Cyber security defence strategies of distribution synchrophasor in smart grids

In smart grids, the data collected by Phasor Measurement Units (PMUs) is crucial to the daily operation and control of the grid, but it has been demonstrated that PMU data is highly vulnerable to cyber-attacks where the data is corrupted when being transmitted to the Local Control Centre (LCC).

This project aims to design and develop a lightweight deep learning system that can be efficiently deployed on resource-constrained relay devices between PMUs and the LCC to support real-time data attack detection. The techniques will be wrapped into ready-to-use software, followed by thorough evaluations of its accuracy, efficiency, and robustness in production environments.

Industry Collaborators: NOJA Power