Many mountainous regions with high wind energy potential are characterized by multi-scale variabilities of vegetation in both spatial and time dimensions, which strongly affect the spatial distribution of wind resource and its time evolution. To this end, we developed a coupled interdisciplinary modeling framework capable of assessing the shifts in wind energy potential following land-use driven vegetation dynamics in complex mountain terrain. It was applied to a case study area in the Romanian Carpathians. The results show that the overall shifts in wind energy potential following the changes of vegetation pattern due to different land-use policies can be dramatic. This suggests that the planning of wind energy project should be integrated with the land-use planning at a specific site to ensure that the expected energy production of the planned wind farm can be reached over its entire lifetime. Moreover, the changes in the spatial distribution of wind and turbulence under different scenarios of land-use are complex, and they must be taken into account in the micro-siting of wind turbines to maximize wind energy production and minimize fatigue loads (and associated maintenance costs). The proposed new modeling framework offers, for the first time, a powerful tool for assessing long-term variability in local wind energy potential that emerges from land-use change driven vegetation dynamics over complex terrain. Following a previously unexplored pathway of cause-effect relationships, it demonstrates a new linkage of agro- and forest policies in landscape development with an ultimate trade-off between renewable energy production and biodiversity targets. Moreover, it can be extended to study the potential effects of micro-climatic changes associated with wind farms on vegetation development (growth and patterning), which could in turn have a long-term feedback effect on wind resource distribution in mountainous regions.
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http://dx.doi.org/10.1016/j.scitotenv.2018.05.083 | DOI Listing |
Heliyon
January 2025
MaREI Centre, University College Cork, Cork, Ireland.
Airborne wind energy is an emerging technology that can harness stronger and more consistent winds in higher altitudes using less mechanical and civil infrastructures than conventional wind energy systems. This article outlines a techno-economic study on using this technology for reverse osmosis seawater desalination in which a semi-permeable membrane process is used to remove salts and contaminants from water. To understand the techno-economic feasibility of such a system, this research work studies a 2 MW airborne wind-driven reverse osmosis plant.
View Article and Find Full Text PDFHeliyon
January 2025
Mechanical Power Engineering Department, Faculty of Engineering - Mataria, Helwan University, Cairo, 11718, Egypt.
Wind turbine control is critical in power generation from wind, thus assuring great efficiency and cost-effectiveness. This has been a subject of intense research, and its advancements are critical to developing even better and efficient wind turbines. This research looks at several passive flow control mechanisms for horizontal wind turbines.
View Article and Find Full Text PDFACS Sustain Resour Manag
January 2025
Sandia National Laboratories, Albuquerque, New Mexico 87123, United States.
Wind energy offers a low emission source of energy while also being among the cheapest forms of electricity generation in the United States. While most materials in a wind turbine can be recycled at the end of their life, large composite blades are often treated as waste, leading to potential strains on regional landfills, a loss of durable materials, and forfeiture of embodied energy. Numerous approaches exist for recycling composite wind blades at various levels of technological and commercial maturity.
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January 2025
Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado 80401, United States.
We propose a generic, modular framework to optimize the placement of point-in-space continuous monitoring system sensors on oil and gas sites aiming to maximize the methane emission detection efficiency. Our proposed framework substantially expands the problem scale compared to previous related studies and can be adapted for different objectives in sensor placement. This optimization framework is comprised of five steps: (1) simulate emission scenarios using site-specific wind and emission information; (2) set possible sensor locations under consideration of the site layout and any site-specific constraints; (3) simulate methane concentrations for each pair of emission scenario and possible sensor location; (4) determine emissions detection based on the site-specific simulated concentrations; and (5) select the best subset of sensor locations, under a given number of sensors to place, using genetic algorithms combined with Pareto optimization.
View Article and Find Full Text PDFInnovation (Camb)
January 2025
Regional Climate Group, Department of Earth Sciences, University of Gothenburg, 40530 Gothenburg, Sweden.
Near-surface wind speed (NSWS), a determinant of wind energy, is influenced by both natural and anthropogenic factors. However, the specific impacts of volcanic eruptions on NSWS, remain unexplored. Our simulations spanning the last millennium reveal a consistent 2-year global NSWS reduction following 10 major historical eruptions.
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