Reduced model for power system state estimation using artificial neural networks

被引：3
|
作者：
Onwuachumba, Amamihe [1 ]
Wu, Yunhui [1 ]
Musavi, Mohamad
机构：
[1] Univ Maine, Dept Elect & Comp Engn, Orono, ME 04469 USA
来源：
2013 IEEE GREEN TECHNOLOGIES CONFERENCE | 2013年
关键词：
Artificial neural networks; network observability; power systems; state estimation; OBSERVABILITY;
D O I：
10.1109/GreenTech.2013.69
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than conventional techniques. This approach has been successfully implemented on 6-bus and 18-bus power systems and the results are provided.
引用
收藏
页码：407 / 413
页数：7
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