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.
Bibliographical noteGenerated from Scopus record by KAUST IRTS on 2022-09-13
ASJC Scopus subject areas
- Computer Science(all)
- Materials Science(all)