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Quantification And Reduction Of Uncertainty Of Model Predictions Of Wind Turbines And Plants Via Highfidelity Simulations Daniel V Foti

Name: Quantification And Reduction Of Uncertainty Of Model Predictions Of Wind Turbines And Plants Via Highfidelity Simulations Daniel V Foti
SKU: BELL-37465452
Price: 31.00 USD
Availability: InStock
Rating: 4.8 (34 reviews)

SKU: BELL-37465452

Quantification And Reduction Of Uncertainty Of Model Predictions Of Wind Turbines And Plants Via Highfidelity Simulations Daniel V Foti

$ 31.00 ~~$ 45.00~~ (-31%)

4.8

34 reviews

Quantification And Reduction Of Uncertainty Of Model Predictions Of Wind Turbines And Plants Via Highfidelity Simulations Daniel V Foti instant download after payment.

Publisher: UNIVERSITY OF MINNESOTA

File Extension: PDF

File size: 27.68 MB

Pages: 269

Author: Daniel V. Foti

Language: English

Year: 2016

Product desciption

Quantification And Reduction Of Uncertainty Of Model Predictions Of Wind Turbines And Plants Via Highfidelity Simulations Daniel V Foti by Daniel V. Foti instant download after payment.

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.