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Normalized performance and load data for the deepwind demonstrator in controlled conditions.

L Battisti1, E Benini1, A Brighenti1

  • 1Dipartimento di Ingegneria Civile Ambientale e Meccanica, Università di Trento, Italy.

Data in Brief
|January 19, 2019
PubMed
Summary
This summary is machine-generated.

This study presents benchmark data from large-scale wind tunnel tests on a vertical-axis wind turbine. The findings aid in validating numerical simulation codes for wind energy applications.

Keywords:
DeepWind ProjectSkewed flowTroposkien rotorVAWTWind tunnel measurementsWind turbine benchmark data

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Area of Science:

  • Renewable Energy Engineering
  • Aerodynamics
  • Computational Fluid Dynamics

Background:

  • Accurate validation data is crucial for developing reliable wind turbine simulation codes.
  • Previous studies have provided some data, but comprehensive benchmark datasets are still needed.
  • Large-scale experimental data is essential for bridging the gap between simulation and real-world performance.

Purpose of the Study:

  • To provide benchmark data for validating numerical codes used in wind turbine simulations.
  • To present performance and load normalized coefficients from real-scale wind turbine measurements.
  • To complement and support existing experimental data for vertical-axis wind turbines.

Main Methods:

  • Conducted an experimental campaign of measurements at a large-scale wind tunnel.
  • Utilized a three-bladed Troposkien vertical-axis wind turbine for testing.
  • Manipulated raw data into a format suitable for comparison with simulation code outputs.

Main Results:

  • Generated performance and load normalized coefficients from experimental measurements.
  • Processed rough data from real-scale turbine tests.
  • Created easily comparable datasets for numerical code validation.

Conclusions:

  • The presented data serves as valuable benchmark for validating numerical codes.
  • The findings contribute to improving the accuracy of wind turbine simulations.
  • This work supports the ongoing development and refinement of wind energy technologies.