Published by: Institute of Artificial Intelligence and Information Fusion

 Edited by: Wang Xiangyu

WUST News — Researchers from the Institute of Artificial Intelligence and Information Fusion at Wuhan University of Science and Technology (WUST) have made significant advances in the interdisciplinary field of distributed optimization and smart grids. Their work tackles critical challenges in areas like privacy-preserving collaborative computing, with results published in several top-tier international journals for control science and energy informatics.

Associate Professor Liu Bing led a study published as a full-length article in IEEE Transactions on Automatic Control—one of the two leading journals in control science. The paper, titled “Cryptography-Based Privacy-Preserving Method for Distributed Optimization over Time-Varying Directed Graphs with Enhanced Efficiency,” addresses widespread privacy leakage risks during distributed optimization. Liu and co-author Professor Chai Li of Zhejiang University developed an innovative AES encryption-based algorithm that effectively balances privacy security and computational efficiency in time-varying directed networks. This represents a major step forward in distributed collaborative optimization theory.

Notably, this is the third full-length paper WUST has published in IEEE TAC, each originating from the institute—a clear indicator of its sustained influence in control theory.

Building on this theoretical foundation, Liu Bing and Associate Professor Wu Han extended the privacy-preserving distributed optimization framework to energy cyber-physical systems. Focusing on practical smart grid applications such as economic dispatch and secondary frequency/voltage control, they designed a suite of privacy-aware cooperative optimization algorithms with strong real-world potential. Their applied work has appeared in three papers in IEEE Transactions on Smart Grid and two in IEEE Transactions on Industrial Informatics, offering innovative solutions for building secure, efficient, and reliable smart grid operating systems.

These systematic research achievements have also attracted national funding. In 2025, Liu Bing and Wu Han each secured General Program grants from the National Natural Science Foundation of China for the projects “Privacy-Preserving Distributed Optimization Theory and Its Application in Smart Grid Energy Management” and “Vulnerability Assessment and Security Regulation Mechanisms for Distribution Networks with High Penetration of Renewable Energy in Complex Scenarios”.

This series of breakthroughs underscores WUST’s leading role in cross-disciplinary research linking artificial intelligence and energy systems. It provides a solid theoretical and technical foundation for further organized scientific research, supporting national energy strategy and digital transformation. Moving forward, the institute will continue to address pressing national priorities in AI and global frontiers, fostering deeper integration of artificial intelligence with new energy systems to help WUST produce further internationally impactful innovations. (Institute of Artificial Intelligence and Information Fusion)