AbstractWind energy requires accurate forecasts for adequate integration into the electric grid system. In addition, global atmospheric models are not able to simulate local winds in complex terrain, where wind farms are sometimes placed. For this reason, the use of mesoscale models is vital for estimating wind speed at wind turbine hub height. In this regard, the Weather Research and Forecasting (WRF) Model allows a user to apply different initial and boundary conditions as well as physical parameterizations. In this research, a sensitivity analysis of several physical schemes and initial and boundary conditions was performed for the Alaiz mountain range in the northern Iberian Peninsula, where several wind farms are located. Model performance was evaluated under various atmospheric stabilities and wind speeds. For validation purposes, a mast with anemometers installed at 40, 78, 90, and 118 m above ground level was used. The results indicate that performance of the Global Forecast System analysis and European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) as initial and boundary conditions was similar, although each performed better under certain meteorological conditions. With regard to physical schemes, there is no single combination of parameterizations that performs best during all weather conditions. Nevertheless, some combinations have been identified as inefficient, and therefore their use is discouraged. As a result, the validation of an ensemble prediction system composed of the best 12 deterministic simulations shows the most accurate results, obtaining relative errors in wind speed forecasts that are <15%.
Journal of Applied Meteorology and Climatology – American Meteorological Society
Published: Mar 4, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera