PMU-based recursive state estimation and its performance with neural network

Author

Shabaninia, F. ; Sadeghi, H. ; Vaziri, M. ; Vadhva, S.

Author_Institution

Shiraz Univ., Shiraz, Iran

fYear

2012

fDate

22-26 July 2012

Firstpage

1

Lastpage

5

Abstract

Phasor measurement units (PMUs) are considered promising for future monitoring, protection and control of power systems. In this paper, an approach is proposed to achieve higher degrees of precision in state estimation using PMUs by recursive weighted least square method. Additionally, when neural network is used as a state estimator in conjunction with the PMUs, a method that uses less number of inputs is proposed for even higher precision of estimating the states as compared to conventional methods.

Keywords

least squares approximations; neural nets; phasor measurement; power engineering computing; power system state estimation; recursive estimation; PMU; neural network performance; phasor measurement unit; power system control; power system monitoring; power system protection; recursive state estimation; recursive weighted least square method; Current measurement; Neural networks; Phasor measurement units; Power systems; State estimation; Transmission line measurements; Voltage measurement; Neural Network; PMU; Recursive State Estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Society General Meeting, 2012 IEEE

Conference_Location

San Diego, CA

ISSN

1944-9925

Print_ISBN

978-1-4673-2727-5

Electronic_ISBN

1944-9925

Type

conf

DOI

10.1109/PESGM.2012.6345075

Filename

6345075