X-INtelligent Grid (XING) Laboratory
XING ("Crossing") seeks to create and innovate cross-disciplinary solutions for next-generation smart grids, overlapping socio-economics, meteorology, AI, and machine learning to address the compound real-world needs. Modern power systems are confronted with degraded and even stranded operational performances subject to growing complexity, uncertainty, and volatility from large-scale integration of renewable and distributed energy resources (DERs). Toward next-generation intelligent grids, our mission is to bridge the gap between energy system research and state-of-the-art data science by utilizing diversified data from weather and renewable generation data, phasor measurement units (PMUs), and advanced metering infrastructure (AMI) systems, etc.
Dr. Ying Zhang (Faculty Homepage)
I am currently an Assistant Professor in the Department of Electrical and Computer Engineering at Oklahoma State University (OSU), Stillwater, OK, U.S. I received my Ph.D. degree in Electrical Engineering at Southern Methodist University (SMU), Dallas, TX, U.S. Before joining OSU, I was a postdoctoral research associate in the U.S. DOE’s Brookhaven National Laboratory (BNL) with the Interdisciplinary Science Department, an Assistant Professor at Montana State University (MSU), and a Visiting Scholar in Cornell University. My research is rooted in power system situational awareness via optimization, machine learning, and artificial intelligence (AI) to develop grid-based interdisciplinary research in climate science, data science, and socio-economics.
Email: y.zhang@okstate.edu Office: 217 South Engineering, Stillwater, OK 74078
Research Interests: Energy and Power Systems, Renewable Integration, AI for Energy, Smart Grid, Grid Resilience and Equity Development Against Climate Change.
04/2024: Three ECE students, Taha Saeed Khan (Advisor: Dr. Nazaripouya) , Ahmad Ali (Advisor: Dr. Cui ), and Sungjoo Chung (Advisor: Dr. Y. Zhang), won the “Best in Group” Award in the OSU 2nd CEAT Graduate Student Research Symposium. Congrats to Taha, Ahmad, and Sungjoo.
04/2024: Sungjoo received the 2024 Dr. Ramakumar Family Energy Scholarship sponsored by the College of Engineering, Architecture and Technology at OSU as one of the two runners-up. Congrats, Sungjoo!
03/2024: Our paper, Addressing Wind Power Forecast Errors in Day-Ahead Pricing With Energy Storage Systems: A Distributionally Robust Joint Chance-Constrained Approach, is accepted by IEEE Transactions on Sustainable Energy (IF: 8.8).
02/2024: Our paper, Cooperative Multi-Agent Deep Reinforcement Learning for Adaptive Decentralized Emergency Voltage Control, is selected as the Best Paper Contest Finalist (Top 5) by the 2024 IEEE PES Innovative Smart Grid Technologies Conference!
02/2024: Our paper, Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method, is accepted by the IEEE PES General Meeting, one of the grandest events in the domain of power and energy systems. Congrats to Sungjoo!
01/2024: Yuanshuo Zhang (23' CUHK) joined the lab as a Ph.D. student. Welcome!
12/2023: Dr. Zhang joined Oklahoma State University (OSU) as an Assistant Professor in the Electrical and Computer Engineering Department.
12/2023: Our paper, Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control, is accepted by IEEE Transactions on Neural Networks and Learning Systems (IF: 10.4).
11/2023: Dr. Zhang is appointed Associate Editor of the journal IET Generation, Transmission & Distribution.
10/2023: Dr. Zhang is appointed Vice Chair of the Awards Subcommittee, IEEE Power and Energy Society (PES) Power System Operation, Planning and Economics Committee (2024-2028).
10/2023: Two papers, Deep Reinforcement Learning-Enabled Adaptive Forecasting-Aided State Estimation in Distribution Systems with Multi-Source Multi-Rate Data & Cooperative Multi-Agent Deep Reinforcement Learning for Adaptive Decentralized Emergency Voltage Control, are accepted by the 2024 IEEE IEEE PES Innovative Smart Grid Technologies Conference.
07/2023: Invited Talk in the Outstanding Dissertation Award Panel of the 2023 IEEE PES General Meeting, "Distribution System Situational Awareness: From Model-Based to Data-Driven and Beyond", please see the slides here . Dr. Zhang's dissertation was officially awarded as the 2023 IEEE Power and Energy Society Outstanding Doctoral Dissertation to recognize the research achievement of Ph.D. students who graduated in 2020-2022 worldwide in the power and energy domain.
06/2023: Our paper, "Artificial Intelligence Applications in Electric Distribution Systems: Post-Pandemic Progress and Prospect", is accepted by Applied Sciences. Congrats Sungjoo!
05/2023: Dr. Zhang started a one-month summer visit at Cornell University, a lot of brainstorming and discussion with Dr. Hsiao-Dong Chiang! Thanks for Dr. Chiang's hospitality.
03/2023: Invited Talk in Women in Data Science 2023 @ University of Calgary, Calgary, Canada. Happy International Women's Day!
01/2023: Sungjoo Chung (22' UIUC) joined the lab as a Ph.D. student. Welcome!
01/2023: Our paper, Off-policy deep reinforcement learning with automatic entropy adjustment for adaptive grid emergency control, is accepted by Electric Power Systems Research!
08/2022: Dr. Ying Zhang joined MSU as an Assistant Professor, in the Electrical and Computer Engineering Department, affiliated with MSU's Energy Research Institute.
Looking for Ph.D. students and visiting scholars: I have one fully-funded Ph.D. position in electrical engineering at OSU. I am looking for self-motivated Ph.D. students with research experiences/interests in
1) distribution system operation with high-level renewable penetration and
2) AI applications in cyber-physical energy systems;
Please send your CV and publications (if applicable) via email: imyingzhang@ieee.org and use “PhD Student Candidate” in the email’s subject line.
Due to the high volume of emails we receive, I may not be able to respond to every inquiry. Your understanding is greatly appreciated. If you don't receive a response, please don't take offense.
Update (01/2023): The 2023 Spring position is filled.
Update (11/2023): The 2024 Spring position is filled, and feel free to check this webpage later for possible openings.
