False Data Injection Attacks Targeting Power System Generation Control/Scheduling and Their Mitigations

Electric power systems are subject to cyberattacks. In this project, we intend to investigate false data injection attacks (FDIAs) targeting the automatic generation control (AGC) and the economic dispatch (ED) of electric power systems. Such a class of attacks may significantly affect the system frequency stability and result in huge economic loss and even catastrophic blackouts. Particularly, we will develop novel FDIA models targeting AGC and ED from the intruder’s perspectives, evaluate the impacts of developed FDIAs on benchmark test systems, and then design effective mitigation methods against those FDIAs from the defender’s viewpoint to reduce the negative impacts of the FDIAs and ensure the secure operation of power grids. The research outcomes will shed light on how we can better defend Canada’s power grids and minimize catastrophic consequences on the security and integrity of the country’s critical infrastructures against potential cyberattacks that are increasing both in frequency and severity.

Faculty Supervisor:

Xiaozhe Wang

Student:

Partner:

Institut de Recherche Hydro-Québec

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Utilities

University:

McGill University

Program: