Abstract
False data injection (FDI) is considered to be one of the most dangerous cyber-attacks in smart grids, as it may lead to energy theft from end users, false dispatch in the distribution process, and device breakdown during power generation. In this paper, a novel kind of FDI attack, named tolerable false data injection (TFDI), is constructed. Such attacks exploit the traditional detector’s tolerance of observation errors to bypass the traditional bad data detection. Then, a method based on extended distributed state estimation (EDSE) is proposed to detect TFDI in smart grids. The smart grid is decomposed into several subsystems, exploiting graph partition algorithms. Each subsystem is extended outward to include the adjacent buses and tie lines, and generate the extended subsystem. The Chi-squares test is applied to detect the false data in each extended subsystem. Through decomposition, the false data stands out distinctively from normal observation errors and the detection sensitivity is increased. Extensive TFDI attack cases are simulated in the Institute of Electrical and Electronics Engineers (IEEE) 14-, 39-, 118- and 300-bus systems. Simulation results show that the detection precision of the EDSE-based method is much higher than that of the traditional method, while the proposed method significantly reduces the associated computational costs.
Highlights
In smart grids, information techniques are applied to provide a desirable infrastructure for real-time measurement, transmission, decision and control
Bad data detection based on extended distributed state estimation (EDSE) is applied to detect these attacks; in Section 6.2, the Institute of Electrical and Electronics Engineers (IEEE)-39 bus system is used to present a statistical comparison of detection performances between the traditional and EDSE-based methods; in Section 6.3, we discuss the some tolerable false data injection (TFDI) attacks which are not detected by the EDSE-based method; the evaluation of time complexity is shown in Section 6.4; and in Section 6.5, the proper number of subsystems is discussed
From the traversal attack simulation on an IEEE 39-bus system, we find that attacks on the transmission lines connected to bus6, bus16 and bus26 are more likely to trigger the detector, even with very low Injected data levels (IDL)
Summary
Information techniques are applied to provide a desirable infrastructure for real-time measurement, transmission, decision and control. For this purpose many sensors are deployed across millions of buildings and streets. Power system state estimation (SE) has been believed to be a good solution to process the bad data, since the pioneering work of Schweppe in 1970 [2] It is applied in supervisory control and data acquisition (SCADA) systems to reduce the observation errors, detect bad data and estimate the electrical states of power systems through processing the set of real-time redundant measurements, typically bus voltage magnitudes and phase angles
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