Abstract

The electric power grid is a complex cyberphysical energy system (CPES) in which information and communication technologies (ICT) are integrated into the operations and services of the power grid infrastructure. The growing number of Internet-of-things (IoT) high-wattage appliances, such as air conditioners and electric vehicles, being connected to the power grid, together with the high dependence of ICT and control interfaces, make CPES vulnerable to high-impact, low-probability load-changing cyberattacks. Moreover, the side-effects of the COVID-19 pandemic demonstrate a modification of electricity consumption patterns with utilities experiencing significant net-load and peak reductions. These unusual sustained low load demand conditions could be leveraged by adversaries to cause frequency instabilities in CPES by compromising hundreds of thousands of IoT-connected high-wattage loads. This article presents a feasibility study of the impacts of load-changing attacks on CPES during the low loading conditions caused by the lockdown measures implemented during the COVID-19 pandemic. The load demand reductions caused by the lockdown measures are analyzed using dynamic mode decomposition (DMD), focusing on the March-to-July 2020 period and the New York region as the most impacted time period and location in terms of load reduction due to the lockdowns being in full execution. Our feasibility study evaluates load-changing attack scenarios using real load consumption data from the New York Independent System Operator (NYISO) and shows that an attacker with sufficient knowledge and resources could be capable of producing frequency stability problems, with frequency excursions going up to 60.5 Hz and 63.4 Hz, when no mitigation measures are taken.

Highlights

  • The wide-scale deployment of information, sensing, and communication technologies in electric power systems (EPS) contribute to various power grid functionalities

  • ANALYZING THE FEASIBILITY OF LOAD-CHANGING ATTACKS: EXPERIMENTAL SETUP & RESULTS we present the experimental setup used for evaluating the feasibility of a load-changing attack in a system such as New York Independent System Operator (NYISO) during low load demand periods such as the ones encountered during the COVID-19 pandemic

  • WORK This article explores the feasibility of load-changing attacks in cyberphysical energy systems (CPES) that experience abnormal low loading conditions caused by events such as the COVID-19 pandemic and its corresponding lockdown measures

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Summary

Introduction

The wide-scale deployment of information, sensing, and communication technologies in electric power systems (EPS) contribute to various power grid functionalities. The roll-out of customer-end IoT-controllable high-wattage devices and distributed energy resources (DERs) unlocks new vulnerabilities on the demand-side of CPES and opens new avenues for adversaries to launch large-scale coordinated remote attacks on power system’s assets. DERs or modern controllable loads use IoT devices to coordinate their operations with other CPES (e.g., via IoT-based smart meters or other home assistants such as Amazon Echo and Google Home). These IoT interfaces become great attack vectors due to the countless vulnerabilities engendered by the complex IoT supply chains. Firmware updates are another source of contamination [2], making

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