  High-wattage demand-side appliances such as Plug-in Electric Vehicles (PEVs)
are proliferating. As a result, information on the charging patterns of PEVs is
becoming accessible via smartphone applications, which aggregate real-time
availability and historical usage of public PEV charging stations. Moreover,
information on the power grid infrastructure and operations has become
increasingly available in technical documents and real-time dashboards of the
utilities, affiliates, and the power grid operators. The research question that
this study explores is: Can one combine high-wattage demand-side appliances
with public information to launch cyberattacks on the power grid? To answer
this question and report a proof of concept demonstration, the study scrapes
data from public sources for Manhattan, NY using the electric vehicle charging
station smartphone application and the power grid data circulated by the US
Energy Information Administration, New York Independent System Operator, and
the local utility in New York City. It then designs a novel data-driven
cyberattack strategy using state-feedback based partial eigenvalue relocation,
which targets frequency stability of the power grid. The study establishes that
while such an attack is not possible at the current penetration level of PEVs,
it will be practical once the number of PEVs increases.
