Finite Time Fault Estimation for Multi-Area Power System under FDI Attack

Authors: qidong  liu
Venue: IEEE_org_ICIST_2024_Conference
Published: 2024-08-21 07:46:09

Abstract: In this paper, we address the problem of finite-time fault estimation for multi-area power systems under false data injection (FDI) attacks. The increasing sophistication of cyber attacks poses significant risks to the reliable operation of power systems, especially when they are geographically distributed and interconnected. We propose a novel fault estimation scheme that guarantees accurate detection of faults within a finite time, despite the presence of FDI attacks. The proposed method leverages a combination of Lyapunov-based analysis and adaptive observers to achieve robust fault estimation. The effectiveness of the approach is demonstrated through theoretical analysis and validated by simulation results, confirming that the proposed estimator is resilient to FDI attacks and ensures timely fault detection across different areas of the power system.

Main paper: 
 i. introduction: 
 The increasing complexity and interconnectivity of modern power systems have made them highly susceptible to cyber attacks, which can have severe consequences for system stability and reliability. Among various types of cyber threats, false data injection (FDI) attacks have emerged as particularly dangerous, as they involve the malicious alteration of measurement data used by system operators to monitor and control the power grid. Such attacks can lead to undetected faults, incorrect system state estimation, and ultimately, catastrophic failures if not properly mitigated [2] .Multi-area power systems, which are composed of interconnected regions, are particularly vulnerable to FDI attacks due to the distributed nature of their control and monitoring systems [5] . In these systems, faults in one area can propagate to other areas, making early and accurate fault detection critical. Traditional fault detection methods, which often rely on asymptotic convergence, may fail to provide timely alerts in the presence of FDI attacks [4] . This highlights the need for fault estimation schemes that can operate within a finite time, ensuring that faults are detected quickly and accurately despite the presence of adversarial actions.Finite-time estimation has gained attention in recent years as an effective approach to addressing the limitations of traditional fault detection methods. Unlike conventional estimation techniques that guarantee asymptotic convergence, finite-time estimation ensures that the fault estimation error converges to zero within a pre-specified finite time. This property is particularly valuable in power systems, where rapid fault detection is essential to prevent cascading failures and maintain system stability [1] [3] .The primary challenge in designing finite-time fault estimators for multi-area power systems under FDI attacks lies in the need to account for both the distributed nature of the system and the adversarial manipulation of data [6] . The estimator must be robust enough to detect faults accurately despite the presence of compromised measurements, while also ensuring that the estimation process is completed within a finite time.To address these challenges, this paper proposes a novel finite-time fault estimation scheme tailored to multi-area power systems under FDI attacks. The proposed approach leverages Lyapunov-based methods to design an adaptive observer that can estimate faults in real-time, even when the system is subjected to malicious data injections. The key contributions of this paper are summarized as follows:1. We develop a finite-time fault estimation scheme that is robust to FDI attacks, ensuring that faults are detected accurately across different areas of the power system. 2. The proposed method employs Lyapunov functions to guarantee the finite-time convergence of the fault estimation error, providing a rigorous theoretical foundation for the approach.II. PROBLEM FORMULATION Consider a multi-area power system represented by the following state-space model:ẋ(t) = Ax(t) + Bu(t) + F f (t) + Ed(t), y(t) = Cx(t) + Df (t) + v(t),where x(t) ∈ R n is the state vector, u(t) ∈ R m is the control input, y(t) ∈ R p is the output vector, f (t) ∈ R q represents the fault vector, and d(t) ∈ R r is the disturbance vector. The matrices A, B, C, D, F , and E are system matrices of appropriate dimensions. The term v(t) denotes the measurement noise.Under FDI attacks, the measurement y(t) is corrupted by an additional term a(t) that represents the injected false data, leading to the observed output: ỹ(t) = y(t) + a(t).The objective is to design a fault estimation scheme that can accurately estimate the fault f (t) within a finite time, despite the presence of the attack a(t). 
 
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