Virtual sensors for wind turbines with machine learning‐based time series models
Author:
Affiliation:
1. DTU Wind and Energy Systems Technical University of Denmark Roskilde Denmark
Publisher
Wiley
Subject
Renewable Energy, Sustainability and the Environment
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2762
Reference33 articles.
1. Virtual Wind Speed Sensor for Wind Turbines
2. From wind to loads: wind turbine site-specific load estimation with surrogate models trained on high-fidelity load databases
3. Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates
4. Surrogate models for parameterized representation of wake‐induced loads in wind farms
5. Parametric hierarchical kriging for multi-fidelity aero-servo-elastic simulators — Application to extreme loads on wind turbines
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