电力系统自动化2026，Vol.50Issue(4)：133-141,9.DOI:10.7500/AEPS20250525005
基于结构化神经网络的微电网二次调频控制
Secondary Frequency Regulation for Microgrids Based on Structured Neural Networks
摘要
Abstract
With the increasing complexity and uncertainty of microgrid systems,designing secondary frequency regulation control methods that combine both stability and output tracking capabilities is crucial for the safe and reliable operation of the system.To this end,this paper proposes a secondary frequency regulation method for microgrids based on structured neural networks.First,by leveraging the equilibrium point independent passivity widely present in physical systems,the secondary frequency regulation problem for microgrids is formulated as a strictly monotonic proportional-integral(PI)control structure,and the PI parameters are parameterized as the gradient of a strictly convex neural network(SCNN).Second,the SCNN is constructed using a Softplus-β activation function with tunable coefficients,which not only ensures its universal approximation capability but also effectively adapts to the diverse communication constraints in microgrids.Furthermore,by employing the gradient of the strictly convex function constructed by the SCNN as a Lyapunov function,an end-to-end stability proof for the system is provided.Simulation results show that,compared with other unstructured neural network control methods which may lead to system instability,the proposed method not only guarantees system stability but also outperforms traditional control methods in both transient and steady-state performance.关键词
微电网/二次调频/不确定性/稳定性/神经网络/比例-积分控制/平衡点/独立无源性Key words
microgrid/secondary frequency regulation/uncertainty/stability/neural network/proportional-integral(PI)control/equilibrium point/independent passivity引用本文复制引用
李锦泽,何晓敏,吴锦辉,郭方洪..基于结构化神经网络的微电网二次调频控制[J].电力系统自动化,2026,50(4):133-141,9.基金项目
国家自然科学基金资助项目(62373328) （62373328）
浙江省自然科学基金资助项目(LR25F030003). This work is supported by National Natural Science Foundation of China(No.62373328)and Zhejiang Provincial Natural Science Foundation of China(No.LR25F030003). （LR25F030003）
