Data Science for Wind Energy

1st Edition

Yu Ding

Chapman and Hall/CRC
June 6, 2019 Forthcoming
Reference - 388 Pages - 103 B/W Illustrations
ISBN 9781138590526 - CAT# K386763

For Instructors Request Inspection Copy

was $119.95

USD$101.96

SAVE ~$17.99

Add to Wish List
FREE Standard Shipping!

Summary

This book provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, from near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods will be covered, including time series models, spatio-temporal model and analysis, kernel regression, decision trees, k-NN, splines, Bayesian inference, and MCMC sampling. More importantly, the data science methods will be described in the context of wind energy applications, with specific wind energy examples and case studies.

Instructors

We provide complimentary e-inspection copies of primary textbooks to instructors considering our books for course adoption.

Request an
e-inspection copy

Share this Title