High breakdown point estimation in electric power systems

Author

Mili, L. ; Phaniraj, V. ; Rousseeuw, P.J.

Author_Institution

Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA

fYear

1990

fDate

1-3 May 1990

Firstpage

1843

Abstract

The application of the least mean square estimator to electric power systems is addressed. This is a high-breakdown point estimator developed by P.J. Rousseeuw (1984). The estimator is solved through resampling techniques in conjunction with fast decoupled methods and simple observability checks. Concepts such as fundamental set and local breakdown point are introduced. They extend the robust estimation theory to sparse regression models. Based on these concepts, optimal meter placement methodologies for bad-data identification are described

Keywords

estimation theory; least squares approximations; observability; power system measurement; power systems; bad-data identification; electric power systems; fast decoupled methods; fundamental set; high-breakdown point estimator; least mean square estimator; local breakdown point; observability checks; optimal meter placement methodologies; resampling techniques; robust estimation theory; sparse regression models; Contamination; Distribution functions; Electric breakdown; Electric variables measurement; Parameter estimation; Pollution measurement; Power measurement; Robustness; State estimation; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1990., IEEE International Symposium on

Conference_Location

New Orleans, LA

Type

conf

DOI

10.1109/ISCAS.1990.112013

Filename

112013