Special Session 22
Privacy-preserving Distributed Optimization Methods of Modern Power System Considering Flexible Power Resources
With the large-scale integration of distributed energy resources (DERs), the operational paradigm of modern power system is undergoing a fundamental transformation. Conventional centralized optimization framework may increasingly face the challenges of privacy leakage, high communication and computation burden, and limited scalability. Meanwhile, the integration of inter-temporal flexible resources (e.g., energy storage), system multiple uncertainties, and potential external cyber attacks further increase operational risks and scheduling complexity. In this context, distributed optimization provides an effective solution by enabling scalable, reliable, and privacy-aware coordination among various DERs. This special session focuses on privacy-preserving distributed optimization methods for modern power systems under uncertainty, covering flexible resource coordination, market participation, data-driven approaches, and practical applications in transmission, distribution, and integrated energy systems. Suggested topics include, but are not limited to:(1) Distributed optimization and operation methods for modern power system under uncertainty
(2) Distributed coordination of flexible power resources (energy storage, demand response, et al)
(3) Privacy-aware trading and bidding strategies in electricity market
(4) AI-based data-driven distributed optimization methods
(5) Differential privacy, secure computation, and encryption techniques in power system optimization
(6) Practical application in transmission system, distribution system, and integrated energy system
Chairs:
Dr. Xizhen Xue, Nanyang Technological University, Singapore
Xizhen Xue receives the B.E. degree and Ph.D. degrees in electrical engineering from the Huazhong University of Science and Technology, Wuhan, China, in 2019 and 2024, respectively. From 2023 to 2024, he was a Visiting Research Scholar with the Department of Electrical and Computer Engineering, Clarkson University, Potsdam, NY, USA. He is currently a Research Fellow with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His current research interests include approximate dynamic programming, distributed optimization algorithm, energy storage scheduling and planning, and integrated energy systems.
Assoc. Prof. Yumin Zhang, Shandong University of Science and Technology, China
Dr. Yumin Zhang is an associate professor and postgraduate supervisor in Shandong University of Science and Technology (China), holding a PhD in electrical engineering from Shandong University (China). She is a member of IEEE and serves as the session chair and track chair for the Industry Applications Society’s international conferences, and is an editorial board member and reviewer for multiple prestigious academic journals.
Dr. Zhang’s research interests include economic operation of power systems, low-carbon optimization of integrated energy systems, electricity market, demand-side response, and distribution systems and their automation. She has led numerous significant research projects, including National Natural Science Foundation projects and key research topics for State Grid Corporation of China.
She has published over 60 academic papers in journals and international conferences, with several high-impact and highly cited papers. Dr. Zhang has received many honors, including “Best Conference Paper” and “Outstanding Reviewer.” She holds more than 20 national invention patents and has contributed to several monographs and technical standards. She was awarded the second prize of Shandong Electric Power Science and Technology Progress Award.
Assist. Prof. Wenlong Liao, University of of Leicester, UK
Wenlong Liao (Fellows of MSCA, JSPS, DAAD AI-net) received his Bachelor's, Master's, and PhD degrees from China Agricultural University, Tianjin University, and Aalborg University, respectively. From Aug. 2023 to Mar. 2025, he was a postdoc with the Ecole Polytechnique Federale de Lausanne (EPFL). He was a visiting researcher at the University of Hong Kong, Tokyo Institute of Technology in Japan, and TU Dortmund University in Germany. He is currently an assistant Professor at University of Leicester. His current research interests include smart grids, machine learning, and renewable energy.
Dr. Xu Liu, Imperial College London, UK
Dr. Xu Liu received the degree of Doctor of Philosophy in Engineering from Tsinghua University in 2024. In 2022, He was a Visiting Fellow in the JC STEM Lab of Innovative Thermo-Fluid Science of the Department of Mechanical Engineering at City University of Hong Kong. Currently, he serves as a Research Associate in the Clean Energy Processes (CEP) Laboratory of the Department of Chemical Engineering at Imperial College London. His research interests include the optimal configuration and coordinated operation of distributed energy systems, and the active regulation of multi-energy storage systems.
Dr. Feng An, The University of Queensland, Australia
Dr Feng (Chris) An completed his Ph.D. degree in Electrical Engineering at the Tsinghua University in 2023. He joined the Power & Energy Systems Research Group with the School of Electrical Engineering and Computer Science at the University of Queensland in 2024. His research interests include renewable energy power conversion, topology and control of power electronic converters, optimized operation and modeling of power systems integrating power electronic equipment. He is also the reviewer of many top journals, such as: IEEE Transactions on Power Electronics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Power System, etc. Dr. Feng made the Stanford/Elsevier Top 2% Scientists List 2024.