Tag: adaptive

Congratulations to our labmates and collaborators, Keerthiraj Nagaraj, Sheng Zou, Cody Ruben, Surya Dhulipala, Allen Starke, Arturo Bretas, Alina Zare , and Janise McNair!  Their paper, “Ensemble CorrDet with Adaptive Statistics for Bad Data Detection,” was accepted to IET Smart Grid.   The online publication can be found here. Check it out!

Abstract: Smart grid (SG) systems are designed to leverage digital automation technologies for monitoring, control and analysis. As SG technology is implemented in increasing numbers of power systems, SG data becomes increasingly vulnerable to cyber-attacks. Classic analytic physics-model based bad data detection methods may not detect these attacks. Recently, physics-model and datadriven methods have been […]