Date

2018

Document Type

Thesis

Degree

Master of Science

Department

Industrial Engineering

First Adviser

Lawrence V. Snyder

Abstract

In this thesis, we introduce a method to identify the most critical components (e.g., generators, transformers, transmission lines) in an existing electric power grid, that contains renewable (wind) generators. We assume the power system is under threat of intentional attacks. By learning the potentially best attacking plan, the system operator can have a better understanding of the most important components in the system. We use a bilevel optimization model to describe the problem and a decomposition approach to solve the bilevel model by finding maximally disruptive attack plans for attackers who have limited attacking resources. The testing data are based on standard reliability test networks and we formalized the original data with real data collected from Texas by the Electric Reliability Council of Texas (ERCOT). Our results show that the method in this thesis can be used by the operator of the power system to find out critical components and make better defensive plans to improve system security.

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