Acquisition, processing and utilization of wind turbine data

Titel: Acquisition, processing and utilization of wind turbine data
  • Bachelorarbeit
Status: offen


Wind energy is becoming more and more relevant as the need for switching to renewable energy
sources increases. In order to reduce the cost of producing energy from wind turbines (WTs), their
efficiency should be increased while reducing the manufacturing costs. In this direction, in the
framework of ANWIND national project, we are trying to increase our understanding of the
phenomena occurring by the interaction of complex systems like WTs with wind during operation.
Since experiments on scaled models cannot give enough insight the main source of experimental
data is from sensors installed on commercial operating turbines.

In the present thesis project, measurements from German Alpha Ventus
offshore wind farm will be utilized. A 5 MW Senvion wind turbine is
heavily instrumented for research purposes and will be used. Wind,
power performance and structural loads measurements are available
from sensors including anemometers, accelerometers, strain gauges etc.
One of the latest additions is Fiber Bragg Grating (FBG) sensors
measuring rotor blade operational loads in multiple cross sections.

The scope of the project is to acquire and process the measurements from FBGs as well as a specific
set of other sensors. The data should be processed in order to discard corrupted or erroneous data.
Moreover, the data from the various sensors should be calibrated/combined in order to produce
meaningful information in specified units and sampling rates. This data should then be able to be
examined as 10 minute statistics and time series. Finally, the data will be assessed in terms of quality
(e.g. agreement of blade root bending moments measurements from FBGs and strain gauges) as well
as possible correlations (e.g. correlation between wind speed and blade root bending moments

The student will get acquainted with the workflow of acquiring and manipulating large amount of real
wind turbine data, the possibilities and limitations of data acquisition systems and will develop a
mindset allowing the evaluation and assessment of measurement data.


  • Understanding of measured signals and sensors used on a wind turbine
  • Getting familiar with data structure and format
  • Implementing scripts in order to acquire and process the data
  • Post-process “clean” measured data to generate useful information
  • Document and present the work carried out in a clear, brief and technical manner


  • MATLAB programming
  • Time series large data manipulation
  • Basic understanding of statistics