电力系统及其自动化学报2026，Vol.38Issue(4)：12-24,13.DOI:10.19635/j.cnki.csu-epsa.001692
融合时序卷积与多头自注意力的暂态电压稳定评估
Transient Voltage Stability Assessment Integrating Temporal Convolution and Multi-head Self-attention
摘要
Abstract
To enhance the performance of transient voltage stability assessment models and improve the interpretability of assessment results,a method integrating temporal convolutional and a multi-head self-attention mechanism is pro-posed in this paper.First,to accurately assess the power system's transient voltage stability,the Transformer encoder is modified by embedding a temporal convolutional module,thus capturing the global and local information about elec-trical parameters throughout the transient process.Second,an adaptive threshold focal loss function is put forward to mitigate the adverse impact of sample imbalance on model training.Third,an interpretability analysis method based on the multi-head self-attention mechanism is employed to calculate attention weights across both the temporal and spatial dimensions,providing insights into the decision-making process of the assessment model.Finally,the proposed method is verified by simulations conducted on an IEEE-39 bus system and an IEEE-300 bus system,and results demonstrate that it achieves higher assessment accuracy,exhibits strong robustness,and offers interpretability.关键词
暂态电压稳定评估/多头自注意力机制/时序卷积模块/可解释性/样本不平衡Key words
transient voltage stability assessment/multi-head self-attention mechanism/temporal convolutional mod-ule/interpretability/sample imbalance分类
信息技术与安全科学引用本文复制引用
李欣,张耀为,赵乔,郭攀锋,刘静茹,吴昌杰..融合时序卷积与多头自注意力的暂态电压稳定评估[J].电力系统及其自动化学报,2026,38(4):12-24,13.基金项目
国家自然科学基金资助项目(52107107). （52107107）
