山东电力技术2024，Vol.51Issue(4)：27-35,9.DOI:10.20097/j.cnki.issn1007-9904.2024.04.003
数据驱动的电力系统动态安全评估研究综述
Review on Data-driven Dynamic Security Assessment of Power Systems
摘要
Abstract
The integration of large-scale new energy and flexible loads increases the uncertainty of power grid operating conditions,and the operating status of the power grid frequently approaches the stability limit,highlighting various dynamic security risks.As an efficient assessment method,data-driven dynamic security assessment(DSA)can directly obtain the mapping relationship between input features and dynamic security output,which can timely discover various dynamic security risks.It is an important means to improve the intelligent defense level of the power system.With the development of power big data and artificial intelligence techniques,various cutting-edge machine learning methods are explored and applied to the DSA.According to the procedure of data-driven DSA,the current research status was reviewed in terms of four perspectives:feature selection,model training,model updating,and online assessment.Moreover,five major challenges were summarized.关键词
数据驱动/动态安全评估/特征选择/模型训练/模型更新/在线评估Key words
data-driven/dynamic security assessment/feature selection/model training/model updating/online assessment分类
信息技术与安全科学引用本文复制引用
姜力杨,盖晨昊,齐航,孙润稼..数据驱动的电力系统动态安全评估研究综述[J].山东电力技术,2024,51(4):27-35,9.基金项目
国家自然科学基金(52177096) （52177096）
山东省自然科学基金(ZR2021QE221). National Natural Science Foundation of China(52177096) （ZR2021QE221）
Natural Science Foundation of Shandong Province(ZR2021QE221). （ZR2021QE221）
