Title :
The innovation concept in bad data analysis using the composed measurements errors for power system state estimation
Author :
Bretas, N.G. ; Pierreti, S.A.
Author_Institution :
Dept. of Electr. Eng., Univ. of Sao Paulo, São Paulo, Brazil
Abstract :
The available bad data identification procedures for power system state estimation, is totally inadequate since they do not consider the masked effect of the measurement error. The measurement gross error identification procedure, presented in this paper, attempts to alleviate these difficulties. The innovation concept is used to estimate the measurement total error. This is required because the power system equations are very much correlated to each other and as a consequence part of the measurements errors is masked. To find that masked error, the innovation index (II), which provides the measurement quantity of new information is proposed. The total gross error of that measurement is composed and used to the gross error detection and identification test. However, using the composed gross error, the largest normalized residual test is not valid anymore then a new gross error detection and identification is proposed. A two-bus system is used in order to demonstrate the proposed gross error detection and identification test.
Keywords :
data analysis; measurement errors; power system measurement; power system state estimation; bad data analysis; bad data identification procedures; composed measurement errors; gross error detection; innovation index; measurement gross error identification procedure; normalized residual test; power system equations; power system state estimation; two-bus system; Gross Errors Analysis; Orthogonal Projections; Recovering Errors; State Estimation; Undetectability Index;
Conference_Titel :
Power and Energy Society General Meeting, 2010 IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-6549-1
Electronic_ISBN :
1944-9925
DOI :
10.1109/PES.2010.5589569