We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations.
- Authors
Branlard, Emmanuel; Giardina, Dylan; Brown, Cameron S. D.
- Abstract
This article presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin, perform condition monitoring, or assess loads for dedicated control strategies. The mechanical model is built using a Rayleigh-Ritz approach and a set of joint coordinates. We present a general method and illustrate it using a 2-degrees-of-freedom (DOF) model of a wind turbine and using rotor speed, generator torque, pitch, and tower-top acceleration as measurement signals. The different components of the model are tested individually. The overall method is evaluated by computing the errors in estimated tower-bottom-equivalent moment from a set of simulations. From this preliminary study, it appears that the tower-bottom-equivalent moment is obtained with about 10% accuracy. The limitation of the model and the required steps forward are discussed.
- Subjects
KALMAN filtering; MECHANICAL models; WIND turbines; WIND speed; RAYLEIGH waves
- Publication
Wind Energy Science, 2020, Vol 5, Issue 3, p1155
- ISSN
2366-7443
- Publication type
Article
- DOI
10.5194/wes-5-1155-2020