cff-version: 1.2.0
abstract: "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.<br>"
authors:
  - family-names: Neustroev
    given-names: Greg
    orcid: "https://orcid.org/0000-0002-7706-7778"
  - family-names: de Weerdt
    given-names: Mathijs
    orcid: "https://orcid.org/0000-0002-0470-6241"
  - family-names: Verzijbergh
    given-names: Remco
  - family-names: Andringa
    given-names: Sytze
    orcid: "https://orcid.org/0000-0003-4061-7104"
title: "Source code and data for the experiments presented in Deep Reinforcement Learning for Active Wake Control"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/19107257.v1
license: MIT
date-released: 2022-02-04