浙江电力2025，Vol.44Issue(5)：53-65,13.DOI:10.19585/j.zjdl.202505006
基于ISSA-MSVR的风机并网系统暂态稳定评估
Transient stability assessment of wind turbine grid-connected systems using ISSA-MSVR
摘要
Abstract
To address the issue of inaccurate transient stability analysis in power systems after wind farm integra-tion,this paper proposes a method combining improved sparrow search algorithm(ISSA)-optimized multi-output support vector regression(MSVR).First,an energy function is established for direct-drive wind turbines integrated into the grid.For wind turbine grid-connected systems,an interpretable stability energy function is constructed us-ing an improved Deep Q-Network(DQN)algorithm.The unstable equilibrium points(UEPs)of the system are then determined via the boundary of stability region based controlling UEP method(BCU),generating the training and testing datasets for the prediction model.Next,to overcome the limitations of the SSA algorithm,such as susceptibil-ity to local optima,inverse learning,piecewise weighting,and Cauchy mutation are introduced to enhance SSA.The ISSA is then employed to optimally tune the penalty factor and kernel width in MSVR.The proposed method is validated on a modified IEEE 39-bus system.Experimental results demonstrate that the ISSA-MSVR approach achieves smaller prediction errors and reduced training time compared to other state-of-the-art AI methods,effec-tively predicting the UEPs in wind farm-integrated systems.关键词
直驱风机并网/虚拟同步机控制/BCU/改进麻雀搜索算法/多输出支持向量回归Key words
direct-drive wind turbine integration/VSG control/BCU/ISSA/MSVR/UPE prediction引用本文复制引用
范宏,徐勇杰,徐涛..基于ISSA-MSVR的风机并网系统暂态稳定评估[J].浙江电力,2025,44(5):53-65,13.基金项目
国家重点研发计划(2022YFA10046000) （2022YFA10046000）
