电测与仪表2024，Vol.61Issue(10)：119-127,9.DOI:10.19753/j.issn1001-1390.2024.10.016
基于XGboost-DF的电力系统暂态稳定评估方法
A transient stability assessment method of power system based on XGboost-DF
摘要
Abstract
Aiming at the phenomenon that the instability mode of modern interconnected power grid is no longer single and multiple swing instability occurs frequently after disturbance,a transient stability assessment method based on eXtreme Gradient Boosting-deep forest is proposed in this paper.An artificial feature set is constructed by using the bus voltage track cluster,and supervised feature coding was performed on the feature set by XGboost.The sparse matrix after supervised coding was tri-classified by deep forest,and the mapping relationship between large-scale data set and unstable mode was established.The simulation analysis is carried out on IEEE 39 and IEEE 140 nodes.The proposed method has high accuracy and anti-noise performance,and can effectively reduce the misjudg-ment rate of multiple swing instability.Moreover,it still has strong robustness when the synchronous phasor meas-urement unit is missing.关键词
暂态稳定评估/多摆失稳/极限梯度提升/深度森林/稀疏矩阵Key words
transient stability assessment/multiple swing instability/XGboost/deep forest/sparse matrix分类
动力与电气工程引用本文复制引用
李楠,张家恒..基于XGboost-DF的电力系统暂态稳定评估方法[J].电测与仪表,2024,61(10):119-127,9.基金项目
国家自然科学基金资助项目(61973072) （61973072）
