Siby Jose Plathottam

Siby Jose Plathottam is a Postdoctoral appointee in the Energy Systems and Infrastructure Analysis division. In his Ph.D. dissertation, he applied optimal control theory to determine how to accelerate induction motors with minimal energy losses. His research interests include modeling and controlling energy systems and utilizing Deep learning for power system applications.

At ANL, he worked on the following projects:

• Device level DER Cybersecurity using Machine Learning
• Transmission and Distribution Co-simulation open-source software.
• Controller and power hardware in the loop simulation with power electronic modules and edge AI devices.
• Developing an open-source Python module for simulating the dynamic behavior of solar PV distributed energy resources (DERs) connected to the distribution grid.
• Generating synthetic load curves and load forecasting at Zip code level using Variational Autoencoders (VAEs).
• Identifying electric vehicle charging patterns at the household level by applying clustering algorithms to half-hourly smart meter data.