摘要
新息图法可以以较少的量测值 ,快速地排除坏数据和识别拓扑错误 ,为状态估计识别拓扑错误开辟了一条新的途径。文中提出给扩展新息向量加入加权因子 ,以排除大潮流支路误差对小潮流支路的不良影响 ,达到识别小潮流支路拓扑错误的目的 ,并给出了计算加权因子的方法。IEEE— 1 1 8节点系统的算例表明 。
The innovation graph approach,as a new way for identification of abnorm al network configuration in state estimation,can fast identify bad data and topology errors with lower m easurem ent redundancy.This paper describes that a weighting factor is added to the extended innovation vector for elim inating the influence of large power flow branch to small ones,thus the topology error on sm all load flow branches can be identified efficiently.The way of calculating weighting factor is also presented in this paper. The IEEE- 118bus system exam ple shows that this approach is capable of identifying topology error on branches with small load flow.
出处
《电力系统自动化》
EI
CSCD
北大核心
2001年第5期27-30,共4页
Automation of Electric Power Systems
基金
清华大学电力系统国家重点实验室开放基金资助项目
关键词
电力系统
状态估计
潮流支路
加权新息图法
识别
power system s
state estimation
topology error
innovation vector
innovation graph
