Can I read Quantification and Reduction of Uncertainty of Model Predictions of Wind Turbines and Plants via High-fidelity Simulations on EtoBox?

Quantification and Reduction of Uncertainty of Model Predictions of Wind Turbines and Plants via High-fidelity Simulations by Daniel V. Foti is a nonfiction available to read on EtoBox.

What is Quantification and Reduction of Uncertainty of Model Predictions of Wind Turbines and Plants via High-fidelity Simulations about?

With increasing energy demands renewable energy sources are continuing to receiveattention and investment to become a larger source for electricity production. Today,wind generated power through wind turbines creates 4% of the electricity in the UnitedStates. The wind energy share of the electricity market is expected to grow rapidly asthe United States Department of Energy goal is to reach 20% wind generated electricityby 2030. Computational models for wind plants can be used to predict wind plantperformance and optimize the turbine placement and controls. However, uncertaintiesassociated with such models, due to, among others, the computationally expedient simplificationsneed to be carefully assessed, quantified and reduced.

Who reads Quantification and Reduction of Uncertainty of Model Predictions of Wind Turbines and Plants via High-fidelity Simulations?

Author

Daniel V. Foti

Publisher

UNIVERSITY OF MINNESOTA

Published

2016

Language

EN

Category

nonfiction

Subjects

Technology, Stem