Fault Localization and State Estimation of Power Grid under Parallel Cyber-Physical Attacks
Parallel cyber-physical attacks (PCPA) refer to those attacks on power grids by disturbing/cutting off physical transmission lines and meanwhile blocking transmission of measurement data to dwarf or delay the system protection and recovery actions. Such fierce hostile attacks impose critical threats to the modern power grids when there is a fusion of power grids and telecommunication technologies. In this paper, we investigate the fault diagnosis problem of faulty transmission lines under a broader spectrum of PCPA for a linearized (or DC) power flow model. The physical attack mechanism of PCPA includes not only disconnection but also admittance value modification on transmission lines, for example, by invading distributed flexible AC transmission system (D-FACTS). To tackle the problem, we first recover the information of voltage phase angles within the attacked area. Using the information of voltage phase angle and power injection of buses, a graph attention network-based fault localization (GAT-FL) algorithm is proposed to find the locations of the physical attacks. By capitalizing on the feature extraction capability of the GAT on graph data, the fault localization algorithm outperforms the existing results when under cyber attacks, e.g., denial of service (DoS) attacks. A line state identification algorithm is then developed to identify the states of the transmission lines within the attacked area. Specifically, the algorithm restores the power injection of buses within the attacked area and then identities the state of all the transmission lines within the attacked area by solving a linear programming (LP) problem. Experimental simulations are effectiveness of the proposed fault diagnosis algorithms.
Code (0)
등록된 구현이 없습니다.
Tasks
BlockingFault DiagnosisFault localizationGraph AttentionState EstimationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
AI-Enhanced Inverter Fault and Anomaly Detection System for Distributed Energy Resources in Microgrids
The integration of Distributed Energy Resources (DERs) into power distribution systems has made microgrids foundational to grid modernization. These DERs, connected through power electronic inverters, create power electr…
Anomaly DetectionFault DetectionSet-Estimation based Networked Model Predictive Control for Energy Management of Faulty Microgrids
This paper addresses the issue of power flow control for partially faulty microgrids. In microgrid control systems, faults may occur in both electrical and communication layers. This may have severe effects on the operat…
energy managementManagementModel Predictive ControlReal-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks
Diverse fault types, fast re-closures, and complicated transient states after a fault event make real-time fault location in power grids challenging. Existing localization techniques in this area rely on simplistic assum…
Estimating Technical Loss without Power Flows: A Practical, Data-Driven Approach for Loss Estimation in Distribution Grids
Electric grids in low- and middle-income countries (LMICs) across the world face an acute challenge. To support global decarbonisation efforts and raise millions from energy poverty, these grids must shoulder substantial…
Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids
In smart electrical grids, fault detection tasks may have a high impact on society due to their economic and critical implications. In the recent years, numerous smart grid applications, such as defect detection and load…
Defect DetectionFault DetectionFault localizationLoad Forecasting