海角直播app

Lab Members

Principal Investigator 鈥� Junjian Qi, Ph.D.

Harold C. Hohbach Endowed Assistant Professor in Electrical Engineering, McComish Department of Electrical Engineering and Computer Science, 海角直播app

• Junjian Qi received his B.E. degree in electrical engineering from Shandong University, Jinan, China, in 2008, and his Ph.D. degree in electrical engineering from Tsinghua University, Beijing, China, in 2013.
• He was an assistant professor with the Department of Electrical and Computer Engineering, University of Central Florida, Orlando, from 2017 to 2020 and an assistant professor with the Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, New Jersey, from 2020 to 2023.
• He joined the McComish Department of Electrical Engineering and Computer Science, South Dakota State University, Brookings, in 2023 as the Harold C. Hohbach Endowed Assistant Professor. His research interests include cascading blackouts, microgrid control, cyber-physical system security and synchrophasor.
• Qi was a recipient of the National Science Foundation CAREER Award in 2020; the 2021 Best Paper Award from the Institute of Electrical and Electronics Engineers Transactions on Power Systems; the 2022 Best Paper Award from the Journal of Modern Power Systems and Clean Energy; and the Best Paper Awards from the Institute of Electrical and Electronics Engineers Power and Energy Society General Meetings and Institute of Electrical and Electronics Engineers Power and Energy Society Innovative Smart Grid Technologies Asia. He is an associate editor of Institute of Electrical and Electronics Engineers Transactions on Power Systems and Institute of Electrical and Electronics Engineers Power Engineering Letters.

Team Members

Current Research

Cascading Blackout Simulation, Analysis and Mitigation

Cascading blackouts are complicated sequences of dependent outages that could bring about tremendous economic and social losses. Large-scale cascading blackouts have substantial risk and pose great challenges in simulation, analysis and mitigation. We develop both physics-based and statistical models to simulate, analyze and mitigate cascading failures. In particular, with the support of a National Science Foundation CAREER project, we develop data-driven interaction analysis approaches to help understand the propagation patterns of cascading blackouts and reduce the risk of cascading.

Distributed Microgrid Control

A microgrid can operate either in islanded or grid-connected mode. In grid-connected mode, the distributed generators operate in grid-following mode and inject power into the grid. In islanded mode, the distributed generator controllers usually operate in grid-forming mode to regulate the microgrid voltage and frequency. With the support from National Science Foundation and U.S. Department of Defense, we develop distributed control algorithms to coordinate the distributed generators in either grid-following or grid-forming modes and achieve system-level performance.

Cyber-Physical System Security

With more control and communication integrated into the electric power system, cyber-physical system security is becoming a major concern. We develop application-level methodologies, such as robust estimation methods and machine learning based attack detection, to enhance the attack resiliency of the power system monitoring (e.g., state estimation), protection, and control (e.g., load frequency control, microgrid control) and make sure the key functionalities can still be sustained even under cyber attacks. 

Parameter Identifiability Analysis and Estimation

Accurate models are essential for reliable, stable, and efficient power system operation. North American Electric Reliability Corporation requires that dynamic models be validated with phasor measurement unit data every two years to confirm the accuracy of the planning models. We perform parameter identifiability analysis for the power system dynamic models and develop Bayesian inference and machine learning based methods to calibrate the model parameters using phasor measurement unit data. 

Lab Setup

Controller Hardware-in-the-Loop Microgrid Testbed

This testbed is designed to provide a real-time simulation environment for rigorous testing and validation of various AC/DC microgrid control algorithms. It includes an OPAL-RT OP5707XG real-time simulator, four OP8666 DSP controllers, serial communication interfaces, a host computer, and relays. We have deployed our distributed optimal secondary controls on the hardware-in-the-loop testbed to significantly improve voltage regulation and reactive power sharing.

Programmable Versatile Power Inverters

Our Taraz dual 3-phase programmable inverter systems (rated at 800V DC-link and 16A) can be used for both power and controller hardware-in-the-loop simulations. They feature overvoltage and overcurrent protection, along with an intelliSENS power electronics data acquisition system for real-time analysis. The inverters support customizable bridge topologies and are highly compatibility with various inverter and converter configurations, making them adaptable to diverse power electronics and microgrid applications.

Educational IoT-Based Microgrid Hardware Testbed

A 12-volt educational microgrid hardware system is developed for authentic microgrid control testing, featuring low-voltage design for enhanced safety and cost-effectiveness. The system includes TI inverter boards, digital signal processor control boards, filters, relays, circuit breakers and loads. Raspberry Pis are integrated for user interface management, secondary control, and IoT-based communication, enabling remote monitoring and control.