Online Identification and Data Recovery for PMU Data Manipulation Attack
ABSTARCT :
Some of the modern smart grid infrastructures, phasor measurement units (PMUs) for instance, are vulnerable to cyber attacks due to their ever-increasing dependence on information and communications technologies. In general, existing solutions to cyber attacks focus on creating redundancy and/or enhancing security levels of sensing and communication networks. These solutions require intensive offline efforts and therefore are economically expensive. Further, they are generally inefficient when dealing with dynamic attacks. This paper proposes a novel density-based spatial clustering approach for online detection, classification, and data recovery for data manipulation attacks to PMU measurements. The proposed method is purely data-driven and is applicable to simultaneous multi-measurement attacks without requiring additional hardware in the existing infrastructure. The proposed approach is also independent of the conventional state estimation (SE). Comprehensive case studies demonstrate the effectiveness of the proposed method
EXISTING SYSTEM :
? A sensitivity analysis of state estimation residuals on a single GSA phase angle is firstly implemented.
? An identification algorithm using a probing technique is proposed to determine the locations of spoofed PMUs and the ranges of GSA phase shifts.
? Based on the identification results, these GSA phase shifts are determined via an estimation algorithm that minimizes the mismatch between measurements and system states.
? Further, with the attacked PMU data corrected, the system states are recovered. Simulations in unbalanced IEEE 34-bus and 123-bus distribution systems demonstrates the efficiency and accuracy of the proposed method.
DISADVANTAGE :
At the same time, it costs nearly negligible time delay which can mask the action.
Once the attack is successfully implemented, it can bias power system state estimates, induce the regional control center to issue detrimental control actions, cause less economic power dispatch, and result in the adversary’s monetary gains and outages and/or damages.
With sufficient knowledge of a power system, an adversary can maximize damages to the grid without being detected by the conventional bad data detection scheme.
PROPOSED SYSTEM :
? This study proposes a method to recover the missing or abnormal amplitude data in PMU measurements (i.e. the active power, reactive power, positive sequence current, and voltage amplitude), based on the historical PMU data obtained from both ends of the line, which is independent of the transmission line parameters and the phase angle that may be influenced by synchronisation.
? The model of data recovery is established , and the recovery method, which recovers the voltage amplitude, active power, reactive power, and current amplitude in sequence, using historical amplitude data to calculate related recovery coefficients is proposed
ADVANTAGE :
? We can perform these kinds of attacks by adding a minor constant or a slope to the original data packet which is effective and costs the least effort from the attacker’s point of view.
? A security perspective, by tampering with the power system measurement data and affecting the normal dispatching operation of the power system, such attacks can cause the grid control/dispatch center to issue detrimental commands.
? In this way, a cyber-terrorist can directly threaten the power supply and even national security.
? The attackers, therefore, have sufficient motivations to perform such malicious attacks.
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