Attack Identification and Correction for PMU GPS Spoofing in Unbalanced Distribution Systems

Zhang, Ying; Wang, Jianhui; Liu, Jianzhe

doi:10.1109/tsg.2019.2937554

Cited by 48 publications

(28 citation statements)

References 34 publications

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“…The input data errors are also discussed here. The data error management is a critical part during the service restoration process due to the possible failure or malfunction of DMS and SCADA systems [29]. For example, the input data errors during the model formulation can lead to a sub-optimal or infeasible solution, such as the system parameter errors, geographic information errors and available resources information errors.…”

Section: F Co-optimization Of Model With Data Uncertaintymentioning

confidence: 99%

Sequential Disaster Recovery Model for Distribution Systems With Co-Optimization of Maintenance and Restoration Crew Dispatch

Zhang

et al. 2020

IEEE Trans. Smart Grid

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To efficiently restore electricity customers from a large-scale blackout, this paper proposes a novel mixedinteger linear programing (MILP) model for the optimal disaster recovery of power distribution systems. In the proposed recovery scheme, the maintenance crews (MCs) are scheduled to repair damaged components, and the restoration crews (RCs) are dispatched to switch on the manual switches. Then, the MC and RC dispatch models are integrated into the disaster recovery scheme, which will generate an optimal sequence of control actions for distributed generation (DG), controllable load, and remote/manual switches. Besides, to address the time scale related challenges in the model formulation, the technical constraints for system operation are investigated in each energization step rather than time step, hence the co-optimization problem is formulated as an "event-based" model with variable time steps. Consequently, the disaster recovery, MC dispatch and RC dispatch are properly cooperated, and the whole distribution systems can be restored step by step. Last, the effectiveness of the co-optimization model is validated in the modified IEEE 123 bus test distribution system. 1

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Section: F Co-optimization Of Model With Data Uncertaintymentioning

confidence: 99%

Sequential Disaster Recovery Model for Distribution Systems With Co-Optimization of Maintenance and Restoration Crew Dispatch

Zhang

et al. 2020

IEEE Trans. Smart Grid

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“…We will show that the third term comprising M is full-rank, and therefore, M is invertible. The third term in M can be written as shown in (20).…”

Section: A Minimization With Respect To Statementioning

confidence: 99%

“…Various threat scenarios, security gaps, and mitigation strategies in relation to TSAs have been assessed in [3] and [4]. Specific selected works representing effects and mitigation of GPS spoofing attacks in power systems include [5] - [20] and these are reviewed next.…”

Section: Introductionmentioning

confidence: 99%

“…A sparse error correction for PMU data under GPS spoofing attacks is presented in [19]. A novel GPS spoofing identification and correction algorithm for SE in unbalanced distribution grids is developed in [20]. References [16] - [20] pertain to a static SE setup, whereby a set of measurements from a particular time instant is processed to produce a state estimate corresponding to that time instant.…”

Section: Introductionmentioning

confidence: 99%

“…A novel GPS spoofing identification and correction algorithm for SE in unbalanced distribution grids is developed in [20]. References [16] - [20] pertain to a static SE setup, whereby a set of measurements from a particular time instant is processed to produce a state estimate corresponding to that time instant. A dynamic SE model under GPS spoofing based on the swing equation is introduced in [21], where the presence of attack is detected using a generalized likelihood ratio test.…”

Section: Introductionmentioning

confidence: 99%

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Multi-period Power System State Estimation with PMUs Under GPS Spoofing Attacks

Risbud

Gatsis

Taha

2020

Journal of Modern Power Systems and Clean Energy

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This paper introduces a dynamic network model together with a phasor measurement unit (PMU) measurement model suitable for power system state estimation under spoofing attacks on the global positioning system (GPS) receivers of PMUs. The spoofing attacks may introduce time-varying phase offsets in the affected PMU measurements. An algorithm is developed to jointly estimate the state of the network, which amounts to the nodal voltages in rectangular coordinates, as well as the time-varying attacks. The algorithm features closedform updates. The effectiveness of the algorithm is verified on the standard IEEE transmission networks. It is numerically shown that the estimation performance is improved when the dynamic network model is accounted for compared with a previously reported static approach.

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Novel trends in resilience assessment of a distribution system using synchrophasor application: A literature review

Sonal

Ghosh

2021

Int Trans Electr Energ Syst

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Summary The gradual sprawl of power system toward smart grid and enhanced integration of distributed energy resources at the distribution end is transforming the conventional distribution system and is eventually making it self‐sustained. The distribution system is thus continuously evolving to prepare itself for any unforeseen natural, man‐made, and complex events. These events may impact the distribution system as high‐impact low‐frequency (HILF) scenarios. The high intensity and widespread damage of the power system due to HILF scenarios necessitate resilience. Resilience analysis aims to identify these region‐specific vulnerabilities of the electricity network and implement appropriate methods to quickly restore the system to its predisturbance state. Further to enhance the network visibility and situational awareness, integration of synchrophasor to resilience is significant. Therefore, synchrophasor technology integrated with resilience provides online wide area visibility of the distribution system. Using synchrophasor for resilience assessment propels an agile network for coordinating accurate and timely analysis of the system parameters. Therefore, understanding the concept of resilience, its evolution, detailed overview, synchrophasor‐based resilience (SBR) methods as well as its applications are necessary. This article outlines the key points of the synchrophasor technology based resilience technique, its significance, and lays a foundation for continuing research in this area. It offers detailed insight into the comprehensive review of this evolving concept. The article majorly focuses on all the aspects of SBR, its necessity in performance evaluation, synchrophasor measurement based resilience enhancement methods, and application of different SBR techniques in the distribution system. A detailed comparative analysis of SBR features, sample efficiency, result accuracy, merits, and demerits based on available literature is provided. Finally, future perspectives are discussed for implementing resilience assessment using synchrophasor technology in the distribution system.

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Attack Identification and Correction for PMU GPS Spoofing in Unbalanced Distribution Systems

Cited by 48 publications

References 34 publications

Sequential Disaster Recovery Model for Distribution Systems With Co-Optimization of Maintenance and Restoration Crew Dispatch

Sequential Disaster Recovery Model for Distribution Systems With Co-Optimization of Maintenance and Restoration Crew Dispatch

Multi-period Power System State Estimation with PMUs Under GPS Spoofing Attacks

Novel trends in resilience assessment of a distribution system using synchrophasor application: A literature review

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