Analysis of cyber attacks in power grids with increasing renewable energy penetration

Abstract

With the application of advanced computer and communication technologies, traditional power systems are converting to cyber-physical power systems. [1] Several secondary systems, like SCADA (Supervisory Control and Data Acquisition), WAMS (Wide Area Monitoring System), AMI (Advanced Metering Infrastructure), and smart substations, are the main cyber-physical subsystems that could be vulnerable to cyber-attacks. [1], [3] Mathematically modeled cyber-attack types such as FDIA (False Data Injection Attack) [1], [2], [3], [4], DoS (Denial of Service) [1], [3], replay attacks, etc. can be modeled using the PSCAD power system model with the addition of renewable power source models to the system. The goal of this project is to develop a PSCAD power system model with increasing renewable power sources, simulate the different kinds of cyber-attacks mentioned above in the PSCAD power system model, collect faulty data, and develop a deep learning model to detect and act against the cyber-attacks.