ENGS9BB.F

Turbulence and wind energy

Credits : 2 ECTS

Duration : 21 hours

Semester : S9

Persons in charge: Emmanuel Plaut, professor

http://emmanuelplaut.perso.univ-lorraine.fr/welcome-e.htm

Michaël Hölling, associate researcher at ForWind, universität Oldenburg (with Erasmus+ support)

http://www.forwind.de

Keywords: deterministic models, stochastic models

Prerequisites: fluid dynamics elementary course

Objective: learn advanced turbulence modeling, with a focus on wind energy systems, that always operate under turbulent conditions.

Program and contents:

Advanced turbulence modelling is introduced, with deterministic then stochastic models.

  1. Reynolds Averaged Navier-Stokes (RANS) models

    In order to motivate the need for `sophisticated' RANS models, the weaknesses of the `standard' kε model are evidenced, by comparisons with recent direct numerical simulations (DNS). Improved k ε models or alternative RANS models are then introduced.

  2. Large Eddy Simulations (LES)
    The failures of RANS models to describe some turbulent flows with large dynamic eddies is exemplified. LES is then introduced.

  3. Hybrid RANS – LES methods

    An introduction to these methods concludes this first part of the module.

  4. Stochastic models, especially, in the context of wind energy

    This second part of the module is focused on the wind energy sciences. Knowing that the wind in the atmospheric boundary layer is always turbulent, the small scale statistics of turbulent flows is reviewed, with a focus on the intermittency phenomena and extreme events like `wind gusts'. The principles of wind energy conversion and the aerodynamics of wind turbines are also presented. The International Electrotechnical Commission (IEC) standards to evaluate power curves and annual energy production of a given wind turbine is introduced. The limitations of this approach are discussed and more accurate stochastic approaches are introduced, which lead for instance to the notion of `Langevin power curves'.

Please check the web page of this module on http://emmanuelplaut.perso.univ-lorraine.fr/turbuwe : it sketches the planning of this module, gives instructions and files, etc... In particular, students will use the statistical computing software R on their laptop, to study various `turbulence data bases'.

Abilities: 

Levels

Description and operational vocabulary

Know

Hybrid RANS - LES methods. Be aware of current research in the domain of CFD of turbulent flows

Understand

The RANS approach - the LES approach - Strengths and weaknesses of each approach

The notion of intermittency and extreme events

Apply

The RANS approach - the LES approach

Analyze

The RANS approach - the LES approach

Analyze a velocity time series: be able to extract mean and standard deviation values, a PDF of the velocity and of the velocity increments, etc...

Analyze a wind time series: construct the IEC power curve

Summarize


Assess

Choose a good approach - model to solve numerically a given turbulent flow problem

Evaluation:

  • Written test
  • Continuous assessment
  • Oral presentation
  • Project
  • Written report