REINFORCEMENT LEARNING-BASED REAL TIME ROBUST VARIABLE PITCH CONTROL OF WIND TURBINE SYSTEMS

摘要

Disclosed are a system and a method for reinforcement learning-based real time robust variable pitch control of a wind turbine system. The system includes: a wind speed collecting module to collect wind speed values of a wind farm; a wind turbine information collecting module to collect a rotor angular speed; a reinforcement signal generating module to generate a reinforcement signal based on the collected rotor angular speed and the rated rotor angular speed; a variable pitch robust control module including an action network and a critic network, wherein the action network is configured to generate an action value based on the wind speed of the wind farm and the rotor angular speed and output the action value to the critic network; the critic network is configured to perform learning training based on the reinforcement signal and the action value, generate a cumulative return value and output the cumulative return value to the action network; and the action network performs learning training based on the cumulative return value to update the action value and output the updated action value; and a control signal generating module connected to the action network, configured to generate a corresponding control signal based on the received action value. The wind power generator adjusts the pitch angle based on the control signal, which realizes adjustment of the rotor angle speed and guarantees smooth and stable power output of the wind turbine.