Modelling and analysis on smart grid against smart attacks

Modern power systems worldwide are facing a rising appeal for the upgrade to a highly intelligent generation of electricity networks commonly known as the Smart Grid. Advanced monitoring and control systems like Supervisory Control And Data Acquisition (SCADA) and Advanced Metering Infrastructure (AMI) systems have been widely deployed and management based on them provides more flexible and achievable optimal control of power generation, transmission and distribution. However, the growing integration of power system with communication networks also brings increasing challenges to the security of the modern power grid, from both cyber and physical space. Malicious attackers can take advantage of the increased access to the monitoring and control of the system and exploit some of the inherent structural vulnerability of power grids. Motivated by these security challenges, the goal of this thesis is to facilitate the understanding of power grid outages and blackouts triggered by these attacks, to analyze the cascading process that leads to the impactful events, and to support the decision making in defense and protection for a reliable and secure Smart Grid around the corner. Simulation results from real-world power system benchmarks have been analytically discussed from both the spatial and temporal perspectives and important decision-support information have been revealed through several chapters of the thesis. This research is part of an ongoing National Science Foundation (NSF) funded Smart Grid security project led by Dr. Haibo He, Dr. Yan (Lindsay) Sun from the Electrical Engineering Department and Dr. Peter August from the Natural Resources Science Department, all at the University of Rhode Island