Identification of Critical Locations of Power Systems

被引：3

作者：

Onwuachumba, Amamihe ^{[1
]}

Lerley, Paul ^{[1
]}

Musavi, Mohamad ^{[2
]}

机构：

[1] RLC Engn, Hallowell, ME 04347 USA

[2] Univ Maine, Orono, ME USA

来源：

2017 NINTH ANNUAL IEEE GREEN TECHNOLOGIES CONFERENCE (GREENTECH 2017) | 2017年

关键词：

Critical locations; critical variables; eigenvalues; eigenvectors; monitoring and control; power system; Principal Component Analysis; steady state; system security; PRINCIPAL COMPONENT ANALYSIS;

D O I：

10.1109/GreenTech.2017.48

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This paper presents a methodology for the identification of critical locations of power systems using eigenvalue analysis of measurements of the system variables. The eigenvalue analysis is implemented using Principal Component Analysis (PCA) and the methodology is tested on the IEEE 118-bus system. The identification of critical locations in a power system would enable the utility company smartly utilize resources and have a focused visualization of their system without incurring considerable financial burdens. Also, the effectiveness of monitoring critical locations of a power system in ensuring steady state system security is demonstrated on the IEEE 118-bus system.

引用

页码：290 / 296

页数：7

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