I work on applying algorithms and developing models for solving real-world problems, especially in Power & Energy field. The research topics include but are not limited to:
Power systems modeling
Power systems dynamics
Power systems operation, optimization, and control
Renewable energy integration
Classic machine learning, deep learning, and reinforcement learning
Georgia Institute of Technology, GA
M.S. in Computer Science (Specialization in machine learning), January 2024 - Now
University of Texas at Arlington, TX
PH.D. in Electrical Engineering, August 2016 - May 2021
Advisor: Prof. Wei-Jen Lee
Huazhong University of Science and Technology, China
M.E. in Electrical Engineering, September 2013 - June 2016
Advisor: Prof. Chengxiong Mao, Prof. Jiming Lu
Huazhong University of Science and Technology, China
B.E. in Electrical Engineering, September 2009 - June 2013
The 2022 best paper award, Journal of Modern Power Systems and Clean Energy (2024)
The 2020 best paper award, Journal of Modern Power Systems and Clean Energy (2021)
“K. R. Rao electrical engineering graduate fellowship” Scholarship, University of Texas at Arlington (2021)
“Mo-Shing Chen” Scholarship, University of Texas at Arlington (2020)
IEEE/IAS Electrical Safety Prevention through Design Student Engineering Education Initiative (2020)
IEEE/IAS Electrical Safety Workshop Best Focus Session Paper Award, IEEE (2018)
Outstanding Graduate Teaching Assistant Award, University of Texas at Arlington (2018)
Outstanding Graduate, Huazhong University of Science and Technology (2013)
Outstanding Undergraduate Student, Huazhong University of Science and Technology (2011 & 2012)
ETAP/Operation Technology, Inc. (owned by Schneider Electric), Irvine, CA
Senior Power Systems/Software Engineer (1/2022 – Now)
Power Systems/Software Engineer (7/2021 – 12/2021)
Research, design, and develop control modules and functions for the generic model of renewable energy resources (wind generator, PV, energy storage systems, fuel cell, STATCOM) in ETAP based on C#, C++, Python, Sqlite, etc. using Visual Studio for power systems static and dynamic studies. The developed functions for dynamic studies include grid-following, grid-forming, droop control, virtual inertia, virtual impedance, fault ride through, etc., which also can be integrated with the microgrid controller and power plant controller in ETAP as the digital twin platform. The developed control modules are released since ETAP 22.0 in 2022 and have been used by many industrial customers.
Develop the wrapper interface in C# for functional mockup unit (FMU) files that can be directly integrated by ETAP control modules. The developed wrapper interface is used by customers like Vestas.
Develop report generation function via Python that can automatically show the descriptions and plots for the results of the Grid Code Study module for renewable power plants in ETAP.
Perform data analysis and visualization of the renewable power plant for battery sizing in Python.
Conduct transient stability studies using PSCAD and ETAP including motor starting for the facility integrated with fuel cell systems under island operation mode.
Conduct code testing and documentation for the developed functions in ETAP. Manage software codes via AccuRev.
Developed the example microgrid controller with active power control function at POI released in ETAP 21.0 in 2021.
Global Energy Interconnection Research Institute North America (GEIRINA), San Jose, CA
Summer Research Intern - AI & Systems Analytics (5/2021 – 8/2019)
Researched and developed deep reinforcement learning-based algorithms for solving the grid-level least-cost dispatching (AC optimal power flow problem) in Python using TensorFlow, scikit-learn, numpy, etc.
PH. D. Projects, University of Texas at Arlington, 2016-2021
Machine learning application
1. Deep reinforcement learning based methods to solve the AC optimal power flow using Python, TensorFlow, etc.: (1) Proposed to apply imitation learning to initialize the neural network, which is formulated as supervised regression tasks. (3) Adopted convolutional neural network (CNN) and proximal policy optimization (PPO) for solving the real-time AC optimal power flow considering uncertainties including power grid topology changes with N-1 contingencies. (4) Created a CNN-based classifier to identify the feasible/infeasible grid operation conditions.
2. Dynamic equivalent modeling for large-scale wind farms using Matlab and Simulink: Developed the robust and accurate dynamic equivalent model for wind farms using unsupervised clustering and heuristic optimization.
3. Arcing fault detection using Matlab and Python: Applied the neural network-based classifier for high-speed arcing fault detection using light spectral data, which was collected via experiments in the lab.
Optimization
1. Implemented the AC optimal power flow algorithm based on semi-definite programming for hybrid AC and DC power grids. The optimization was based on CVX and YALMIP in Matlab using the Mosek solver.
Data acquisition and monitoring system design
1. Participated the design of the real-time monitoring system for the petrochemical power plant substation and wind generators using NI-Labview and FPGA.
M. S. Projects, Huazhong University of Science and Technology, 2013-2016
Power systems modeling
1. Designed a novel Control Strategy in the Current Source Converter Based Excitation System for synchronous generators.
2. Participated in the design of the Industrial Prototype of the Three-phase Voltage Source Converter Based Excitation System for synchronous generators based on the DSP TI-28335 chip using C programming.
Reviewer (Web of Science Core Collection)
Being an active reviewer for IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, IEEE Transactions on Industry Applications, IEEE Transactions on Sustainable Energy, IEEE Transactions on Energy Conversion, IET Generation, Transmission & Distribution, Electric Power System Research, International Journal of Electrical Power and Energy Systems, IEEE Open Access Journal of Power and Energy, CSEE Journal of Power and Energy Systems, Journal of Wind Engineering & Industrial Aerodynamics, IEEE PES conferences, IEEE CDC, etc.
Chair - IEEE industry applications society University of Texas-Arlington student chapter (2020-2021)
IEEE Member
Introduction to power systems simulation-overview
Date: Nov. 2022
Sponsor: IEEE Black Hills IAS/PES Chapter
Location: Virtual/South Dakota School of Mines and Tech, Rapid City, South Dakota
EE 3302 - Fundamentals of power systems, teaching assistant, University of Texas at Arlington, TX
EE 3310 - Advanced microcontroller, teaching assistant, University of Texas at Arlington, TX
EE 5308 - Power systems modeling and analysis, teaching assistant, University of Texas at Arlington, TX
EE 5374 - Protective relay systems, teaching assistant, University of Texas at Arlington, TX
EE 5377 - Programmable logic controllers (PLC), teaching assistant, University of Texas at Arlington, TX
EE 5378 - Power quality, teaching assistant, University of Texas at Arlington, TX
I like music and concerts, soccer (a gunner and a fan of Messi), swimming, fitness, hiking, road trip, photography, movies, etc.
I play the violin. I was the concertmaster in my undergraduate symphony orchestra from 2011 to 2012.