Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction (Wind Energy Engineering) 1st Edition
by Harsh S. Dhiman,Dipankar Deb,Valentina Emilia Balas
Series: Wind Energy Engineering
Print Length 页数: 216 pages
Publisher finelybook 出版社: Academic Press; 1 edition (February 14,2020)
Language 语言: English
ISBN-10: 0128213531
ISBN-13: 9780128213537
Book 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.
Contents
List of figures
List of tables
Biography
Preface
Acknowledgments
Acronyms
1Introduction
2 Wind energy fundamentals
3 Paradigms in wind forecasting
4 Supervised machine learning models based on support vector regression
5 Decision tree ensemble-based regression models
6Hybrid machine intelligent wind speed forecasting models
7 Ramp prediction in wind farms
8 Supervised learning for forecasting in presence of wind wakes
Epilogue
APPENDIX A Introduction to R for machine learning regression
Index
