Title :
Malicious data identification in smart grid based on residual error method
Author :
Hu, Zongshuai ; Wang, Yong ; Gu, Chunhua ; Mengm, Dejun ; Yang, Xiaoli ; Chen, Shuai
Author_Institution :
Shanghai University of Electric Power Shanghai, China
Abstract :
Most of methods on malicious data identification are based on the residual in power system applications. Residual error method, which is an effective method to identify a single malicious data can be basically divided into weighted residual error method and normalized residual error method. In this paper the states and measurement estimated value can be calculated firstly by the traditional weighted least squares state estimation algorithm. Then the measurement residual and the objective function value can be also calculated. The algorithm of weighted residual error method is tested on IEEE5 bus system by MATLAB and the analysis on the results of calculation example shows that this method is an effective one which a single malicious data can be effectively dealt with, and it can be applied to malicious data identification. In this paper the largest weighted residues in the case of single malicious data are 8.361 and correspond to real power injection at bus2, which are far above the threshold to improve the efficiency of malicious data identification.
Keywords :
MATLAB; Measurement uncertainty; Pollution measurement; Power systems; State estimation; Transmission line measurements; Weight measurement; malicious data identification; measurement residual Introduction; residual error method; smart grid; the states; weighted least squares state estimation;
Conference_Titel :
Cyber Security of Smart Cities, Industrial Control System and Communications (SSIC), 2015 International Conference on
Conference_Location :
Shanghai, China
DOI :
10.1109/SSIC.2015.7245325