A Multifidelity Framework for Wind Speed Data

Colombo, P., Miller, C. , O'Donnell, R. and Yang, X. (2023) A Multifidelity Framework for Wind Speed Data. In: 37th International Workshop on Statistical Modelling (IWSM), Dortmund, Germany, 16-21 Jul 2023, ISBN 9783947323425

Abstract

Monitoring wind speed is essential to develop offshore wind farms. However, recorded wind data often lack the necessary accuracy for understanding the profitability of the wind farm, and even when they exist, they are scarce in time or space. Intuitively, using multiple data sources could balance the trade-off between scarcity and accuracy. A multi-fidelity framework in the form of the autoregressive Gaussian process is introduced to analyze wind speed reanalysis data fusing datasets of different reliability and resolution to provide a more accurate wind speed data product.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Colombo, Mr Pietro and O'Donnell, Dr Ruth and Miller, Professor Claire and Yang, Dr Xiaochen
• Authors: Colombo, P., Miller, C., O'Donnell, R., and Yang, X.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• ISBN: 9783947323425
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Proceedings of the 37th International Workshop on Statistical Modelling (IWSM)
• Publisher Policy: Reproduced with the permission of the Author

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