Can a wind turbine learn to operate itself? Evaluation of the potential of a heuristic, data-driven self-optimizing control system for a 5MW offshore wind turbine
Iordanov, Stefan Gueorguiev and Collu, Maurizio and Cao, Yi (2017) Can a wind turbine learn to operate itself? Evaluation of the potential of a heuristic, data-driven self-optimizing control system for a 5MW offshore wind turbine. Energy Procedia, 137. pp. 26-37. ISSN 1876-6102 (https://doi.org/10.1016/j.egypro.2017.10.332)
Preview |
Text.
Filename: Iordanov_etal_EP2017_Can_a_wind_turbine_learn_to_operate_itself.pdf
Final Published Version License: Download (1MB)| Preview |
Abstract
Larger and more expensive offshore wind turbines, subject to more complex loads, operating in larger wind farms, could substantially benefit from more advanced control strategies. Nonetheless, the wind industry is reluctant to adopt such advanced, more efficient solutions, since this is perceived linked to a lower reliability. Here, a relatively simple self-optimizing control strategy, capable to "learn" (data-driven) which is the optimum control strategy depending on the objective defined, is presented. It is proved that it "re-discovers", model-free, the optimum strategy adopted by commercial wind turbine in region 2. This methodology has the potential to achieve advanced control performance without compromising its simplicity and reliability.
ORCID iDs
Iordanov, Stefan Gueorguiev, Collu, Maurizio ORCID: https://orcid.org/0000-0001-7692-4988 and Cao, Yi;-
-
Item type: Article ID code: 65390 Dates: DateEvent30 October 2017Published1 October 2017AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) > Environmental engineering Department: Faculty of Engineering > Naval Architecture, Ocean & Marine Engineering Depositing user: Pure Administrator Date deposited: 07 Sep 2018 10:57 Last modified: 11 Nov 2024 12:06 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/65390