Visible to the public Risk analysis of GPS-dependent critical infrastructure system of systems

TitleRisk analysis of GPS-dependent critical infrastructure system of systems
Publication TypeConference Paper
Year of Publication2014
AuthorsChen, K.Y., Heckel-Jones, C.A.C., Maupin, N.G., Rubin, S.M., Bogdanor, J.M., Zhenyu Guo, Haimes, Y.Y.
Conference NameSystems and Information Engineering Design Symposium (SIEDS), 2014
Date PublishedApril
KeywordsClocks, critical infrastructure, critical infrastructures, Department of Energy, electric phasor measurement units, Electricity, electricity subsector, electricity-dependent critical infrastructure sectors, Global Positioning System, GPS, GPS timing, GPS-dependent CI sectors, GPS-dependent critical infrastructure system, Modeling, phasor measurement, phasor measurement units, PMU, risk analysis, risk analysis methodology, risk management, smart power grids, SmartGrid, SmartGrid initiative, SoS, system of systems, Systems Engineering, US Department of Homeland Security, US electric grid
Abstract

The Department of Energy seeks to modernize the U.S. electric grid through the SmartGrid initiative, which includes the use of Global Positioning System (GPS)-timing dependent electric phasor measurement units (PMUs) for continual monitoring and automated controls. The U.S. Department of Homeland Security is concerned with the associated risks of increased utilization of GPS timing in the electricity subsector, which could in turn affect a large number of electricity-dependent Critical Infrastructure (CI) sectors. Exploiting the vulnerabilities of GPS systems in the electricity subsector can result to large-scale and costly blackouts. This paper seeks to analyze the risks of increased dependence of GPS into the electric grid through the introduction of PMUs and provides a systems engineering perspective to the GPS-dependent System of Systems (S-o-S) created by the SmartGrid initiative. The team started by defining and modeling the S-o-S followed by usage of a risk analysis methodology to identify and measure risks and evaluate solutions to mitigating the effects of the risks. The team expects that the designs and models resulting from the study will prove useful in terms of determining both current and future risks to GPS-dependent CIs sectors along with the appropriate countermeasures as the United States moves towards a SmartGrid system.

DOI10.1109/SIEDS.2014.6829911
Citation Key6829911