中国电机工程学报2025，Vol.45Issue(14)：5589-5600,中插22,13.DOI:10.13334/j.0258-8013.pcsee.240141
主导模式引导的电力系统暂态稳定数据驱动评估方法
Data-driven Method for Transient Stability Assessment of Power System Guided by Dominant Pattern
摘要
Abstract
Transient stability assessment(TSA)of power systems based on deep learning faces practical implementation challenges due to the unpredictability of evaluation results and uncontrollability of decision-making processes.While attention mechanisms show promising potential in addressing unpredictable and uncontrollable problems,current research primarily focuses on the former issue.To bridge this gap,this study proposes a method that utilizes system dominant patterns to guide models in assigning more rational feature attention weights,thereby controllably enhancing model generalization capability.First,the improved MeanShift algorithm is used to cluster the generators of each training set sample and the critical cluster is labeled to capture the dominant pattern.Then,an objective function fused with dominant pattern information is constructed to optimize the distribution of attention weights.Finally,the new objective function is applied for training and updating of the model.The examples of IEEE 39-bus system and East China power grid show that the model constructed using the proposed method has stronger generalization ability and better noise resistance,and the model’s unpredictability and uncontrollability can be improved.关键词
暂态稳定/注意力机制/主导模式/MeanShift算法Key words
transient stability/attention mechanism/dominant pattern/MeanShift algorithm分类
信息技术与安全科学引用本文复制引用
任顺鑫,王怀远,李剑,卢国强..主导模式引导的电力系统暂态稳定数据驱动评估方法[J].中国电机工程学报,2025,45(14):5589-5600,中插22,13.基金项目
福建省自然科学基金项目(2022J01113) （2022J01113）
国网青海省电力公司科技项目(522800230001). Project Supported by Natural Science Foundation of Fujian Province(2022J01113) （522800230001）
Science and Technology Project of State Grid Qinghai Electric Power Company(522800230001). （522800230001）
