Active disturbance rejection controller for multi-area interconnected power system based on reinforcement learning
Active disturbance rejection controller for multi-area interconnected power system based on reinforcement learning
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DOI：
10.1016/j.neucom.2020.03.070
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发表时间：
2020-04
期刊：
影响因子：
6
通讯作者：
Yuemin Zheng;Zengqiang Chen;Zhaoyang Huang;Mingwei Sun;Qinglin Sun
中科院分区：
文献类型：
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作者：
Yuemin Zheng;Zengqiang Chen;Zhaoyang Huang;Mingwei Sun;Qinglin Sun
针对多区域互联电力系统，提出一种基于强化学习（RL）Q学习的自抗扰控制器（ADRC）方法。负载的过度变化可能会导致系统不稳定。因此，采用ADRC控制器，以其较强的抗干扰性能和Q学习算法来选择控制器的自适应参数，使负载保持在额定范围内。最后，通过分别对传统和解除管制的三区互联电力系统进行仿真实验，证明了所提方法的有效性，结果表明强化学习确实可以用来解决控制器参数调节问题。
In this paper, a method of Active Disturbance Rejection Controller (ADRC) is proposed based on Q-learning of Reinforcement Learning (RL) for multi-area interconnected power system. Excessive changes in load can cause instability to the system. Therefore, the ADRC controller is used to keep the load within rated range for its strong anti-interference performance and Q-learning algorithm to select the adaptive parameters of the controller. Finally, through simulation experiments on traditional and deregulated three-area interconnected power system respectively, the effectiveness of the proposed method is proved and the results show that reinforcement learning can indeed be used to solve the problem of controller parameter adjustment.