A recursive measurement error estimation identification method for bad data analysis in power system state estimation

Author

Zhang, B.M. ; Lo, K.L.

Author_Institution

Dept. of Electr. Eng., Tsinghua Univ., Beijing, China

Volume

6

Issue

1

fYear

1991

fDate

2/1/1991 12:00:00 AM

Firstpage

191

Lastpage

198

Abstract

A recursive measurement error estimation identification algorithm is proposed for identifying multiple interacting bad data in power system static state estimation. A set of linearized formulae are developed and used to recursively calculate normalized residuals and normalized measurement error estimates upon which the bad data identification method is based. Sparse vector and partial factor modification techniques are used in the recursive identification calculations. Neither the submatrix of the residual sensitivity matrix, W_ss, nor state reestimation is needed in the whole identification process. Digital tests on various power systems, including a 171 bus real system, are done to show the validity and efficiency of the proposed bad data identification method

Keywords

measurement errors; power systems; state estimation; algorithm; bad data analysis; efficiency; linearized formulae; partial factor modification techniques; power system state estimation; recursive measurement error estimation identification method; residuals; sparse vector techniques; validity; Data analysis; Error analysis; Estimation error; Measurement errors; Power system analysis computing; Power system measurements; Power system reliability; Power systems; Recursive estimation; State estimation;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.131062

Filename

131062