Suhan Zhang

Dr. Suhan Zhang is a Researcher in the School of Electrical and Electronic Engineering at the University of Sheffield, specializing in power systems engineering and integrated energy systems. His research focuses on optimizing cross-sector energy systems, cybersecurity in cyber-physical infrastructure, and developing advanced simulation and optimization methods for gas-electricity coupling, multi-timescale security analysis, and distributed energy resource management. He leads projects on fast gas flow calculation, dynamic energy flow analysis, and AI-driven approaches for energy storage system vulnerabilities. His work bridges theoretical advancements with practical applications in smart grid technologies and energy market mechanisms.

Key research areas include:

• Integrated electricity-gas-heating systems
• Cyber-physical interdependence analysis
• Optimization under uncertainty
• Physics-informed machine learning
• Energy storage system security
• Multi-scale energy market design

Recent contributions highlight novel methods like semi-implicit simulation approaches for fault propagation analysis, physics-informed neural networks for gas flow modeling, and truthful combinatorial auctions for regulation reserve aggregation. His work is published in top-tier journals and conferences, addressing both foundational and applied challenges in energy systems engineering.