Farms

Journal of Imaging ◽

10.3390/jimaging7110227 ◽

2021 ◽

Vol 7 (11) ◽

pp. 227

Author(s):

Hiba Alqaysi ◽

Igor Fedorov ◽

Faisal Z. Qureshi ◽

Mattias O’Nils

Keyword(s):

Object Detection ◽

Wind Turbines ◽

Wind Farms ◽

Detection Accuracy ◽

Ensemble Model ◽

Challenging Problem ◽

Training Set ◽

Bird Detection ◽

Set Up ◽

Small Bird

Object detection for sky surveillance is a challenging problem due to having small objects in a large volume and a constantly changing background which requires high resolution frames. For example, detecting flying birds in wind farms to prevent their collision with the wind turbines. This paper proposes a YOLOv4-based ensemble model for bird detection in grayscale videos captured around wind turbines in wind farms. In order to tackle this problem, we introduce two datasets—(1) Klim and (2) Skagen—collected at two locations in Denmark. We use Klim training set to train three increasingly capable YOLOv4 based models. Model 1 uses YOLOv4 trained on the Klim dataset, Model 2 introduces tiling to improve small bird detection, and the last model uses tiling and temporal stacking and achieves the best mAP values on both Klim and Skagen datasets. We used this model to set up an ensemble detector, which further improves mAP values on both datasets. The three models achieve testing mAP values of 82%, 88%, and 90% on the Klim dataset. mAP values for Model 1 and Model 3 on the Skagen dataset are 60% and 92%. Improving object detection accuracy could mitigate birds’ mortality rate by choosing the locations for such establishment and the turbines location. It can also be used to improve the collision avoidance systems used in wind energy facilities.

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Offshore Wind Energy Resource Assessment across the Territory of Oman: A Spatial-Temporal Data Analysis

Sustainability ◽

10.3390/su13052862 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2862

Author(s):

Amer Al-Hinai ◽

Yassine Charabi ◽

Seyed H. Aghay Kaboli

Keyword(s):

Data Analysis ◽

Wind Energy ◽

Wind Turbines ◽

Energy Resource ◽

Wind Farms ◽

Offshore Wind ◽

Wind Data ◽

Offshore Wind Energy ◽

Offshore Wind Turbines ◽

Wind Potential

Despite the long shoreline of Oman, the wind energy industry is still confined to onshore due to the lack of knowledge about offshore wind potential. A spatial-temporal wind data analysis is performed in this research to find the locations in Oman’s territorial seas with the highest potential for offshore wind energy. Thus, wind data are statistically analyzed for assessing wind characteristics. Statistical analysis of wind data include the wind power density, and Weibull scale and shape factors. In addition, there is an estimation of the possible energy production and capacity factor by three commercial offshore wind turbines suitable for 80 up to a 110 m hub height. The findings show that offshore wind turbines can produce at least 1.34 times more energy than land-based and nearshore wind turbines. Additionally, offshore wind turbines generate more power in the Omani peak electricity demand during the summer. Thus, offshore wind turbines have great advantages over land-based wind turbines in Oman. Overall, this work provides guidance on the deployment and production of offshore wind energy in Oman. A thorough study using bankable wind data along with various logistical considerations would still be required to turn offshore wind potential into real wind farms in Oman.

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Wealth of Wind and Visitors: Tourist Industry Attitudes towards Wind Energy Development in Iceland

Land ◽

10.3390/land10070693 ◽

2021 ◽

Vol 10 (7) ◽

pp. 693

Author(s):

Anna Dóra Sæþórsdóttir ◽

Margrét Wendt ◽

Edita Tverijonaite

Keyword(s):

Land Use ◽

Wind Energy ◽

Wind Turbines ◽

Wind Farm ◽

Service Providers ◽

Wind Farms ◽

Energy Development ◽

Tourism Industry ◽

Land Use Conflicts ◽

Wind Energy Development

The interest in harnessing wind energy keeps increasing globally. Iceland is considering building its first wind farms, but its landscape and nature are not only a resource for renewable energy production; they are also the main attraction for tourists. As wind turbines affect how the landscape is perceived and experienced, it is foreseeable that the construction of wind farms in Iceland will create land use conflicts between the energy sector and the tourism industry. This study sheds light on the impacts of wind farms on nature-based tourism as perceived by the tourism industry. Based on 47 semi-structured interviews with tourism service providers, it revealed that the impacts were perceived as mostly negative, since wind farms decrease the quality of the natural landscape. Furthermore, the study identified that the tourism industry considered the following as key factors for selecting suitable wind farm sites: the visibility of wind turbines, the number of tourists and tourist attractions in the area, the area’s degree of naturalness and the local need for energy. The research highlights the importance of analysing the various stakeholders’ opinions with the aim of mitigating land use conflicts and socioeconomic issues related to wind energy development.

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Operation and approximation based on the history of failure modes recorded by SCADA system of Amougdoul Moroccan wind farm using FMECA maintenance model

Wind Engineering ◽

10.1177/0309524x21992456 ◽

2021 ◽

pp. 0309524X2199245

Author(s):

Kawtar Lamhour ◽

Abdeslam Tizliouine

Keyword(s):

Wind Turbines ◽

Wind Farm ◽

Failure Modes ◽

Wind Farms ◽

Scada System ◽

History Of ◽

Criticality Analysis ◽

Maintenance Model ◽

Reliability And Availability ◽

Critical Subsystems

The wind industry is trying to find tools to accurately predict and know the reliability and availability of newly installed wind turbines. Failure modes, effects and criticality analysis (FMECA) is a technique used to determine critical subsystems, causes and consequences of wind turbines. FMECA has been widely used by manufacturers of wind turbine assemblies to analyze, evaluate and prioritize potential/known failure modes. However, its actual implementation in wind farms has some limitations. This paper aims to determine the most critical subsystems, causes and consequences of the wind turbines of the Moroccan wind farm of Amougdoul during the years 2010–2019 by applying the maintenance model (FMECA), which is an analysis of failure modes, effects and criticality based on a history of failure modes occurred by the SCADA system and proposing solutions and recommendations.

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

Conference Papers in Energy ◽

10.1155/2013/750958 ◽

2013 ◽

Vol 2013 ◽

pp. 1-6 ◽

Cited By ~ 2

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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A simulation-driven online scheduling algorithm for the maintenance and operation of wind farm systems

SIMULATION ◽

10.1177/00375497211028605 ◽

2021 ◽

pp. 003754972110286

Author(s):

Eduardo Pérez

Keyword(s):

Wind Turbines ◽

Wind Farm ◽

Computational Study ◽

Scheduling Algorithm ◽

Discrete Event ◽

Wind Farms ◽

Online Scheduling ◽

Maintenance Scheduling ◽

Lead Times ◽

System Specification

Wind turbines experience stochastic loading due to seasonal variations in wind speed and direction. These harsh operational conditions lead to failures of wind turbines, which are difficult to predict. Consequently, it is challenging to schedule maintenance actions that will avoid failures. In this article, a simulation-driven online maintenance scheduling algorithm for wind farm operational planning is derived. Online scheduling is a suitable framework for this problem since it integrates data that evolve over time into the maintenance scheduling decisions. The computational study presented in this article compares the performance of the simulation-driven online scheduling algorithm against two benchmark algorithms commonly used in practice: scheduled maintenance and condition-based monitoring maintenance. An existing discrete event system specification simulation model was used to test and study the benefits of the proposed algorithm. The computational study demonstrates the importance of avoiding over-simplistic assumptions when making maintenance decisions for wind farms. For instance, most literature assumes maintenance lead times are constant. The computational results show that allowing lead times to be adjusted in an online fashion improves the performance of wind farm operations in terms of the number of turbine failures, availability capacity, and power generation.

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Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study

Energies ◽

10.3390/en14144291 ◽

2021 ◽

Vol 14 (14) ◽

pp. 4291

Author(s):

Paxis Marques João Roque ◽

Shyama Pada Chowdhury ◽

Zhongjie Huan

Keyword(s):

Wind Speed ◽

Wind Power ◽

Wind Turbines ◽

Power Output ◽

Wind Farm ◽

Wind Farms ◽

Operating Conditions ◽

Wake Effect ◽

Wind Generators ◽

Wind Potential

District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.

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Synchronization of wind farm power supply into the utility grid

Energy Safety and Energy Economy ◽

10.18635/2071-2219-2021-6-20-25 ◽

2021 ◽

Vol 6 ◽

pp. 20-25

Author(s):

Alexey Bogatyrev

Keyword(s):

Wind Turbines ◽

Power Supply ◽

Distribution System ◽

Wind Farm ◽

Wind Farms ◽

Time Signal ◽

Electricity Distribution ◽

Utility Grid ◽

The Moment ◽

External Time

Wind turbines and wind farms can be connected to the major electricity distribution system. This paper presents the research results on synchronization of wind farm power supply into the utility grid depending on parameters of the grid at the moment. Measurement time gets synchronized with the external time signal delivered from a navigating system like GLONASS. This can help eliminate antiphase operation of individual wind turbines. Connection diagrams and the whole methodology presented in this paper aim to make wind farm power supply into the grid more effective and loss-eliminating.

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Condition Monitoring of Wind Turbines Based on the Scattering Transform of Vibration Data

10.1115/gt2021-60280 ◽

2021 ◽

Author(s):

Junyu Qi ◽

Alexandre Mauricio ◽

Konstantinos Gryllias

Keyword(s):

Condition Monitoring ◽

Wind Turbines ◽

Wind Farms ◽

Operating Conditions ◽

Vibration Data ◽

Bearing Diagnostics ◽

Scattering Transform ◽

The One ◽

Envelope Spectrum ◽

High Effort

Abstract As a renewable, unlimited and free resource, wind energy has been intensively deployed in the past to generate electricity. However, the maintenance of Wind Turbines (WTs) can be challengeable. On the one hand, most wind farms operate in remote areas and on the other hand, the dimension of WTs’ tip/hub/rotor are usually enormous. In order to prevent abrupt breakdowns of WTs, a number of Condition Monitoring (CM) methods have been proposed. Focusing on bearing diagnostics, Squared Envelope Spectrum is one of the most common techniques. Moreover in order to identify the optimum demodulation frequency band, fast Kurtogram, Infogram and Sparsogram are nowadays popular tools evaluating respectively the Kurtosis, the Negentropy and the Sparsity. The analysis of WTs usually requires high effort due to the complexity of the drivetrain and the varying operating conditions and therefore there is still need for research on effective and reliable CM techniques for WT monitoring. Thus the purpose of this paper is to investigate a blind and effective CM approach based on the Scattering Transform. Through the comparison with state of the art techniques, the proposed methodology is found more powerful to detect a fault on six validated WT datasets.

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Simulation of Flow Field on a Large Scale Wind Turbine

Volume 1: Symposia, Parts A and B ◽

10.1115/fedsm2008-55189 ◽

2008 ◽

Author(s):

I. Janajreh ◽

C. Ghenai

Keyword(s):

Flow Field ◽

Wind Energy ◽

Wind Turbine ◽

Wind Turbines ◽

Cross Sections ◽

Large Scale ◽

Wind Farms ◽

Operating Characteristics ◽

Cross Sectional ◽

Capital Costs

Large scale wind turbines and wind farms continue to evolve mounting 94.1GW of the electrical grid capacity in 2007 and expected to reach 160.0GW in 2010 according to World Wind Energy Association. They commence to play a vital role in the quest for renewable and sustainable energy. They are impressive structures of human responsiveness to, and awareness of, the depleting fossil fuel resources. Early generation wind turbines (windmills) were used as kinetic energy transformers and today generate 1/5 of the Denmark’s electricity and planned to double the current German grid capacity by reaching 12.5% by year 2010. Wind energy is plentiful (72 TW is estimated to be commercially viable) and clean while their intensive capital costs and maintenance fees still bar their widespread deployment in the developing world. Additionally, there are technological challenges in the rotor operating characteristics, fatigue load, and noise in meeting reliability and safety standards. Newer inventions, e.g., downstream wind turbines and flapping rotor blades, are sought to absorb a larger portion of the cost attributable to unrestrained lower cost yaw mechanisms, reduction in the moving parts, and noise reduction thereby reducing maintenance. In this work, numerical analysis of the downstream wind turbine blade is conducted. In particular, the interaction between the tower and the rotor passage is investigated. Circular cross sectional tower and aerofoil shapes are considered in a staggered configuration and under cross-stream motion. The resulting blade static pressure and aerodynamic forces are investigated at different incident wind angles and wind speeds. Comparison of the flow field results against the conventional upstream wind turbine is also conducted. The wind flow is considered to be transient, incompressible, viscous Navier-Stokes and turbulent. The k-ε model is utilized as the turbulence closure. The passage of the rotor blade is governed by ALE and is represented numerically as a sliding mesh against the upstream fixed tower domain. Both the blade and tower cross sections are padded with a boundary layer mesh to accurately capture the viscous forces while several levels of refinement were implemented throughout the domain to assess and avoid the mesh dependence.

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