基于深度强化学习的电力储能接入系统设计

Design of Electric Energy Storage Access System Based on Deep Reinforcement Learning

传统的电力储能接入系统多依赖于固定的控制策略和参数设置,无法有效应对电力系统中复杂多变的运行环境和需求变化。为充分满足电力系统的电力接入需求,引入深度强化学习设计电力储能接入系统。首先,对变流器进行选型,设计信号接口电路,实现电力储能接入系统的硬件设计。然后,基于系统硬件设计,利用深度强化学习进行储能优化配置、负荷低谷与负荷峰值接入设计,实现软件部分的设计,以完成整体的电力储能接入系统设计。通过仿真对比实验证明,在所提储能接入系统的应用下,功率变化与未接入时相符,可以在满足电力系统用电需求的同时提高电力储能质量,实际应用效果良好。

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.