Malicious data identification in smart grid based on residual error method

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.

Smart Grids Data Analysis: A Systematic Mapping Study

“…C9. Security Intrusion detection ( [8], [15], [52], [74], [76], [77], [143], [148], [209]),false data injection attacks ( [13], [16], [17], [31], [100], [119], [151], [163], [168], [184], [185], [230], [251], [257]), energy theft ( [54], [99], [169], [191], [254], [258]), distinguishing cyber-attacks from physical faults ( [18])…”

“…C9. Security Intrusion detection ( [8], [15], [52], [74], [76], [77], [143], [148], [209]),false data injection attacks ( [13], [16], [17], [31], [100], [119], [151], [163], [168], [184], [185], [230], [251], [257]), energy theft ( [54], [99], [169], [191], [254], [258]), distinguishing cyber-attacks from physical faults ( [18]) C10. SG failures fault status detection [41], [46], [61], [62], [126], [127], [142], [176], fault type classification [197], power distribution reliability [149], [195] As it can be seen, there is large variability in the aspects covered by the research.…”