Error analysis in static harmonic State estimation: a statistical approach

Author

Yu, Kent K C ; Watson, Neville R. ; Arrillaga, Jos

Author_Institution

Univ. of Canterbury, Christchurch, New Zealand

Volume

20

Issue

2

fYear

2005

fDate

4/1/2005 12:00:00 AM

Firstpage

1045

Lastpage

1050

Abstract

The effectiveness of harmonic state estimation (HSE) in identifying the location and magnitude of harmonic sources is largely dependent on the accuracy of the measurements. Measurement errors (or bad data) can be classified into two groups; measurement noise and gross error. This paper uses a statistical approach (cumulative probability density functions) obtained from five thousand Monte Carlos runs to investigate the impact of measurement noise and gross errors in harmonic state estimation. The Lower South Island of the New Zealand system is used as the test system and the results are probability curves containing the statistics of the estimation error. The effect of additional measurements on an over-determined system to filter noise is also discussed.

Keywords

Monte Carlo methods; error analysis; harmonic analysis; noise measurement; probability; state estimation; statistical analysis; Monte Carlo method; error analysis; harmonic analysis; noise filtering; noise measurement; probability density function; static harmonic state estimation; statistical approach; Density measurement; Error analysis; Measurement errors; Monte Carlo methods; Noise measurement; Power harmonic filters; Probability density function; State estimation; Statistical analysis; System testing; Error analysis; harmonic analysis; state estimation;

fLanguage

English

Journal_Title

Power Delivery, IEEE Transactions on

Publisher

ieee

ISSN

0885-8977

Type

jour

DOI

10.1109/TPWRD.2004.833895

Filename

1413351