Dr. Mikhak Samadi
Ph.D. degree in electrical and computer engineering, from the University of Ottawa, Canada, in 2022. Her research interests include smart grid applications, demand response, game theory, optimization models, machine learning, and data science.
Siavash Hosseini
Ph.D. student, He is developing a scalable model for microgrid reconfiguration and energy management. This involves creating a data-driven graph machine learning model to predict system responses and plan power flow contingencies in the reduced-order microgrid.
Narges Fatemi
Ph.D. student, She is developing an efficient and enhanced peer-to-peer data exchange system for heterogeneous Distributed Energy Resources (DERs) using autoregressive large language models to address technical, interoperability, and security challenges.
Alireza Rajabi
Ph.D. student, He is developing a bidirectional active cell balancing system for a hybrid battery and supercapacitor setup, enhanced with model predictive control to manage sudden and high-frequency load demands from the EV powertrain.
Behrad Jamadi
M.Sc. student, He is developing a decentralized charge session management system and an edge OCPP 2.0.1 server compatible with ISO 15118-20, utilizing advanced robust distributed optimization techniques to optimize EV energy resource usage within an energy management system.
Baturay Onural
M.Sc. student, He is developing a modular IoT board designed for EVSE energy management applications, integrating a Wi-SUN module to enable efficient and reliable mesh networking, WebSocket connectivity, and real-time data imputation.
Maryam Bazyari
M.Sc. student, She is constructing data-driven digital twins for grid-forming, grid-following, and bidirectional inverters, utilizing a state-based mechanism to integrate multiple digital twins in both series and parallel configurations.
Amine Kraiem
M.Sc. student, He is developing a battery management system to actively manage charge/discharge cycles and monitor cell voltage, state of charge (SoC), state of health (SoH), power, and thermal limits for specific electrodes in LiFePO4 and EDLC supercapacitor materials, aiming to optimize energy density and cross-validate the results using FEM simulations.
Capstone Group 2024
Fatima-Ezzahraa Mouaraf
Guitri Ngoune Fouatia
Mohamed Laliam
Amélia Vachon
Serge Tsongo
A smart energy management system using fuzzy logic as the supervisory modulator control is designed for integration into electric scooters. This system will facilitate the dynamic optimization of energy flow between batteries and supercapacitors.