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portada Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction (Wind Energy Engineering)
Type
Physical Book
Publisher
Author
Year
2020
Language
English
Pages
216
Format
Paperback
ISBN13
9780128213537
Edition No.
1
Categories

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

Harsh S. Dhiman; Dipankar Deb; Valentina Emilia Balas (Author) · Academic Press · Paperback

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction (Wind Energy Engineering) - Harsh S. Dhiman; Dipankar Deb; Valentina Emilia Balas

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Synopsis "Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction (Wind Energy Engineering) "

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.Features various supervised machine learning based regression modelsOffers global case studies for turbine wind farm layoutsIncludes state-of-the-art models and methodologies in wind forecasting

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