To meet the expanding land use required for wind energy development, a better understanding of the effects on terrestrial animals' responses to such development is required. Using GPS-data from 50 freely ranging female reindeer () in the Malå reindeer herding community, Sweden, we determined reindeer calving sites and estimated reindeer habitat selection using resource selection functions (RSF). RSFs were estimated at both second- (selection of home range) and third-order (selection within home range) scale in relation to environmental variables, wind farm (WF) development phase (before construction, construction, and operation), distance to the WFs and at the second-order scale whether the wind turbines were in or out of sight of the reindeer. We found that the distance between reindeer calving site and WFs increased during the operation phase, compared to before construction. At both scales of selection, we found a significant decrease in habitat selection of areas in proximity of the WFs, in the same comparison. The results also revealed a shift in home range selection away from habitats where wind turbines became visible toward habitats where the wind turbines were obscured by topography (increase in use by 79% at 5 km). We interpret the reindeer shift in home range selection as an effect of the wind turbines per se. Using topography and land cover information together with the positions of wind turbines could therefore help identify sensitive habitats for reindeer and improve the planning and placement of WFs. In addition, we found that operation phase of these WFs had a stronger adverse impact on reindeer habitat selection than the construction phase. Thus, the continuous running of the wind turbines making a sound both day and night seemed to have disturbed the reindeer more than the sudden sounds and increased human activity during construction work.
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http://dx.doi.org/10.1002/ece3.4476 | DOI Listing |
Sensors (Basel)
December 2024
Faculty of Mechanical Engineering and Robotics, AGH University of Krakow, 30-059, Krakow, Poland.
In this study, a predictive maintenance (PdM) system focused on feature selection for the detection and classification of simulated defects in wind turbine blades has been developed. Traditional PdM systems often rely on numerous, broadly chosen diagnostic indicators derived from vibration data, yet many of these features offer little added value and may even degrade model performance. General feature selection methods might not be suitable for PdM solutions, as information regarding observed faults is often misinterpreted or lost.
View Article and Find Full Text PDFAnimals (Basel)
December 2024
School of Science & Technology, University of New England, Armidale, NSW 2351, Australia.
Human interaction with birds has never been more positive and supported by so many private citizens and professional groups. However, direct mortality of birds from anthropogenic causes has increased and has led to significant annual losses of birds. We know of the crucial impact of habitat loss on the survival of birds and its effects on biodiversity.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, 35111, Egypt.
The research study objective seeks to improve the efficiency of wind turbines using state-of-the-art techniques in the domain of ML, making wind energy the key player in fashioning a favorable future. Wind Turbine Health Monitoring (WTHM) is typically achieved through either vibration analysis or by using Supervisory Control and Data Acquisition (SCADA) data of wind turbines, wherein conventional fault pattern identification is a time-consuming, guesswork process. This work proposed an intelligent automated approach to early fault detection through the implementation of the HARO (Huber Adam Regression Optimizer) model, which combines Transformer networks with Lasso Regression and the Adam optimizer.
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January 2025
Department of Electrical Engineering, College of Engineering, King Khalid University, P.O. Box 394, 61421, Abha, KSA, Saudi Arabia.
The direct power control (DPC) algorithm is one of the most popular linear techniques used to implement notable controllers, known for their simplicity and fast dynamic response. However, this approach has drawbacks that cause a decrease in the current quality and disturbances in the network. Therefore, this experimental work presents a simple and efficient solution that uses a proportional-integral regulator based on a genetic algorithm to regulate the power quality.
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January 2025
College of Engineering, Arab Academy for Science, Technology and Maritime Transport, Alexandria, Egypt.
Bladeless wind turbines face operational limitations due to the lock-in phenomenon. This study introduces two novel mechanisms for designing bladeless wind turbines to address this issue, enabling operation across a broad wind speed range from 2 to 10 m/s while ensuring that lock-in conditions are satisfied at any wind speed within this range. The study aims to maintain optimal performance without any decline that is observed in conventional bladeless wind turbines by controlling the turbine's natural frequency through implementing these mechanisms, either by adjusting the effective length of the stand or by incorporating an additional mass in the hollow mast, or both.
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