Subseasonal-to-seasonal forecasting for wind turbine maintenance scheduling

Tawn, R., Browell, J. and McMillan, D. (2022) Subseasonal-to-seasonal forecasting for wind turbine maintenance scheduling. Wind, 2(2), pp. 260-287. (doi: 10.3390/wind2020015)

Abstract

Certain wind turbine maintenance tasks require specialist equipment, such as a large crane for heavy lift operations. Equipment hire often has a lead time of several weeks but equipment use is restricted by future weather conditions through wind speed safety limits, necessitating an assessment of future weather conditions. This paper sets out a methodology for producing subseasonal-to-seasonal (up to 6 weeks ahead) forecasts that are site- and task-specific. Forecasts are shown to improve on climatology at all sites, with fair skill out to six weeks for both variability and weather window forecasts. For the case of crane hire, a cost-loss model identifies the range of electricity prices where the hiring decision is sensitive to the forecasts. While there is little difference in the hiring decision made by the proposed forecasts and the climatology benchmark at most electricity prices, the repair cost per turbine is reduced at lower electricity prices.

• Item Type: Articles
• Additional Information: This research was funded by The Data Lab Innovation Centre with co-funding from Natural Power Consultants Ltd. through the Ph.D. studentship held by Rosemary Tawn.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Browell, Dr Jethro

Creator Roles

Browell, J.: Conceptualization, Methodology, Writing – review and editing, Supervision

• Authors: Tawn, R., Browell, J., and McMillan, D.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Wind
• Publisher: MDPI
• ISSN: 2674-032X
• ISSN (Online): 2674-032X
• Published Online: 12 May 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Wind 2(2):260-287
• Publisher Policy: Reproduced under a Creative Commons license