Data‐driven weather forecasting models performance comparison for improving offshore wind turbine availability and maintenance-Reference-Cited by-同舟云学术

Data‐driven weather forecasting models performance comparison for improving offshore wind turbine availability and maintenance

Published:2020-09-14 Issue:13 Volume:14 Page:2386-2394
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Generation

Author:

Pandit Ravi Kumar¹^ORCID,Kolios Athanasios¹^ORCID,Infield David²

Affiliation:

1. Naval Architecture, Ocean & Marine EngineeringUniversity of Strathclyde16 Richmond StGlasgowG1 1XQScotlandUK

2. Electronics and Electrical EngineeringUniversity of Strathclyde16 Richmond StGlasgowG1 1XQScotlandUK

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2019.0941

Reference37 articles.

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2. Layout optimisation for an installation port of an offshore wind farm

3. Garrad HassanG.L.: ‘A guide to UK offshore wind operations and maintenance’. Scottish Enterprise and the Crown Estate 2013

4. A lifecycle techno-economic model of offshore wind energy for different entry and exit instances

5. PanditR.K. InfieldD.: ‘Using Gaussian process theory for wind turbine power curve analysis with emphasis on the confidence intervals’.2017 6th International Conference on Clean Electrical Power (ICCEP) Santa Margherita Ligure 2017 pp.744–749 doi:https://doi.org/10.1109/ICCEP.2017.8004774

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