基于协同强化学习的微电网分布式两级电压优化控制

Distributed secondary voltage optimization control for a microgrid based on cooperative reinforcement learning

由于微电网中分布式电源组成复杂,运行模式多样,孤岛微电网的电压恢复控制面临着不确定性干扰的影响。为此,针对不确定性干扰下微电网的二级电压恢复控制问题,提出了一种基于协同强化学习的微电网分布式两级电压优化控制方法,实现孤岛模式下微电网的电压调节控制。首先构建孤岛微电网分布式一致性协同电压控制算法,并建立李雅普诺夫函数稳定性判定方法。其次根据控制器性能与控制器增益参数的关系,求解孤岛微电网电压控制器增益上界,并根据控制器增益参数上界限制强化学习智能体动作集。随后,采用强化学习算法优化二级控制器增益参数,给出相应的强化学习智能体状态集、协同全局奖励函数。最后在Matlab/Simulink上通过仿真实验验证了所提出的控制方法的有效性和适应性。

Because of the complex composition of distributed generators and various operational modes in the microgrid,the voltage restoration control of an islanded microgrid will be affected by uncertain disturbances.In this paper,a distributed secondary microgrid voltage optimization control method based on cooperative reinforcement learning algorithm applied to the secondary voltage restore control problem of the microgrid under uncertain disturbances is proposed.This can realize the voltage regulation control of an islanded microgrid.First,a distributed consensus cooperative voltage control algorithm of the islanded microgrid is constructed,and a stability judgement method based on the Lyapunov function is established.Second,from the relationship between controller performance and gain parameters,the upper bound of the voltage controller gain of the islanded microgrid is derived.This can be used to constrain the action space of the reinforcement learning agent.Third,the reinforcement learning algorithm is applied to optimize the secondary voltage controller gain parameters,and the corresponding reinforcement learning state space and cooperative global reward function are presented.Finally,the effectiveness and adaptability of the proposed control are verified by simulation experiments on Matlab/Simulink.