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Source code and data for the experiments presented in Deep Reinforcement Learning for Active Wake Control
Source code and data for the experiments presented in Deep Reinforcement Learning for Active Wake Control
4
contributors
Description
This is a simulation study to illustrate benefits of reinforcement learning (RL) for active wake control in wind farms. The repository includes a simulator (./code/wind_farm_gym), implementation of RL agents (./code/agent), and configurations for the experiments presented in the paper (./code/configs), as well as the simulation results (./data). For more detailed instructions, see README.md.
License
- MIT
</>Source code
Not specified
Contributors
GN
Greg Neustroev
MdW
Mathijs de Weerdt
RV
Remco Verzijbergh
SA
Sytze Andringa