Model order selection for probing-based power system mode estimation

Author

Peric, Vedran S. ; Bogodorova, Tetiana ; Mete, Ahmet N. ; VANFRETTI, LUIGI

Author_Institution

KTH R. Inst. of Technol., Stockholm, Sweden

fYear

2015

fDate

20-21 Feb. 2015

Firstpage

1

Lastpage

5

Abstract

The paper discusses model order selection for probing mode estimation algorithms. Four methods are analyzed and compared: 1) Residual analysis based model order selection, 2) Model order selection based on singular values, 3) Akaike Information Criterion, and 4) Variance-Accounted-For (VAF) as a measure of optimal fitting between measured data and model response. The methods are assessed using synthetic PMU measurements from the simulation of the KTH Nordic 32 Test system and the IEEE test system with 50 generators and 145 buses.

Keywords

power system measurement; singular value decomposition; Akaike information criterion; IEEE test system; KTH Nordic 32 test system; PMU measurements; WAMS; model response; optimal fitting measure; probing-based power system mode estimation algorithms; residual analysis based model order selection; singular values; variance-accounted-for; wide-area monitoring system; Algorithm design and analysis; Analytical models; Computational modeling; Correlation; Data models; Estimation; Signal processing algorithms; Akaike Information Criterion (AIC); Model order selection; Probing mode estimation; Variance-Accounted-For;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Conference at Illinois (PECI), 2015 IEEE

Conference_Location

Champaign, IL

Type

conf

DOI

10.1109/PECI.2015.7064883

Filename

7064883