CAREER: A Hybrid Physics-Based/Data-Driven Modeling and Mitigation Approach for Interdependencies Between the Electric Power, ICT, and Transportation Critical Infrastructures

Cuny City College, New York NY

Investigators

Abstract

Improving the protection and resilience of critical infrastructures (CIs) against natural disasters and manmade threats is an imperative short-term goal. Three highly interdependent CIs are the focus of this research: electric power systems, information and communication technologies (ICT), and electricity- based vehicles/transportation (e-transportation). Network modeling of failure modes and propagation is needed by managers to devise strategies that mitigate the impact of failures across interdependent CIs. Although much progress has been made in network modeling of CIs to date, these efforts fail to capture the complexity of CIs, are based on inadequate or inaccurate assumptions, neglect interdependencies, and are mostly empirical and statistically driven rather than based on principles of physics. The objective of this research is to improve failure and resilience modeling of interdependent CIs. This work will then be expanded using reinforcement learning to aid in decision-making. The outcome will be a framework to account for CI interdependencies that are critical for failure and disaster planning and recovery. Intellectual Merit. The influence graph-based model and reinforcement learning-based interdependency mitigation framework eloquently address a key problem that has long challenged city/infrastructure planners and operators: how to model, forecast, and prevent cascaded failures that propagate through multiple critical infrastructures. Current approaches lack accuracy and the ability to handle complexities and interdependencies. This work applies detailed physics-based bottom-up modeling coupled with the innovative application of reinforcement learning to provide a transformative advancement to the field, resulting in a much more flexible and accurate analysis methodology for use in CI design, management, disaster planning, and recovery. Broader Impact. This project will positively impact society by reducing the operational cost of infrastructures, decreasing the likelihood and impact of blackouts, and improving cities' responses to major disturbances. The educational components will benefit hundreds of students from CUNY and neighboring high schools that enroll significant numbers of students who are underrepresented in STEM fields. This will increase the number of highly trained engineers and scientists with multidisciplinary backgrounds who will have a major role in defining the future of society. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.