Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction (Paperback)

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation.

General

Imprint:	Academic Press Inc
Country of origin:	United States
Series:	Wind Energy Engineering
Release date:	2020
First published:	2020
Authors:	Harsh S. Dhiman • Dipankar Deb • Valentina E. Balas
Dimensions:	229 x 152 x 13mm (L x W x T)
Format:	Paperback
Pages:	216
ISBN-13:	978-0-12-821353-7
Categories:	Books > Professional & Technical > Energy technology & engineering > Alternative & renewable energy sources & technology
LSN:	0-12-821353-1
Barcode:	9780128213537

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