Quantification and reduction of uncertainty of model predictions of wind turbines and plants via high-fidelity simulations PDF
269 Pages·2016·27.6779 MB·other
Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.
Preview Quantification and reduction of uncertainty of model predictions of wind turbines and plants via high-fidelity simulations
Description:
With increasing energy demands renewable energy sources are continuing to receive
attention and investment to become a larger source for electricity production. Today,
wind generated power through wind turbines creates 4% of the electricity in the United
States. The wind energy share of the electricity market is expected to grow rapidly as
the United States Department of Energy goal is to reach 20% wind generated electricity
by 2030. Computational models for wind plants can be used to predict wind plant
performance and optimize the turbine placement and controls. However, uncertainties
associated with such models, due to, among others, the computationally expedient simplifications
need to be carefully assessed, quantified and reduced.
See more
The list of books you might like
Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.
