Travis Hagan | Searcharxiv

arXiv2021

Impacts of Earthquakes on Electrical Grid Resilience

One of the most complex and devastating disaster scenarios that the U.S.~Pacific Northwest region and the state of Oregon faces is a large magnitude Cascadia Subduction Zone earthquake event. The region's electrical grid lacks in resilience against the destruction of a megathrust earthquake, a powerful tsunami, hundreds of aftershocks and increased volcanic activity, all of which are highly probable components of this hazard. This research seeks to catalyze further understanding and improvement of resilience. By systematizing power system related experiences of historical earthquakes, and collecting practical and innovative ideas from other regions on how to enhance network design, construction, and operation, important steps are being taken toward a more resilient, earthquake-resistant grid. This paper presents relevant findings in an effort to be an overview and a useful guideline for those who are also working towards greater electrical grid resilience.

eess.SY↗

arXiv2020

On PMU Data Integrity under GPS Spoofing Attacks: A Sparse Error Correction Framework

Consider the problem of mitigating the impact on data integrity of phasor measurement units (PMUs) given a GPS spoofing attack. We present a sparse error correction framework to treat PMU measurements that are potentially corrupted due to a GPS spoofing attack. We exploit the sparse nature of a GPS spoofing attack, which is that only a small fraction of PMUs are affected by the attack. We first present attack identifiability conditions (in terms of network topology, PMU locations, and the number of spoofed PMUs) under which data manipulation by the spoofing attack is identifiable. The identifiability conditions have important implications on how the locations of PMUs affect their resilience to GPS spoofing attacks. To effectively correct spoofed PMU data, we present a sparse error correction approach wherein computation tasks are decomposed into smaller zones to ensure scalability. We present experimental results obtained from numerical simulations with the IEEE RTS-96 and IEEE 300 test networks to demonstrate the effectiveness of the proposed approach.

eess.SP↗