Design of Electric Energy Storage Access System Based on Deep Reinforcement Learning
Traditional power storage access systems often rely on fixed control strategies and parameter settings,which cannot effectively cope with the complex and ever-changing operating environment and demand changes in the power system.To fully meet the power access needs of the power system,deep reinforcement learning is introduced to design the power storage access system.Firstly,select the inverter and design the signal interface circuit to achieve the hardware design of the power storage access system.Then,based on the system hardware design,deep reinforcement learning is used for energy storage optimization configuration,load trough and load peak access design to realize the design of the software part,thereby completing the overall design of the power energy storage access system.Through simulation and comparative experiments,it has been proven that under the application of the proposed energy storage access system,the power change is consistent with that when not connected,and it can improve the quality of power storage while meeting the electricity demand of the power system,the actual application effect is good.
deep reinforcement learningenergy storageenergy storage optimization configuration
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