中国电机工程学报2024，Vol.44Issue(4)：1419-1429,中插14,12.DOI:10.13334/j.0258-8013.pcsee.221686
基于超松弛双Q学习的源荷储协同频率稳定算法研究
Research on Source Load Storage Cooperative Frequency Stabilization Algorithm Based on Super Relaxed Double Q Learning
摘要
Abstract
The large-scale access to new energy with strong random characteristics will bring strong random disturbance to the power grid.The traditional control methods can not effectively solve the problems of frequency instability and worse control performance standards caused by a strong random disturbance in the distributed power grid mode.From the point of secondary frequency modulation,this paper proposes a multi-agent cooperative control algorithm for distributed multi-area interconnected power grid,i.e.over-relaxation double Q learning algorithm to obtain multi-area cooperation control.The proposed algorithm introduces an over-relaxation factor based on fast Q-learning ω.To accelerate the calculation of the optimal value function,at the same time,the double Q learning strategy is introduced to solve the problem of overestimation of the active exploration value in the reinforcement learning of the Q algorithm system,so as to improve the update efficiency and convergence performance of the algorithm.Through the simulation of the improved IEEE standard two-area load frequency control model and Yunnan interconnected power grid model,the proposed algorithm shows better control performance and convergence speed.关键词
新能源/二次调频/强化学习/多智能体Key words
new energy/secondary frequency modulation/reinforcement learning/multi agent分类
信息技术与安全科学引用本文复制引用
周博奇,柳丹,席磊,李彦营..基于超松弛双Q学习的源荷储协同频率稳定算法研究[J].中国电机工程学报,2024,44(4):1419-1429,中插14,12.基金项目
国家自然科学基金项目(52277108). Project Supported by National Natural Science Foundation of China(52277108). （52277108）
