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Towards digital twin technology: Wind farm operation analysis and optimization using model-supported data analytics
Schröder, Laura
(PhD Student)
Chatzi, Eleni
(Examiner)
Watson, Simon
(Examiner)
Rethore, Pierre-Elouan Mikael
(Examiner)
Dimitrov, Nikolay
(Main Supervisor)
Sørensen, John Aasted
(Supervisor)
Verelst, David Robert
(Supervisor)
Wind Energy Materials and Components Division
Structural Integrity and Loads Assessment
Department of Wind and Energy Systems
Department of Engineering Technology and Didactics
Wind Turbine Design Division
Response, Aeroelasticity, Control and Hydrodynamics
Overview
Fingerprint
Publications
(1)
Project Details
Status
Finished
Effective start/end date
01/10/2017
→
15/04/2021
Funding
Technical University of Denmark
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Wind Turbine
Engineering
100%
Operation and Maintenance
Engineering
33%
Surrogate Model
Engineering
25%
Artificial Neural Network
Engineering
25%
Offshore Wind Farms
Engineering
16%
Maintenance Strategy
Engineering
16%
Wind Power
Engineering
16%
Operational Data
Engineering
16%
Research output
Research output per year
2020
2020
2020
1
Ph.D. thesis
Research output per year
Research output per year
Towards digital twins: wind farm operation analysis and optimization using model-supported data analytics
Schröder, L.,
2020
, Risø, Roskilde, Denmark:
DTU Wind Energy
.
123 p.
(DTU Wind Energy PhD; No. 0106(EN)).
Research output
:
Book/Report
›
Ph.D. thesis
Open Access
File
Wind Turbine
100%
Neural Network
100%
Learning System
66%
Operation and Maintenance
33%
Surrogate Model
25%
1563
Downloads (Orbit)