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2024 | OriginalPaper | Chapter

Performance Analysis of N-Beats and Regression Learners for Wind Speed Forecasting and Predictions

Authors : Jatin Prakash, P. K. Kankar, Ankur Miglani

Published in: Proceedings of the 9th National Conference on Wind Engineering

Publisher: Springer Nature Singapore

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Abstract

The chapter delves into the critical need for accurate wind speed forecasting in the context of renewable energy. It discusses the application of XGBoost and AdaBoost regressors for wind speed prediction, comparing their performance metrics. Additionally, the chapter introduces the N-Beats model for time series forecasting, demonstrating its effectiveness in minimizing power supply fluctuations. The methodologies presented offer valuable insights into enhancing the management of wind power generation, making the chapter a must-read for specialists in the field.

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previous chapter Vibrational Characteristics of the LEP Vertical-Axis Wind Turbine Shaft for Various Solidity Ratios

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Title: Performance Analysis of N-Beats and Regression Learners for Wind Speed Forecasting and Predictions
Authors: Jatin Prakash
P. K. Kankar
Ankur Miglani
Publisher: Springer Nature Singapore
Book: Proceedings of the 9th National Conference on Wind Engineering
Print ISBN: 978-981-9941-82-7

Electronic ISBN: 978-981-9941-83-4

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-981-99-4183-4_6