Abstract
A previously published wind sensing method is applied to an experimental dataset obtained from a 3.5 MW turbine. The method is based on a load-wind model that correlates once-per-revolution blade load harmonics to rotor-equivalent shears and wind directions. Loads measured during turbine operation are used to estimate online - through the load-wind model - the inflow at the rotor disk, thereby turning the whole turbine into a sort of generalized anemometer. The experimental dataset consists of synchronous measurements of loads, from blade-mounted strain gages, and of the inflow, obtained from a nearby met mast. As the mast reaches only to hub height, a second independent method is used to extend the met-mast-measured shear above hub height to cover the entire rotor disk. Part of the dataset is first used to identify the load-wind model, and then the performance of the wind observer is characterized with the rest of the data. Although the experimental setup falls short of providing a thorough validation of the method, it still allows for a realistic practical demonstration of some of its main features. Results indicate a good quality of the estimated linear shear both in terms of 1 and 10 min averages and of resolved time histories, with mean average errors around 0.04. A similarly accuracy is found in the estimation of the yaw misalignment, with mean errors typically below 3°.
| Original language | English |
|---|---|
| Pages (from-to) | 759-775 |
| Number of pages | 17 |
| Journal | Wind Energy Science |
| Volume | 6 |
| Issue number | 3 |
| DOIs | |
| State | Published - 28 May 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Fingerprint
Dive into the research topics of 'Wind inflow observation from load harmonics: Initial steps towards a field validation'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver