Wake characteristics of a wind farm – Numerical simulations
Background:
The effectiveness of wind farms in energy production is largely influenced by energy entrainment. In the atmosphere, the boundary layer fluctuates throughout the day, depending on factors such as temperature, terrain, and geographical location. As temperatures change during the day, the atmospheric boundary layer (ABL) can be classified into three types: neutral, unstable, and stable. The conditions at the inlet significantly affect energy entrainment and, consequently, the overall effectiveness of wind farms. A substantial body of literature has focused on this impact, primarily through experiments using scaled-down wind turbines in wind tunnels. However, representing the motion of wind turbines numerically poses challenges, particularly with dynamic meshing. Techniques such as the Actuator Disk Model and Actuator Line Model can be employed to simulate wind turbine wakes effectively. This project will utilize open-source code from the National Renewable Energy Laboratory’s Simulator for Wind Farm Applications (SOWFA-6) based on OpenFOAM. The goal is to study energy entrainment across various terrains and ABL profiles, using two to three different wind farm configurations.
Specific tasks:
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- Literature study on the ABL over various terrains and wind farm configurations and their influence on entrainment.
- Installation of SOWFA6 on the cluster and setting up the simulation with ADM and ALM for unstable and stable ABL.
- Creation of hexagonal mesh of various terrain (atleast two: valley and rough terrain) and setting up the precursor simulations to generated ABL profiles.
- Setting up the simulation with the effective model over two wind farm configurations over the discussed terrains.
- Data analysis and reporting of the results
Requirements:
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- Experience and interest to learn and be proficient in OpenFOAM/SOWFA
- Curiosity to conduct research and studying ABLs and wind energy
- Data analysis experience in Python and/or Matlab
- Independence working style; proactive and passionate students are encouraged to apply
Starting date: Immediately, flexible
Advisors:
