Based on the Van der Hoven's seminal work, wind power industry has adopted the 10 minutes mean time as the proper sampling to estimate resource assessment. However, research within the literature questions the generalization of the 10 minutes as a standard measure of minima dispersion due to the particular geographic characteristics where the measurements took place. In this work the power spectrum of a high-frequency wind speed time series is analyzed and its influence over the resource assessment in the region of La Ventosa, Oaxaca, Mexico. Power spectrum analysis from a monthly, seasonal, and annual time series results show a defined synoptic-scale, diurnal, and semi-diurnal variations, which changes in amplitude throughout the year.To ...
Renewable energy sources are increasing in order to provide power with minimal envi- ronmental impac...
Wind by its very nature is a variable element. Its variation is different on different timescales an...
In this study, we use a k-mean clustering approach to investigate the weather patterns responsible f...
Understanding near-surface wind variability is crucial to support wind power penetration on national...
In the fundamental stage of resource assessment, high-quality wind speed measurements are required t...
Most publicly available wind data are aggregated to a temporal resolution of 30 or 60 min. This is a...
Renewable energies play a significant role to mitigate the impacts of climate change. In countries l...
textThe research presented herein concentrates on the quantification, assessment and forecasting of ...
This thesis describes work on the statistics of the temporal and spatial variation of wind power in ...
The desire to reduce dependence on fossil fuels is resulting in numerous policy incentives for incre...
Atmospheric reanalyses are widely used for understanding the past and present climate. They have bec...
Wind resources are increasingly being investigated as a clean alternative for generating energy. Thi...
For the purposes of understanding the impacts on the electricity network, estimates of hourly aggreg...
University of Minnesota Ph.D. dissertation. August 2020. Major: Geography. Advisor: Katherine Klink....
The intermittent nature of the wind resource, together with short-term power fluctuations, are the t...
Renewable energy sources are increasing in order to provide power with minimal envi- ronmental impac...
Wind by its very nature is a variable element. Its variation is different on different timescales an...
In this study, we use a k-mean clustering approach to investigate the weather patterns responsible f...
Understanding near-surface wind variability is crucial to support wind power penetration on national...
In the fundamental stage of resource assessment, high-quality wind speed measurements are required t...
Most publicly available wind data are aggregated to a temporal resolution of 30 or 60 min. This is a...
Renewable energies play a significant role to mitigate the impacts of climate change. In countries l...
textThe research presented herein concentrates on the quantification, assessment and forecasting of ...
This thesis describes work on the statistics of the temporal and spatial variation of wind power in ...
The desire to reduce dependence on fossil fuels is resulting in numerous policy incentives for incre...
Atmospheric reanalyses are widely used for understanding the past and present climate. They have bec...
Wind resources are increasingly being investigated as a clean alternative for generating energy. Thi...
For the purposes of understanding the impacts on the electricity network, estimates of hourly aggreg...
University of Minnesota Ph.D. dissertation. August 2020. Major: Geography. Advisor: Katherine Klink....
The intermittent nature of the wind resource, together with short-term power fluctuations, are the t...
Renewable energy sources are increasing in order to provide power with minimal envi- ronmental impac...
Wind by its very nature is a variable element. Its variation is different on different timescales an...
In this study, we use a k-mean clustering approach to investigate the weather patterns responsible f...