Large-scale use of wind power can alter local and global climate by extracting kinetic energy and altering turbulent transport in the atmospheric boundary layer. We report climate-model simulations that address the possible climatic impacts of wind power at regional to global scales by using two general circulation models and several parameterizations of the interaction of wind turbines with the boundary layer. We find that very large amounts of wind power can produce nonnegligible climatic change at continental scales. Although large-scale effects are observed, wind power has a negligible effect on global-mean surface temperature, and it would deliver enormous global benefits by reducing emissions of CO(2) and air pollutants. Our results may enable a comparison between the climate impacts due to wind power and the reduction in climatic impacts achieved by the substitution of wind for fossil fuels.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC526278 | PMC |
| http://dx.doi.org/10.1073/pnas.0406930101 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Boundary Layer Control with a Plasma Actuator Utilizing a Large GND Mesh Electrode and Two HV Electrode Configurations.
Sensors (Basel)
December 2024
Faculty of Management, Lublin University of Technology, 20-618 Lublin, Poland.
This article presents the results of experimental studies on the influence of the geometry of high-voltage plasma actuator electrodes on the change in flow in the boundary layer and their influence on the change in the lift coefficient. The plasma actuator used in the described experimental studies has a completely different structure. The experimental model of the plasma actuator uses a large mesh ground electrode and different geometries of the high-voltage electrodes, namely copper solid electrodes and mesh electrodes (the use of mesh electrodes, large GND and HV is a new solution).
View Article and Find Full Text PDFDust deposition characteristics on photovoltaic arrays investigated through wind tunnel experiments.
Sci Rep
January 2025
School of Physics, Ningxia University, Yinchuan, 750021, China.
Optimizing the installation parameters of photovoltaic panels in a photovoltaic array to reduce dust accumulation, thereby enhancing their power generation, is a crucial research topic in the construction of solar power stations in desert regions. Utilizing a series of wind tunnel experiments on a photovoltaic array comprising four equally sized panels, this study assessed how variations in tilt angle, mounting height, spacing, and incoming flow direction influence both the accumulation mass of dust and the particle size distribution in a photovoltaic array. The results indicate that the dust accumulation on the first panel exponential growth with increasing tilt angle, incoming flow angles, and height, while subsequent panels displayed a trend of initial increase followed by a decrease, with a maximum increasing ratio achieved at specific installation configurations, the difference of dust mass on each panel can even be several times.
View Article and Find Full Text PDFUnraveling climate change-induced compound low-solar-low-wind extremes in China.
Natl Sci Rev
January 2025
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
China's pursuit of carbon neutrality targets hinges on a profound shift towards low-carbon energy, primarily reliant on intermittent and variable, yet crucial, solar and wind power sources. In particular, low-solar-low-wind (LSLW) compound extremes present a critical yet largely ignored threat to the reliability of renewable electricity generation. While existing studies have largely evaluated the impacts of average climate-induced changes in renewable energy resources, comprehensive analyses of the compound extremes and, particularly, the underpinning dynamic mechanisms remain scarce.
View Article and Find Full Text PDFMachine learning boosts wind turbine efficiency with smart failure detection and strategic placement.
Sci 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.
View Article and Find Full Text PDFExperimental analysis of genetic algorithm-enhanced PI controller for power optimization in multi-rotor variable-speed wind turbine systems.
Sci Rep
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.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!