Method of controlling a wind farm using a reinforcement learning method
AssigneesIfp Energies Nouvelles, Institut De Recherche En Informatique Et En Automatique
InventorsEva Bouba, Donatien Dubuc, Jiamin Zhu, Claire Bizon Monroc, Ana Busic
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Abstract
The present invention is a wind farm control method, wherein a reinforcement learning method (RL) is implemented in a decentralized manner (for each wind turbine). The reward (REC) is calculated according to a wake propagation delay (DEL). Thus, the reward is truly representative of the effect of the last action (previous yaw control for example).
Claims20
A method of control of a wind farm comprising wind turbines, each wind turbine of the wind farm, comprising an actuator for modifying an operating point including a yaw angle of each turbine with the yaw angle being an angle formed between a rotor of the turbine and a wind direction, comprising steps of:
- a. acquiring power generated by each wind turbine, the wind speed, the wind speed direction, and the yaw angle of each turbine;
- b. for each wind turbine, determining a wake propagation delay formed by the turbine, according to the acquired wind speed and direction, and a layout of the wind turbines within the wind farm;
- c. for each wind turbine, determining a value of a reward representing an impact of control of the turbine on a sum of power generated by all the turbines of the wind farm with the reward being calculated by accounting for the determined wake propagation delay;
- d. for each wind turbine, applying a reinforcement learning method to determine a target operating point of the turbine according to the determined value of a reward and a previous yaw angle;
- and
- e. controlling the operating point of each wind turbine by applying the determined target operating point using the actuator.
Dependencies are inferred from the claim text.