太原理工大学学报2024，Vol.55Issue(1)：73-83,11.DOI:10.16355/j.tyut.1007-9432.20220767
基于多源数据驱动的电力系统暂态稳定性分析方法
Transient Stability Analysis Method of Power System Based on Multi-source Data Drive
摘要
Abstract
[Purposes]At present,the data driven method represented by deep learning has been widely used in power transient stability analysis.However,the existing transient stability models for researching data driving have some problems,such as limited generalization ability and insufficient model accuracy,when facing small samples,weak samples,and other actual sce-narios.In order to improve the expression ability of the model,a refined transient stability as-sessment method is proposed in this paper according to operation data and fault data.[Methods]First,four fault information characteristics,namely fault time,fault location,disturbed line,and load level,are constructed according to the transient stability mechanism model of power sys-tem.Then,two feature fusion methods,parallel fusion and serial fusion,are proposed to realize the unified expression of operation features and fault features.The influence of multi-source fea-ture fusion on transient stability analysis model is analyzed in depth.[Findings]The experimen-tal results of the New England system example show that the transient stability analysis method based on multi-source data hybrid drive is conducive to improving the accuracy of the transient stability assessment model,and still has a high accuracy in practical scenarios such as small sam-ples and weak samples.关键词
深度学习/暂态稳定评估/运行信息/故障信息/多源数据Key words
deep learning/transient stability assessment/operation information/fault infor-mation/multi source data分类
信息技术与安全科学引用本文复制引用
曲莹,韩肖清,刘新元,芦晓辉,孟涛,张颖..基于多源数据驱动的电力系统暂态稳定性分析方法[J].太原理工大学学报,2024,55(1):73-83,11.基金项目
国网山西省电力公司科技项目(520530200013) （520530200013）
