Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction Paperback / softback
by Harsh S. (Department of Electrical Engineering, Institute of Infrastructure Technology Resea Dhiman, Dipankar (Professor in Electrical Engineering, Institute of Infrastructure Technology Research Deb, Valentina, PhD (Full Professor, Department of Automatics and Applied Software, Faculty Emilia Balas
Part of the Wind Energy Engineering series
Paperback / softback
Description
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.
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:216 pages
- Publisher:Elsevier Science Publishing Co Inc
- Publication Date:31/01/2020
- Category:
- ISBN:9780128213537
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:216 pages
- Publisher:Elsevier Science Publishing Co Inc
- Publication Date:31/01/2020
- Category:
- ISBN:9780128213537
