Optimization method for cluster operation of cogeneration motors based on load demand and reinforcement learning
The conventional optimization of the operation of cogeneration motor clusters mainly adopts the method of optimizing motor circuit losses,ignoring the influence of motor rotor parameters,resulting in higher stator copper consumption values in the optimization results.Therefore,a cluster operation optimization method for cogeneration motors based on load demand and reinforcement learning is proposed.Analyze the energy flow and energy flow relationship of the electric motor,analyze the distribution energy consumption status of the cogeneration motor,based on the electricity price analysis of the load demand value,correct the inner and outer diameter ratio parameters and radial clearance parameters of the motor rotor,and then solve the rotor speed parameters of the motor cluster based on the linear relationship.Substitute reinforcement learning to optimize the output of the optimal state parameters,in order to achieve its operation optimization process.The experimental results show that the operation optimization results obtained after the application of the proposed method exhibit lower stator copper consumption values and better optimization effects,meeting the practical application requirements of cogeneration motors.
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