基于强化学习的孤岛微电网多源协调频率控制方法

Multi-source Coordinated Frequency Control Method Based on Reinforcement Learning for Island Microgrid

为了提升孤岛微电网频率抗干扰性,提出一种基于强化学习的孤岛微电网多源协调频率控制方法。针对微电网频率偏差进行Q学习,动态调节多个分布式电源的下垂控制参数以改变其输出功率,实现微电网内多源协调有功频率控制。首先,介绍了Q学习算法的基本原理;其次,提出基于Q学习的频率恢复控制方法,并设计基于Q学习算法的控制器,利用Q学习算法动态修正下垂参数,协调微电网多个分布式电源进行频率恢复控制;最后,利用MATLAB建立典型微电网仿真模型,并基于S-function自定义建立强化学习控制器,从Q学习训练过程、频率控制响应特性多个方面验证了所提方法的有效性和适应性。

In order to improve the frequency anti-interference of the island microgrid,a coordinated frequency control method based on reinforcement learning for island microgrid is proposed.The proposed control method performs Q-learning on the basis of the frequency deviation of the microgrid,and dynamically adjusts the droop control parameters of multiple distributed power sources to change their output power,to realize multi-source coordinated active frequency control in the microgrid.Firstly,the principle of Q-learning algorithm is introduced.Secondly,a frequency recovery control method based on Q-learning is proposed,and a controller based on the Q-learning algorithm is set up.The Q-learning algorithm is used to dynamically correct the droop parameters and coordinate multiple distributed power sources in the microgrid for frequency recovery control.Finally,MATLAB is used to establish a typical microgrid simulation model,and on the basis of Sfunction,a self-defined reinforcement learning controller is established to verify the effectiveness and adaptability of the proposed method from the aspects of the Q-learning training process and frequency control response characteristics.