摘要
台风、冰灾和暴雨等极端天气条件下,电力设备故障概率将大幅提升,电网高阶故障状态的数量急剧增加,严重影响到传统基于概率筛选的N-k故障分析方法的计算精度和计算效率。针对该问题,提出一种基于影响增量的电力系统N-k故障分析方法,该方法根据电网有限低阶故障状态的分析结果,仅借助其影响增量即可快速计算相应高阶故障状态的影响,并利用设备间独立关系进一步降低故障分析的计算量,实现大量高阶N-k故障状态的快速分析和筛选。最后,通过IEEE RTS 79测试系统、PEGASE 1354节点测试系统和PEGASE13659节点测试系统对该文所提方法进行分析、验证。结果表明,所提N-k故障分析方法能够快速、准确计算出电力系统N-k故障状态的影响,并有效筛选出电网的高影响N-k故障状态。
Under extreme weather conditions such as typhoon, ice disaster and rainstorm, the grid equipment faults probability and the number of high order contingency states will be greatly increased. Therefore, it seriously affects the calculation accuracy of the traditional N-k contingency analysis methods based on probability and the computational efficiency of calculating the impact of N-k contingency states. This paper proposed a N-k contingency analysis method for power systems based on impact increments. Based on the analysis results of the limited low order contingency states of the power grid, the impact of corresponding high order contingency states can be quickly calculated by using the impact increments. Besides, independent relationship between equipment further reduces the amount of calculation for contingency analysis so that a large number of high order N-k contingency states can be quickly analyzed and screened. The IEEE RTS 79, PEGASE 1354 and PEGASE 13659 test cases are employed to evaluate the performance of the proposed methods. The results show that the proposed N-k contingency analysis method can rapidly and accurately calculate the impact of N-k contingency states and accurately screen the high-impact N-k contingency states.
作者
李雪
孙霆锴
侯恺
姜涛
李国庆
陈厚合
贾宏杰
LI Xue;SUN Tingkai;HOU Kai;JIANG Tao;LI Guoqing;CHEN Houhe;JIA Hongjie(Department of Electrical Engineering,Northeast Electric Power University,Jilin 132012,Jilin Province,China;Key Laboratory of Smart Grid of Ministry of Education(Tianjin University),Nankai District,Tianjin 300072,China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2020年第16期5113-5125,共13页
Proceedings of the CSEE
基金
国家自然科学基金项目(51607033,51877033,51677023)
国家重点研发计划项目(2016YFB0900903)。
关键词
极端天气
影响增量
低阶故障状态
独立关系
extreme weather
impact increments
low order N-k contingency states
independent relationship
