Project 1: Department of Energy - Sponsored by Department of Energy
Project Title: Performance Assessment of Photovoltaic Panels Using Impedance Spectroscopy
Project Period: 09/01/2022 ~ 11/30/2024
The objective of this project is:
- to develop measurements and models for interpretation using a 10W small-scale light intensity-modulated impedance spectroscopy (LIMIS) system,
- to build a scaled-up LIMIS testbed including a whole-module light intensity modulator to test 250W PV panels.
Description of Graphic: The Light Intensity Modular graphic details the process in which light is scaled up involving PV modules using thermal cycling stress concepts.
Project 2: Eversource Project - Sponsored by Eversource Energy Center
Project Title: Development of Cyber-Attack Detection Algorithms using the Smart Inverter and Machine Learning Algorithms
Project Period: 09/01/2023 ~ 5/30/2025
The objective of this project is to develop a technology which assures reliable and resilient power distribution systems during adverse weather and grid conditions, and security events which may impact the utility grid infrastructure.
Description of Graphic: The graphic is representative of several tasks involved in the development of cyber-attack detection algorithms using whle smarter inverters and using the utility grid compromise detection.
Project 3: REP Project - Sponsored by UConn
Project Title: Enhancing the Transient Stability of Inverter-Dominated Power System Through PMU Coordination
Project Period: 06/2024 ~ 5/2025
The objective of this project is to enhance the transient stability of the inverter-dominated power system through coordinated control using phasor measurement unit (PMU) technology
Description of Graphic: The graphic is representative of inverter-dominated power systems from several layers of DER Control and Communication Layers with PMU coordination that starts at the transmission network while using raw data.
Project 4: NIUVT Project - Sponsored by Department of Defense
Project Title: Impedance based Li-Ion Battery Management Systems using Machine Learning
Project Period: 01/2024 ~ 12/2025
The objective of this project is to create a smart Li-Ion battery management system feature using battery cell impedance monitoring and machine learning algorithms.
Description of Graphic: The graphic is representative of Li-Ion battery management system using offline EIS datasets and machine learning algorithms.